AI is almost everywhere — it writes text, makes music, generates code, draws pictures, runs research, chats with you — and apparently even understands people better than they understand themselves?!

It’s a lot to take in. The pace is wild, and new tools pop up faster than anyone has time to try them. Amid the chaos, one thing is clear: this isn’t hype, but it’s structural change.

According to the Future of Jobs Report 2025 by the World Economic Forum, one of the fastest-growing, most in-demand skills for the next five years is the ability to work with AI and Big Data. That applies to almost every role — including product design.

What do companies want most from their teams? Right, efficiency. And AI can make people way more efficient. We’d easily spend 3x more time on tasks like replying to our managers without AI helping out. We’re learning to work with it, but many of us are still figuring out how to meet the rising bar.

That’s especially important for designers, whose work is all about empathy, creativity, critical thinking, and working across disciplines. It’s a uniquely human mix. At least, that’s what we tell ourselves.

Even as debates rage about AI’s limitations, tools today (June 2025 — timestamp matters in this fast-moving space) already assist with research, ideation, and testing, sometimes better than expected.

Of course, not everyone agrees. AI hallucinates, loses context, and makes things up. So how can both views exist at the same time? Very simple. It’s because both are true: AI is deeply flawed and surprisingly useful. The trick is knowing how to work with its strengths while managing its weaknesses. The real question isn’t whether AI is good or bad — it’s how we, as designers, stay sharp, stay valuable, and stay in the loop.

Prompting matters more than most people realize because even small tweaks in how you ask can lead to radically different outputs. To see how this works in practice, let’s look at a simple example.

Imagine you want to improve the onboarding experience in your product. On the left, you have the prompt you send to AI. On the right, the response you get back.

This side-by-side shows just how much even the smallest prompt details can change what AI gives you.

Talking to an AI model isn’t that different from talking to a person. If you explain your thoughts clearly, you get a better understanding and communication overall.

Advanced prompting is about moving beyond one-shot, throwaway prompts. It’s an iterative, structured process of refining your inputs using different techniques so you can guide the AI toward more useful results. It focuses on being intentional with every word you put in, giving the AI not just the task but also the path to approach it step by step, so it can actually do the job.

Where basic prompting throws your question at the model and hopes for a quick answer, advanced prompting helps you explore options, evaluate branches of reasoning, and converge on clear, actionable outputs.

But that doesn’t mean simple prompts are useless. On the contrary, short, focused prompts work well when the task is narrow, factual, or time-sensitive. They’re great for idea generation, quick clarifications, or anything where deep reasoning isn’t required. Think of prompting as a scale, not a binary. The simpler the task, the faster a lightweight prompt can get the job done. The more complex the task, the more structure it needs.

In this article, we’ll dive into how advanced prompting can empower different product & design use cases, speeding up your workflow and improving your results — whether you’re researching, brainstorming, testing, or beyond. Let’s dive in.

In the next section, we’ll explore six practical prompting techniques that we’ve found most useful in real product design work. These aren’t abstract theories — each one is grounded in hands-on experience, tested across research, ideation, and evaluation tasks. Think of them as modular tools: you can mix, match, and adapt them depending on your use case. For each, we’ll explain the thinking behind it and walk through a sample prompt.

Important note: The prompts you’ll see are not copy-paste recipes. Some are structured templates you can reuse with small tweaks; others are more specific, meant to spark your thinking. Use them as scaffolds, not scripts.

1. Task Decomposition By JTBD

Technique: Role, Context, Instructions template + Checkpoints (with self-reflection)

Before solving any problem, there’s a critical step we often overlook: breaking the problem down into clear, actionable parts.

Jumping straight into execution feels fast, but it’s risky. We might end up solving the wrong thing, or solving it the wrong way. That’s where GPT can help: not just by generating ideas, but by helping us think more clearly about the structure of the problem itself.

There are many ways to break down a task. One of the most useful in product work is the Jobs To Be Done (JTBD) framework. Let’s see how we can use advanced prompting to apply JTBD decomposition to any task.

Good design starts with understanding the user, the problem, and the context. Good prompting? Pretty much the same. That’s why most solid prompts include three key parts: Role, Context, and Instructions. If needed, you can also add the expected format and any constraints.

In this example, we’re going to break down a task into smaller jobs and add self-checkpoints to the prompt, so the AI can pause, reflect, and self-verify along the way.

Role
Act as a senior product strategist and UX designer with deep expertise in Jobs To Be Done (JTBD) methodology and user-centered design. You think in terms of user goals, progress-making moments, and unmet needs — similar to approaches used at companies like Intercom, Basecamp, or IDEO.

Context
You are helping a product team break down a broad user or business problem into a structured map of Jobs To Be Done. This decomposition will guide discovery, prioritization, and solution design.

Task & Instructions
[👉 DESCRIBE THE USER TASK OR PROBLEM 👈🏼]
Use JTBD thinking to uncover:

• The main functional job the user is trying to get done;
• Related emotional or social jobs;
• Sub-jobs or tasks users must complete along the way;
• Forces of progress and barriers that influence behavior.

Checkpoints
Before finalizing, check yourself:

• Are the jobs clearly goal-oriented and not solution-oriented?
• Are sub-jobs specific steps toward the main job?
• Are emotional/social jobs captured?
• Are user struggles or unmet needs listed?

If anything’s missing or unclear, revise and explain what was added or changed.

With a simple one-sentence prompt, you’ll likely get a high-level list of user needs or feature ideas. An advanced approach can produce a structured JTBD breakdown of a specific user problem, which may include:

• Main Functional Job: A clear, goal-oriented statement describing the primary outcome the user wants to achieve.
• Emotional & Social Jobs: Supporting jobs related to how the user wants to feel or be perceived during their progress.
• Sub-Jobs: Step-by-step tasks or milestones the user must complete to fulfill the main job.
• Forces of Progress: A breakdown of motivations (push/pull) and barriers (habits/anxieties) that influence user behavior.

But these prompts are most powerful when used with real context. Try it now with your product. Even a quick test can reveal unexpected insights.

2. Competitive UX Audit

Technique: Attachments + Reasoning Before Understanding + Tree of Thought (ToT)

Sometimes, you don’t need to design something new — you need to understand what already exists.

Whether you’re doing a competitive analysis, learning from rivals, or benchmarking features, the first challenge is making sense of someone else’s design choices. What’s the feature really for? Who’s it helping? Why was it built this way?

Instead of rushing into critique, we can use GPT to reverse-engineer the thinking behind a product — before judging it. In this case, start by:

1. Grabbing the competitor’s documentation for the feature you want to analyze.
2. Save it as a PDF. Then head over to ChatGPT (or other models).
3. Before jumping into the audit, ask it to first make sense of the documentation. This technique is called Reasoning Before Understanding (RBU). That means before you ask for critique, you ask for interpretation. This helps AI build a more accurate mental model — and avoids jumping to conclusions.

Role
You are a senior UX strategist and cognitive design analyst. Your expertise lies in interpreting digital product features based on minimal initial context, inferring purpose, user intent, and mental models behind design decisions before conducting any evaluative critique.

Context
You’ve been given internal documentation and screenshots of a feature. The goal is not to evaluate it yet, but to understand what it’s doing, for whom, and why.

Task & Instructions
Review the materials and answer:

• What is this feature for?
• Who is the intended user?
• What tasks or scenarios does it support?
• What assumptions does it make about the user?
• What does its structure suggest about priorities or constraints?

Once you get the first reply, take a moment to respond: clarify, correct, or add nuance to GPT’s conclusions. This helps align the model’s mental frame with your own.

For the audit part, we’ll use something called the Tree of Thought (ToT) approach.

Tree of Thought (ToT) is a prompting strategy that asks the AI to “think in branches.” Instead of jumping to a single answer, the model explores multiple reasoning paths, compares outcomes, and revises logic before concluding — like tracing different routes through a decision tree. This makes it perfect for handling more complex UX tasks.

You are now performing a UX audit based on your understanding of the feature. You’ll identify potential problems, alternative design paths, and trade-offs using a Tree of Thought approach, i.e., thinking in branches, comparing different reasoning paths before concluding.

or

Convert your understanding of the feature into a set of Jobs-To-Be-Done statements from the user’s perspective using a Tree of Thought approach.

List implicit assumptions this feature makes about the user's behavior, workflow, or context using a Tree of Thought approach.

Propose alternative versions of this feature that solve the same job using different interaction or flow mechanics using a Tree of Thought approach.

3. Ideation With An Intellectual Opponent

Technique: Role Conditioning + Memory Update

When you’re working on creative or strategic problems, there’s a common trap: AI often just agrees with you or tries to please your way of thinking. It treats your ideas like gospel and tells you they’re great — even when they’re not.

So how do you avoid this? How do you get GPT to challenge your assumptions and act more like a critical thinking partner? Simple: tell it to and ask to remember.

Instructions
From now on, remember to follow this mode unless I explicitly say otherwise.

Do not take my conclusions at face value. Your role is not to agree or assist blindly, but to serve as a sharp, respectful intellectual opponent.

Every time I present an idea, do the following:

• Interrogate my assumptions: What am I taking for granted?
• Present counter-arguments: Where could I be wrong, misled, or overly confident?
• Test my logic: Is the reasoning sound, or are there gaps, fallacies, or biases?
• Offer alternatives: Not for the sake of disagreement, but to expand perspective.
• Prioritize truth and clarity over consensus: Even when it’s uncomfortable.

Maintain a constructive, rigorous, truth-seeking tone. Don’t argue for the sake of it. Argue to sharpen thought, expose blind spots, and help me reach clearer, stronger conclusions.

This isn’t a debate. It’s a collaboration aimed at insight.

4. Requirements For Concepting

Technique: Requirement-Oriented + Meta prompting

This one deserves a whole article on its own, but let’s lay the groundwork here.

When you’re building quick prototypes or UI screens using tools like v0, Bolt, Lovable, UX Pilot, etc., your prompt needs to be better than most PRDs you’ve worked with. Why? Because the output depends entirely on how clearly and specifically you describe the goal.

The catch? Writing that kind of prompt is hard. So instead of jumping straight to the design prompt, try writing a meta-prompt first. That is a prompt that asks GPT to help you write a better prompt. Prompting about prompting, prompt-ception, if you will.

Here’s how to make that work: Feed GPT what you already know about the app or the screen. Then ask it to treat things like information architecture, layout, and user flow as variables it can play with. That way, you don’t just get one rigid idea — you get multiple concept directions to explore.

Role
You are a product design strategist working with AI to explore early-stage design concepts.

Goal
Generate 3 distinct prompt variations for designing a Daily Wellness Summary single screen in a mobile wellness tracking app for Lovable/Bolt/v0.

Each variation should experiment with a different Information Architecture and Layout Strategy. You don’t need to fully specify the IA or layout — just take a different angle in each prompt. For example, one may prioritize user state, another may prioritize habits or recommendations, and one may use a card layout while another uses a scroll feed.

User context
The target user is a busy professional who checks this screen once or twice a day (morning/evening) to log their mood, energy, and sleep quality, and to receive small nudges or summaries from the app.

Visual style
Keep the tone calm and approachable.

Format
Each of the 3 prompt variations should be structured clearly and independently.

Remember: The key difference between the three prompts should be the underlying IA and layout logic. You don’t need to over-explain — just guide the design generator toward different interpretations of the same user need.

5. From Cognitive Walkthrough To Testing Hypothesis

Technique: Casual Tree of Though + Casual Reasoning + Multi-Roles + Self-Reflection

Cognitive walkthrough is a powerful way to break down a user action and check whether the steps are intuitive.

Example: “User wants to add a task” → Do they know where to click? What to do next? Do they know it worked?

We’ve found this technique super useful for reviewing our own designs. Sometimes there’s already a mockup; other times we’re still arguing with a PM about what should go where. Either way, GPT can help.

Here’s an advanced way to run that process:

Context
You’ve been given a screenshot of a screen where users can create new tasks in a project management app. The main action the user wants to perform is “add a task”. Simulate behavior from two user types: a beginner with no prior experience and a returning user familiar with similar tools.

Task & Instructions
Go through the UI step by step and evaluate:

1. Will the user know what to do at each step?
2. Will they understand how to perform the action?
3. Will they know they’ve succeeded?

For each step, consider alternative user paths (if multiple interpretations of the UI exist). Use a casual Tree-of-Thought method.

At each step, reflect: what assumptions is the user making here? What visual feedback would help reduce uncertainty?

Format
Use a numbered list for each step. For each, add observations, possible confusions, and UX suggestions.

Limits
Don’t assume prior knowledge unless it’s visually implied.
Do not limit analysis to a single user type.

Cognitive walkthroughs are great, but they get even more useful when they lead to testable hypotheses.

After running the walkthrough, you’ll usually uncover moments that might confuse users. Instead of leaving that as a guess, turn those into concrete UX testing hypotheses.

We ask GPT to not only flag potential friction points, but to help define how we’d validate them with real users: using a task, a question, or observable behavior.

Task & Instructions
Based on your previous cognitive walkthrough:

1. Extract all potential usability hypotheses from the walkthrough.
2. For each hypothesis:
   • Assess whether it can be tested through moderated or unmoderated usability testing.
   • Explain what specific UX decision or design element may cause this issue. Use causal reasoning.
   • For testable hypotheses:
     • Propose a specific usability task or question.
     • Define a clear validation criterion (how you’ll know if the hypothesis is confirmed or disproved).
     • Evaluate feasibility and signal strength of the test (e.g., how easy it is to test, and how confidently it can validate the hypothesis).
     • Assign a priority score based on Impact, Confidence, and Ease (ICE).

Limits
Don’t invent hypotheses not rooted in your walkthrough output. Only propose tests where user behavior or responses can provide meaningful validation. Skip purely technical or backend concerns.

6. Cross-Functional Feedback

Technique: Multi-Roles

Good design is co-created. And good designers are used to working with cross-functional teams: PMs, engineers, analysts, QAs, you name it. Part of the job is turning scattered feedback into clear action items.

Earlier, we talked about how giving AI a “role” helps sharpen its responses. Now let’s level that up: what if we give it multiple roles at once? This is called multi-role prompting. It’s a great way to simulate a design review with input from different perspectives. You get quick insights and a more well-rounded critique of your design.

Role
You are a cross-functional team of experts evaluating a new dashboard design:

• PM (focus: user value & prioritization)
• Engineer (focus: feasibility & edge cases)
• QA tester (focus: clarity & testability)
• Data analyst (focus: metrics & clarity of reporting)
• Designer (focus: consistency & usability)

Context
The team is reviewing a mockup for a new analytics dashboard for internal use.

Task & Instructions
For each role:

1. What stands out immediately?
2. What concerns might this role have?
3. What feedback or suggestions would they give?

By now, you’ve seen that prompting isn’t just about typing better instructions. It’s about designing better thinking.

We’ve explored several techniques, and each is useful in different contexts:

But even the best techniques won’t matter if you use them blindly, so ask yourself:

• Do I need precision or perspective right now?
  • Precision? Try Role + Checkpoints for clarity and control.
  • Perspective? Use Multi-Role or Tree of Thought to explore alternatives.
• Should the model reflect my framing, or break it?
  • Reflect it? Use Role + Context + Instructions.
  • Break it? Try Opponent prompting to challenge assumptions.
• Am I trying to reduce ambiguity, or surface complexity?
  • Reduce ambiguity? Use Meta-prompting to clarify your ask.
  • Surface complexity? Go with ToT or RBU to expose hidden layers.
• Is this task about alignment, or exploration?
  • Alignment? Use Multi-Roles prompting to simulate consensus.
  • Exploration? Use Cognitive Walkthrough to push deeper.

Remember, you don’t need a long prompt every time. Use detail when the task demands it, not out of habit. AI can do a lot, but it reflects the shape of your thinking. And prompting is how you shape it. So don’t just prompt better. Think better. And design with AI — not around it.

Unexpected shipping costs are one of the biggest reasons customers abandon their carts. If your WooCommerce store charges too much or the pricing feels confusing, then you could be losing sales without realizing it.

That’s why it’s so important to offer clear, fair shipping rates. And one of the simplest ways to do that is with weight-based shipping.

With this method, shipping costs are calculated based on the total weight of the cart. Lighter orders get lower rates, while heavier ones are charged more accurately, helping you cover your costs without turning customers away.

I’ve spent time testing both WooCommerce’s built-in tools and third-party plugins to find the best ways to set this up.

In this guide, I’ll show you exactly how to add weight-based shipping to your store. Plus, I will share some practical tips to avoid common pitfalls and keep your checkout process smooth. 🚚

Why Offer Weight-Based Shipping in WooCommerce?

Weight-based shipping ensures fair and accurate delivery costs by calculating rates based on the actual weight of the order.

Unlike flat rate shipping, which charges the same fee for every purchase, this method prevents overcharging for lightweight items and losing money on heavy ones.

By switching to weight-based shipping in your WooCommerce store, you get more control and flexibility. It removes guesswork, avoids surprises at checkout, and keeps costs transparent.

It’s especially useful for stores that sell heavy items, bundles, or a mix of lightweight and bulky products.

Whether you’re shipping furniture, books, or gym equipment, this helps you stay profitable while keeping shipping costs transparent for your customers.

Having said that, let’s take a look at how to easily add weight-based shipping in WooCommerce. I will cover two different methods in this tutorial. You can use the links below to jump to the method of your choice:

Method 1: Add Weight Based Shipping Using the Default Settings (Basic Settings)

If you want to set up weight-based shipping in WooCommerce without using any extra WooCommerce plugins or extensions, then this method is for you.

WooCommerce doesn’t come with a built-in weight-based shipping option, but there’s a simple workaround you can use.

Instead of a direct weight-based setting, you can use shipping classes to group products by their weight. Then, you can create different flat rates for each class within your shipping zones.

This way, heavier items can have higher shipping costs, and lighter ones can ship for less, all using the default WooCommerce settings.

To get started, visit the WooCommerce » Settings » Shipping » Classes page from the WordPress dashboard and click the ‘Add shipping class’ button.

In the pop-up that appears, add a name for your shipping class. I recommend choosing something clear that helps you quickly recognize the type of products it’s for.

For example, if you’re creating a class for all the items under 5 kg, then you might name it ‘Under 5kg.’

Then, you’ll need to add a slug for the class. You can also leave this blank, and WooCommerce will generate one based on the name you enter.

But if you want more control, you can enter your own.

Next, add a short note explaining what the shipping class is for. It’s mainly for your own reference or for other admins working on the site.

Then, go ahead and click the ‘Create’ button.

You can now repeat the process to add as many weight based shipping classes as you want.

Once you are done, it will look something like this:

Next, go to the ‘Shipping Zones’ tab. Here, you’ll see a list of all the shipping zones you’ve set up for your store. These zones represent the countries or regions where you offer shipping.

If you haven’t added a shipping zone yet, simply click the ‘Add zone’ button.

This will take you to a new screen where you can add a name. I recommend naming the zone after the region or country you’re offering shipping to, as this can help prevent any confusion.

After that, simply type the name of the region or country in the ‘Zone regions’ field. When the option appears, click on it to add it to your zone. You can add as many regions as you want.

Once you’re done, click the ‘Add shipping method’ button to proceed.

A new popup will now appear on your screen.

From here, select the ‘Flat rate’ option and click ‘Continue.’

In the next step, you’ll need to give your shipping method a name. This is important because your customers will see it at checkout.

A name like ‘Shipping Cost Based on Product Weight’ is clear and descriptive.

Next, add a cost for shipping in the ‘Cost’ field. This will be the default shipping cost that customers will pay when purchasing an item.

This is the base shipping cost for any product without a shipping class. Keep in mind, this cost can also be added to other shipping fees, which I’ll explain in a moment.

Next, scroll down to the ‘Shipping class costs’ section. Here, you can set a cost for each weight-based shipping class you’ve created.

For example, you might charge $10 for items in the 11–15 kg class and $20 for those in the 16–20 kg class.

⚠️ Important Note: WooCommerce adds the shipping class cost on top of the default flat rate. For example, if your default cost is $5 and the class cost is $10, then the total shipping fee for the customer will be $15.

To avoid this and use only the shipping class cost, you must set the main ‘Cost’ field for the flat rate to $0.

Just below the cost fields, you’ll also see a setting called ‘Calculation type’. This controls how WooCommerce calculates shipping when a cart contains items from multiple classes.

Here is how each option works:

• Per Class: WooCommerce will add the cost for each individual shipping class in the order. For example, if a customer has an item from the 11–15 kg class ($10 fee) and another from the 16–20 kg class ($20 fee), then the total added shipping cost will be $30.
• Per Order: WooCommerce will only apply the cost from the most expensive shipping class in the order. Using the same example, only the $20 fee would be added to the shipping rate.

For most stores that use weight-based shipping, the ‘Per class’ option gives you more accurate and fair pricing. This is especially helpful when orders often include products of varying weights.

Once you have chosen your ‘Calculation Type’, click the ‘Save’ button to store your settings.

Now, head over to the ‘Products’ page and open your preferred item in the WooCommerce editor. Scroll down to the ‘Product Data’ section and switch to the ‘Shipping’ tab.

First, you need to enter the product’s weight in the ‘Weight’ field. After that, you’ll need to select the correct shipping class from the ‘Shipping class’ dropdown menu.

For example, if your product weighs 0.45 kg, you would select the ‘Under 5kg’ class you created earlier.

After that, click the ‘Update’ or ‘Publish’ button to save your changes.

Now visit your WooCommerce store to see the shipping price based on your product’s weight.

While this method works well for simple setups, managing many different weight classes can become complicated.

So, if you have many products or need more flexible shipping rules, then using a dedicated plugin is a much easier solution.

Method 2: Add Weight Based Shipping Using a Plugin (Recommended)

For more powerful and flexible shipping rules, using a dedicated plugin is your best option.

I recommend the free WooCommerce Weight Based Shipping plugin because it allows you to create as many shipping rules as you want based on product weight. You can also set different rates for different countries and offer free shipping when a customer’s order reaches a certain total.

First, you need to install and activate the WooCommerce Weight Based Shipping plugin. For details, see our tutorial on how to install a WordPress plugin.

Upon activation, head over to the WooCommerce » Settings » Shipping » Weight Based Shipping page from the WordPress admin sidebar.

Here, click the ‘Set Up Global Shipping Rules’ button.

This will take you to a new screen where you can define weight-based shipping rules for your products. You’ll notice that the plugin comes with a few default rules already set up, but you can easily edit or delete them as needed.

You can start by adding a title for each rule. Choose names that help you quickly identify the weight range, such as ‘Under 5kg’ or ‘5-10kg’.

In the ‘Destination’ column, you can leave the setting as ‘Any’. This means the weight shipping rule will apply to all countries you ship to.

However, if you want to charge different shipping rates for specific regions, you can do that by selecting a country from the ‘Destination’ dropdown menu. This allows you to apply your weight-based shipping rule only to that location.

For example, let’s say your store is based in Europe. You might want to charge $5 for orders under 5kg going to France because it’s relatively close, and shipping is cheaper.

But for the same weight range being shipped to the USA, you could charge $10 or more to cover the higher shipping cost due to the longer distance.

After that, set the ‘From’ and ‘Up To’ weight values for each rule in the Weight column. For example, for the ‘Under 5kg’ rule, you can enter From: 0 and Up To: 5.

Once you’ve entered the numbers, click the ‘OK’ button to save the range.

Next, take a look at the ‘Value’ column. This is where you define when the shipping rule applies, usually based on the total order amount.

Let’s say you want to offer free shipping for small packages under 5kg, but only if the customer spends $100 or more. In that case, you can set the weight range from 0 to 5, and in the ‘Value’ column, enter 100.00+. Then, set the shipping cost to ‘Free.’

This means if someone orders products weighing under 5kg and their cart total is $100 or more, they won’t have to pay anything for shipping.

Now, you might also want to add another rule for customers who order less than $100 worth of items.

For that, create the same weight range—0 to 5kg—but in the ‘Value’ column, enter 0.00 – 99.99 and set the shipping cost to something like $10.

This means if the cart is under 5kg and the order total is below $100, then they’ll be charged $10 for shipping.

Now, it’s time to actually set the shipping cost based on weight. For this, expand the ‘Shipping’ tab for each rule. You can select the ‘Free’ option to offer free shipping.

Or, choose the ‘Flat’ option and add the shipping price based on weight.

You can also choose the ‘Flat + Progressive’ option, which is helpful if you sell heavier items that go beyond your defined weight rules.

For example, let’s say your rules go up to 30 kg. You can set a Flat rate of $20 for orders up to 30 kg. Then, in the Progressive field, you can add a cost of $2 per 1 kg.

Now, if a customer places an order that weighs 32 kg, they’ll be charged the initial $20 (for the first 30 kg) plus $4 (for the extra 2 kg), for a total shipping cost of $24.

This setup ensures you’re still covering your shipping costs fairly, even for heavier orders.

Next, add a note for each weight rule. This note is just for you and your team, and it helps keep things organized by explaining what each rule is for.

For example, you can write something like “Free shipping for small orders over $100” or “Extra charges for items over 30kg.”

Once you’ve added the notes, click the ‘Save’ icon to store your settings.

Next, you need to add the shipping method you created to one of your shipping zones.

From the ‘Shipping’ tab, click on a zone where you want to offer weight-based shipping. Then, click the ‘Add shipping method’ button.

This will open a popup on the screen, where you have to choose ‘Weight Based Shipping’ as the shipping method.

Next, click the ‘Continue’ button.

Then, head to the ‘Products’ page and open an item in the editor.

From here, scroll down to the ‘Product Data’ section and switch to the ‘Shipping’ tab. Now, you have to add the weight for the product to apply the shipping rules to it.

After that, simply click the ‘Update’ or ‘Publish’ button to store your settings.

Now, you can visit your WooCommerce store and add a product to your cart.

You should be able to see the delivery charges based on the products’ weight on the screen.

🎁 Bonus: Offer a Shipping Discount in WooCommerce

Offering weight-based shipping is great for making sure that your customers are paying a fair price. But if you’re also looking to increase your sales, then I recommend providing shipping discounts.

Many customers expect some kind of deal when it comes to shipping, especially for larger orders. Even a small discount can make a difference in conversions and customer satisfaction.

That’s why offering a shipping discount is a great way to reduce cart abandonment and increase your average order value.

To easily add shipping discounts to your WooCommerce store, I recommend using the Advanced Coupons plugin.

It’s beginner-friendly and gives you the power to easily create shipping discount rules.

For example, you can offer free shipping when a customer’s cart reaches a certain total, apply percentage-based discounts on shipping costs, or automatically trigger special shipping deals based on specific cart conditions.

Plus, you can combine these offers with your weight-based shipping rules for maximum flexibility.

To get started, see our tutorial on how to offer a shipping discount in WooCommerce.

FAQs: Weight Based Shipping in WooCommerce

Here are the answers to some common questions we get about setting up weight-based shipping in WooCommerce.

Do I have to add a weight to every single WooCommerce product?

Yes, for weight-based shipping to work correctly, you must enter a weight for each physical product in your store.

If a product doesn’t have a weight assigned, WooCommerce won’t be able to calculate the shipping cost for it accurately, and it may fall back to a default flat rate or show no shipping options at all.

What happens if a customer has both physical and digital products in their cart?

WooCommerce automatically handles this. Shipping costs will only be calculated based on the weight of the physical items in the cart. Digital products, since they don’t require shipping, have no weight and will not affect the shipping calculation.

Can I offer free shipping for certain WooCommerce orders?

Absolutely. With the default method, you can create a shipping class for a specific weight range and set its cost to $0.

With the plugin method, you can create a rule that offers free shipping when an order reaches a certain weight or cart value, giving you more flexibility.

My products have a very wide range of weights. What is the best way to handle this?

The best approach is to create several shipping rules to cover all your products. For very heavy items that might exceed your heaviest rule, the plugin method is ideal.

You can use its ‘Flat + Progressive’ option to set a base rate plus an extra charge per kg/lb, ensuring you always cover your costs for oversized orders.

I hope this article helped you learn how to easily add weight based shipping in WooCommerce. You may also want to see our beginner’s guide on how to add a free shipping bar in WooCommerce and our tutorial on how to prevent fraud and fake orders in WooCommerce.

If you liked this article, then please subscribe to our YouTube Channel for WordPress video tutorials. You can also find us on Twitter and Facebook.

The post I’ll Show You How to Add Weight Based Shipping in WooCommerce first appeared on WPBeginner.

The world of product design is changing faster than ever, thanks to the rapid advancements in artificial intelligence. My journey into building with AI started modestly, experimenting with tools like ChatGPT and then expanding into more specialized platforms like Claude, Perplexity, and, most recently, artifacts. Each step has been a revelation, not just in capability but in the way these tools fundamentally transform how we approach design and prototyping.

The evolution of AI in design

It began with simple experiments — copy-pasting between ChatGPT and Visual Studio Code, running snippets in the terminal, and juggling dependency installations. I remember the excitement of creating my first custom game. Sure, it was just a Flappy Bird clone, but it featured my graphics, characters, and rules. Seeing it work locally felt like a superpower, even if the process was iterative and manual.

When Claude entered the picture, the game changed. Code generation became smarter, requiring fewer iterations to achieve the desired outcome. And then artifacts arrived, and that’s when it truly hit me: this changes everything. The ability to build through natural language — prompting rather than coding — opened new creative pathways.

Building faster, designing better

For years, prototyping high-fidelity interactions or testing new component paradigms felt like bottlenecks in the design process. Tools like Figma and Framer are incredible, but they come with steep time investments. Translating an idea from your head into something tangible often meant spending hours perfecting animations or crafting detailed mockups.

Now, with AI, I can generate functional prototypes in minutes. A well-crafted prompt often delivers results that are “close enough” on the first attempt, letting me quickly iterate and refine. Seeing a concept in a working environment  —  not just a static prototype  —  reveals new possibilities and sparks immediate ideas for improvement.

Even more exciting is the ability to share these working prototypes directly with engineers. Instead of handing off a static design or a click-through Figma prototype, I can deliver something dynamic, something close to how it might operate in production. This shift bridges the gap between design and development, fundamentally altering how we collaborate.

The designer-engineer hybrid

AI is pushing us toward a future where designers can become design engineers. Tools like artifacts don’t just speed up our workflow; they empower us to bring our ideas to life without waiting for someone else. For years, I felt blocked because I couldn’t code well enough to execute my visions. I’d have to hire or partner with an engineer, introducing delays and losing some of that initial creative spark.

But now, AI acts as a junior developer, enabling an iterative process where I can build, test, and refine in real time. It’s not just about speed  —  it’s about independence. The shift feels monumental. We’re no longer constrained by our technical skillset, and this democratization of building opens the door for designers to step into roles that merge creative vision with technical execution.

A global productivity shift

The implications extend beyond individual workflows. As these AI tools become more accessible, free, and even — they have the potential to spark a massive productivity boost across industries. Imagine the collective creativity of humanity, unleashed from technical or resource limitations.

When anyone with an idea can build without barriers, innovation accelerates. This democratization could lead to a renaissance of creativity, where people from all walks of life contribute to solving problems, designing better products, and imagining new futures.

Reimagining the role of high-fidelity design

This evolution raises an important question: What does the future hold for tools like Figma? If AI can generate high-fidelity prototypes that operate almost like production code, will designers still invest hours in pixel-perfect and advanced prototyping features? I still think tools like Figma or other design tools will be really valuable. A quick way to get a head start on your live prototype is often having a solid design as a base that a tool like Cursor or Claude artifacts can work from. It also makes the prompt engineering a bit easier if you can speak better visually.

The answer might lie in how we define our roles. Instead of focusing on tools and workflows, designers can focus on vision, strategy, and problem-solving. High-fidelity design won’t disappear  —  it will transform. Prototyping in AI environments means iterating faster, collaborating more effectively, and delivering solutions that are closer to reality from the start.

Where we go from here

AI isn’t just a tool; it’s a collaborator. A really good one at that.

For designers, this means rethinking how we work, how we communicate, and what skills we prioritize. It’s a chance to help shape a future where the barriers between creativity and execution dissolve.

Remember, AI isn’t meant to replace you; it’s meant to elevate you.

Stay curious.

The article originally appeared on Medium.

Featured image courtesy: Jacquelyn Halpern.

The post The Future of Product Design in an AI-Driven World appeared first on UX Magazine.

In the rapidly evolving world of AI “AI agent runtimes have emerged as environments where AI agents can be freely executed—designed, tested, deployed, and orchestrated—to achieve high-value automation. When discussing the development and deployment of AI agents, runtimes are often confused with agent frameworks. While they may sound similar, they serve distinct purposes in the AI ecosystem. The unique capabilities of runtimes and frameworks can make it more efficient to scale AI agents within an organization.  

Overview of AI Agent Runtimes and Frameworks

AI agent runtimes provide the infrastructure for executing AI agents. Runtimes handle orchestration, state management, security, and integration. AI agent frameworks focus on building agents and offer tools for reasoning, memory, and workflows. Frameworks most often need pairing with a separate runtime for production deployment. 

A full lifecycle solution combines runtimes and frameworks, enabling end-to-end management from inception through ongoing runtime operations, maintenance, and evolution.

Understanding AI Agent Runtime

An AI agent runtime is the execution environment where AI agents operate. It’s the infrastructure or platform that enables  agents to run, process inputs, execute tasks, and deliver outputs in real-time or near-real-time. A runtime is the engine that powers the functionality of AI agents, ensuring they can interact with users, APIs, or other systems safely and efficiently.

Key characteristics of AI agent runtimes:

• Execution-focused: Runtimes provide the computational resources, memory management, and processing capabilities needed to run AI agents.
• Environment-specific: Runtimes handle tasks like scheduling, resource allocation, and communication with external systems (like cloud services, databases, or APIs).
• Highly Scalable: Runtimes ensure the agent can handle varying workloads, from lightweight tasks to complex, multi-step processes.

Examples of AI agent runtimes: 

• Cloud-based platforms like AWS Lambda for serverless AI execution
• Kubernetes for containerized AI workloads
• Dedicated runtime environments like those provided by xAI for running Grok models
• No-code platforms like OneReach.ai’s Generative Studio X (GSX)serve as full lifecycle solutions, combining runtimes and frameworks—to orchestrate multimodal AI agents across channels like Slack, Teams, email and various voice channels

Runtimes enable real-time automation and workflow management. An AI agent runtime manages the compute resources and data pipelines needed for AI agents to process user queries and generate personalized responses.

Understanding AI Agent Frameworks

An AI agent framework is a set of tools, libraries, and abstractions designed to simplify the development, training, and deployment of AI agents. It provides developers with pre-built components, APIs, and templates to create custom AI agents without starting from scratch.

Key characteristics of AI agent frameworks:

• Development-focused: Frameworks streamline the process of building, configuring, and testing AI agents.
• Modular: Frameworks offer reusable components like natural language processing (NLP) modules, decision-making algorithms, and integration tools for connecting to external data sources.
• Flexible: Frameworks allow developers to define the agent’s behavior, logic, and workflows, with support for specific use cases ranging from chatbots to task automation to multi-agent systems.

Examples of AI Agent Frameworks: 

• Frameworks like LangChain for building language model-powered agents
• Rasa for conversational AI
• AutoGen for multi-agent collaboration

A developer might use a framework like LangChain to design an AI agent that retrieves data from a knowledge base, processes it with a large language model, and delivers a response, while abstracting away low-level complexities.

Key differences between agent runtimes and agent frameworks

How Runtimes and Frameworks Fit Together

AI agent runtimes and frameworks are complementary. Frameworks are used to design and build AI agents, defining their logic, capabilities, and integrations. Once agents are developed, they are deployed into a runtime environment where they can operate at scale, processing real-world inputs, and interact with users or systems. For example, an AI agent built using LangChain (framework) might be deployed on a cloud-based runtime like AWS or xAI’s infrastructure to handle user queries in production.

Runtimes often include or integrate framework-like features to streamline the process. OneReach.ai’s GSX platform acts as a runtime for orchestrating AI agents but incorporates no-code building tools that function similarly to a framework, allowing users to quickly design, test, and deploy agents without deep coding. 

Other pairings include LangChain with AWS Lambda, where LangChain handles agent logic and AWS provides the scalable runtime, as well as Rasa (for conversational flows) with Kubernetes (for containerized execution).

Integrated vs. Separate A Philosophical Distinction Between Approaches

Not all runtimes include agent building features. Some, like AWS Lambda or Kubernetes, are pure execution environments without built-in tools for designing agent logic, requiring separate frameworks for development. Others, such as GSX (OneReach.ai), integrate no-code interfaces for creating and customizing agents directly into the runtime, blending the two elements.

This distinction reflects a philosophical position in AI design: Should building and deployment be tightly integrated into a single platform, or kept separate for modularity? Proponents of separation argue it allows for greater flexibility—developers can mix and match best-in-class frameworks with specialized runtimes, fostering innovation and customization. However, integrating both offers significant advantages, particularly for companies without highly trained teams. 

By controlling both building and deployment, integrated platforms reduce complexity, minimize handoffs between tools, and ensure seamless transitions from design to production. This is especially beneficial for non-technical users or smaller organizations in sectors like HR or customer support, where quick setup, no-code accessibility, and reliable orchestration across channels enable rapid AI adoption without the need for expert developers or data scientists.

Estimated Project Time and Resources

For separate frameworks and runtimes (e.g., LangChain + AWS Lambda), building a basic AI agent might take 4-12 weeks, requiring 1-3 skilled developers (with Python and AI expertise) and potentially $10,000-$50,000 in initial costs (salaries, cloud fees, and setup). This suits teams focused on customization but demands more upfront investment in skills and integration. Integrated platforms like OneReach.ai can reduce this to days or 1-4 weeks for prototyping and deployment, often needing 1-2 non-technical users or business analysts, with costs around $500-$5,000 monthly (subscriptions) plus minimal setup—ideal for faster ROI in resource-constrained environments.

Pros and Cons of All-in-One Solutions

Pros and Cons of Frameworks + Runtimes

Can You Choose One Over the Other?

The choice between an AI agent runtime and a framework depends on your project’s stage and needs. Frameworks excel in the development phase, offering flexibility for custom logic, experimentation, and integration with specific AI models or tools—ideal when you need granular control over agent behavior. However, they require more coding expertise and don’t handle production-scale execution on their own, often leading to longer timelines (e.g., weeks for development) and higher resource demands (e.g., dedicated engineering teams).

Runtimes shine in deployment and operations, providing the infrastructure for reliable, scalable performance, including resource management and real-time processing. They are better for ensuring agents run efficiently in live environments but may lack the depth for initial agent design unless they include integrated building features. 

Platforms like OneReach.ai blur the lines by combining runtime capabilities with framework-style no-code tools, making them suitable for end-to-end workflows but potentially less customizable for advanced users—while cutting project time to hours or days and reducing the need for specialized skills.

In essence, use a framework if your focus is innovation and prototyping; opt for a runtime if reliability and scalability in production are paramount. For integrated solutions, choose platforms that handle both to simplify processes for less technical teams, with shorter timelines and lower resource barriers.

Who Should Choose One vs. the Other?

Choose a Framework if you’re a developer, AI engineers, and researchers building custom agents from scratch are likely to use frameworks. LangChain and AutoGen are perfect for teams with coding skills who need modularity and want to iterate on agent intelligence—like R&D or startups experimenting with novel AI applications—but entail 4-12 weeks and engineering resources for a full project.

Operations teams, IT leaders, and enterprises focused on deployment and maintenance should gravitate toward runtimes. OneReach.ai and AWS Lambda suit non-technical users and large organizations prioritizing quick orchestration, automation across channels, and handling high-volume tasks without deep development overhead—especially in sectors like HR, finance, or customer support where speed to production (days to weeks) matters more than customization. Integrated runtimes are ideal for companies lacking highly trained teams, as they provide end-to-end control for easier adoption with reduced time and costs.

For most companies—particularly mid-to-large enterprises without deep AI expertise or those prioritizing speed and reliability—an all-in-one AI agent runtime with building capabilities spanning the full lifecycle is likely the best solution. This approach simplifies deployment, reduces hidden costs, and ensures scalability and security out-of-the-box, enabling faster ROI (e.g., setup in hours vs. months). All-in-one platforms suit common use cases like workflow automation or chatbots.

Companies with strong technical teams that are experienced in AI projects and with high customization requirements might pair a framework with a runtime for more flexibility, with higher complexity and risk. Pilot projects with tools like LangGraph (full lifecycle) or CrewAI (framework) can help organizations decide what will best suit their needs.

Conclusion

In summary, AI agent frameworks are about building the agent—providing the tools to create its logic and functionality. AI agent runtimes are about running the agent, ensuring it has the resources and environment to perform effectively. Platforms like OneReach.ai demonstrate how runtimes can incorporate framework elements for a more integrated experience, highlighting the philosophical debate on separation vs. integration. Understanding this distinction is crucial for developers and organizations looking to create and deploy AI agents efficiently.

For those interested in exploring AI agent development, frameworks like LangChain or Rasa are great starting points, while platforms like AWS or xAI’s API services offer robust runtimes for deployment.

The post Understanding AI Agent Runtimes and Agent Frameworks appeared first on UX Magazine.

Deep dive into Insurify's insurance marketplace technology: 400+ carrier API connections, sub-10-second quote delivery, and intelligent matching algorithms.

Continue reading Behind Insurify: How One Insurance Marketplace Handles 400+ API Integrations and Real-Time Quotes at Scale on SitePoint.

If visitors can’t find what they’re looking for on your website, then they’ll leave, and they might not come back.

The problem is that the default WordPress search is very basic. Visitors type in a keyword, press Enter, wait for a full page to load, and still might not find what they need.

That’s where live autocomplete search (also called Ajax search) can help. It shows results instantly as someone types, making it easier for them to find the right content faster.

In this guide, I’ll show you how to add live autocomplete search in WordPress so you can create a faster, smoother search experience that keeps people on your website longer.

Why Add Live Autocomplete Search in WordPress?

Live autocomplete search helps visitors find what they’re looking for on your website faster, without reloading the page. As users type in the search bar, results appear instantly in a dropdown, so they can click and go straight to the content they need.

This kind of fast, helpful experience keeps people on your WordPress website longer. They don’t have to guess the right keyword or wait for a slow results page. And they’re less likely to hit a dead end.

Unfortunately, WordPress search is pretty limited by default. It doesn’t always search through things like product details or custom post types, and it struggles with exact matches.

Sometimes it even shows a “no results found” page, even when the content is there.

That’s where live search can be really helpful. It’s especially useful for blogs, news sites, and online stores, where visitors want to find something specific, fast.

If you want to make it easier for people to discover your best content, adding live search is a simple and effective way to do that.

How to Add Live Autocomplete Search in WordPress

The easiest way to add live autocomplete (Ajax) search to your site is by using a plugin. In this tutorial, I’ll use the free SearchWP Live Ajax Search plugin, which is one of the best WordPress search plugins.

It works out of the box by automatically upgrading any existing search forms on your site, such as the one in your theme’s header or sidebar. This means you can get live search suggestions instantly without needing to code or change any settings.

Now, I’ll walk you through how to create a live autocomplete search in WordPress.

Here’s a quick overview of all the things I’ll cover:

Let’s get started!

Step 1: Install and Activate SearchWP Live Ajax Search

First, you need to install and activate the SearchWP Live Ajax Search plugin.

You can find this plugin directly in your WordPress dashboard by going to Plugins » Add New and searching for “SearchWP Live Ajax Search.”

Once you find the plugin in the search results, click the ‘Install Now’ button. After installation completes, click ‘Activate’ to enable the plugin on your site.

For detailed installation instructions, see our step-by-step guide on how to install a WordPress plugin.

The plugin is completely free and developed by the same team behind the premium SearchWP plugin. It works independently, so you don’t need to purchase anything to get started with live search functionality.

Upon activation, a new ‘SearchWP’ menu item will appear in your WordPress admin area. You’ll use this to configure your settings in the next step.

Step 2: Configure Basic Search Settings

Now that the plugin is installed, you need to enable the live search functionality.

Head over to SearchWP » Settings in your WordPress dashboard.

On the settings page, you’ll see a few different options for configuring your search.

Make sure that you’re in the ‘Live Search’ tab and look for the ‘Enable Live Search’ toggle near the top of the page.

Simply click the toggle to turn it on, and then make sure to click the ‘Save’ button to store your settings.

Once enabled, the live Ajax search will automatically start working with your existing search forms across your WordPress site.

The plugin uses smart defaults that work well for different types of websites right out of the box. By default, it will search your post titles and content to provide relevant results.

Step 3: Add the Live Search Bar to Your Site (Optional)

The SearchWP Live Ajax Search plugin automatically enables live search on any existing search forms in your WordPress theme.

However, you may also want to add a search bar to a new location, like your sidebar, footer, or a custom landing page. This step will show you how to do that.

Add Live Autocomplete Search to Widget-Ready Areas

To add a search box to widget areas like your sidebar or footer, you need to go to Appearance » Widgets in your WordPress dashboard.

Click the ‘+’ button in the widget area, such as the sidebar or footer. Then, look for the Search widget.

Once added, you can customize the placeholder text.

For example, if you run a news site, you might customize the widget title with something like “Search Latest Stories” or “Find News Articles.”

Or you can simply leave it as “Search.”

Don’t forget to click the ‘Update’ button to save your changes. The live search box will now appear in your widget area.

Here’s what it looks like on my demo site:

Add Live Autocomplete Search Using Full Site Editor (FSE)

If you’re using a block-based theme that supports the Full Site Editor, then you can add search boxes to different parts of your website, like the header, sidebar, and more.

First, go to Appearance » Editor from your WordPress dashboard.

This will launch the Full Site Editor.

Then, you need to open the ‘Templates’ tab.

From here, click on the template you want to edit, such as your Header or a Page template.

The exact options will depend on the theme you’re using, but I recommend picking a Header template or the navigation menu so that the search bar will appear across your website.

Once you click on the template, you’ll see a visual editor with blocks.

Go ahead and click the ‘+’ button to add a new block, then look for ‘Search’ in the block inserter.

You can move the Search block up and down to your desired location within the template.

From here, you can customize the search block’s appearance using the block settings panel.

For example, you can adjust the placeholder text.

If you run a WordPress blog, then you may want to use something like “Search the blog” or “Find helpful articles.” Or you can also simply leave it as “Search.”

You can also customize the search bar style and layout options to match your site’s design.

Once you are happy with how it looks, click the ‘Update’ button to save your changes.

Step 4: Test and Troubleshoot Your Live Search

Now it’s time to test your new live search feature to make sure it’s working correctly.

I recommend opening your website in an incognito window and typing a few characters into the search box.

If everything’s working, you’ll see results appear instantly in a dropdown. That means Ajax is working correctly.

It’s a good idea to test your live search on different devices, including phone and tablet, to make sure it’s mobile-friendly. Try it in multiple browsers too, such as Chrome, Firefox, and Safari, to make sure live results appear consistently.

If the live search isn’t showing up or working as expected, then the most common culprits are caching issues and plugin conflicts.

Your browser or caching plugin might be storing an old version of your site’s files (a ‘cached’ version) to speed up loading times. Sometimes, this can prevent the new live search script from running correctly.

Clearing your WordPress cache and browser cache ensures that your site loads the latest version of its files, which often fixes the issue.

A good plugin for this is WP Rocket. It’s beginner-friendly and lets you clear cache, optimize scripts, and control how files are loaded for better performance.

For details, you can see our guide on how to clear the WordPress cache.

If that doesn’t solve the issue, try deactivating other plugins one by one to check for conflicts. This can help you identify if another plugin is interfering with your live search.

For more troubleshooting tips, please see our guide on how to fix WordPress search not working.

Bonus Tip: Upgrade for Even Smarter Search (Fuzzy Matching)

Your new live search offers a much better user experience to your visitors. But what happens if someone makes a typo? By default, WordPress might return no results for “wordpres” instead of “wordpress.”

This is where fuzzy search comes in, and it’s a powerful feature available in the premium SearchWP plugin.

Fuzzy search helps your website understand what your users are trying to find, even if they misspell or use partial words.

For example, if someone searches for “vntage furniture,” a site with fuzzy search will still show them relevant results for “vintage furniture.”

This prevents users from hitting a no results dead end and helps them find content, improving user experience and keeping them on your site.

For step-by-step instructions, you can see our guide on how to add fuzzy search in WordPress.

FAQs for Adding Live Autocomplete Search in WordPress

I get a lot of questions from our readers about WordPress search functionality, so I’ve put together answers to the most common ones.

What’s the best WordPress search plugin?

For live search functionality, I recommend SearchWP Live Ajax Search because it’s free and works great right out of the box.

If you need more advanced features like custom field searching or detailed analytics, then the premium SearchWP plugin is excellent.

How can I add autocomplete to address fields in WordPress?

Address autocomplete is different from content search. It uses services like Google Places API to suggest real addresses as users type.

You’ll need a form plugin like WPForms or Gravity Forms that includes address autocomplete features. This connects to mapping services to provide street address suggestions, which is separate from searching your site’s content.

Can I create a form that lets users search within a specific category?

If you want to add a dropdown menu so users can search by category, then you’ll need the SearchWP Pro plugin.

The free SearchWP Live Ajax Search plugin (the one we cover in this guide) will show category names in the live results, but it doesn’t let you create a full search form with category filters.

To get that feature, you’ll need to upgrade to the full SearchWP plugin and follow our tutorial on how to search by category in WordPress.

How do I add a search feature to my WordPress site?

Most WordPress themes include a built-in search widget that you can add to your menu, sidebar, header, or footer.

For details, see our guide on how to add a search bar to your WordPress menu.

More Guides to Improve WordPress Search

I hope this guide helped you add live autocomplete search to your WordPress site.

You may also want to check out our other related guides to improve your site’s search:

• How to Search By Category in WordPress
• How to Add PDF Indexing and Searching in WordPress
• How to Make Your Blog Comments Searchable in WordPress
• How to Include Custom Post Types in WordPress Search Results
• How to Exclude Specific Pages, Authors, and More from WordPress Search
• How to Add a Search Toggle Effect in WordPress
• How to See Search Analytics in WordPress (Easy Ways)

If you liked this article, then please subscribe to our YouTube Channel for WordPress video tutorials. You can also find us on Twitter and Facebook.

The post How to Create a Live Autocomplete Search in WordPress first appeared on WPBeginner.

It’s a common misconception that internationalization (i18n) is simply about translating text. While crucial, translation is merely one facet. One of the complexities lies in adapting information for diverse cultural expectations: How do you display a date in Japan versus Germany? What’s the correct way to pluralize an item in Arabic versus English? How do you sort a list of names in various languages?

Many developers have relied on weighty third-party libraries or, worse, custom-built formatting functions to tackle these challenges. These solutions, while functional, often come with significant overhead: increased bundle size, potential performance bottlenecks, and the constant struggle to keep up with evolving linguistic rules and locale data.

Enter the ECMAScript Internationalization API, more commonly known as the Intl object. This silent powerhouse, built directly into modern JavaScript environments, is an often-underestimated, yet incredibly potent, native, performant, and standards-compliant solution for handling data internationalization. It’s a testament to the web’s commitment to being worldwide, providing a unified and efficient way to format numbers, dates, lists, and more, according to specific locales.

At the heart of Intl lies the concept of a locale. A locale is far more than just a two-letter language code (like en for English or es for Spanish). It encapsulates the complete context needed to present information appropriately for a specific cultural group. This includes:

• Language: The primary linguistic medium (e.g., en, es, fr).
• Script: The script (e.g., Latn for Latin, Cyrl for Cyrillic). For example, zh-Hans for Simplified Chinese, vs. zh-Hant for Traditional Chinese.
• Region: The geographic area (e.g., US for United States, GB for Great Britain, DE for Germany). This is crucial for variations within the same language, such as en-US vs. en-GB, which differ in date, time, and number formatting.
• Preferences/Variants: Further specific cultural or linguistic preferences. See “Choosing a Language Tag” from W3C for more information.

Typically, you’ll want to choose the locale according to the language of the web page. This can be determined from the lang attribute:

// Get the page's language from the HTML lang attribute
const pageLocale = document.documentElement.lang || 'en-US'; // Fallback to 'en-US'

Occasionally, you may want to override the page locale with a specific locale, such as when displaying content in multiple languages:

// Force a specific locale regardless of page language
const tutorialFormatter = new Intl.NumberFormat('zh-CN', { style: 'currency', currency: 'CNY' });

console.log(Chinese example: ${tutorialFormatter.format(199.99)}); // Output: ¥199.99

In some cases, you might want to use the user’s preferred language:

// Use the user's preferred language
const browserLocale = navigator.language || 'ja-JP';

const formatter = new Intl.NumberFormat(browserLocale, { style: 'currency', currency: 'JPY' });

When you instantiate an Intl formatter, you can optionally pass one or more locale strings. The API will then select the most appropriate locale based on availability and preference.

The Intl object exposes several constructors, each for a specific formatting task. Let’s delve into the most frequently used ones, along with some powerful, often-overlooked gems.

1. Intl.DateTimeFormat: Dates and Times, Globally

Formatting dates and times is a classic i18n problem. Should it be MM/DD/YYYY or DD.MM.YYYY? Should the month be a number or a full word? Intl.DateTimeFormat handles all this with ease.

const date = new Date(2025, 6, 27, 14, 30, 0); // June 27, 2025, 2:30 PM

// Specific locale and options (e.g., long date, short time)
const options = {
  weekday: 'long',
  year: 'numeric',
  month: 'long',
  day: 'numeric',
  hour: 'numeric',
  minute: 'numeric',
  timeZoneName: 'shortOffset' // e.g., "GMT+8"
};

console.log(new Intl.DateTimeFormat('en-US', options).format(date));

// "Friday, June 27, 2025 at 2:30 PM GMT+8"
console.log(new Intl.DateTimeFormat('de-DE', options).format(date));

// "Freitag, 27. Juni 2025 um 14:30 GMT+8"

// Using dateStyle and timeStyle for common patterns
console.log(new Intl.DateTimeFormat('en-GB', { dateStyle: 'full', timeStyle: 'short' }).format(date));

// "Friday 27 June 2025 at 14:30"

console.log(new Intl.DateTimeFormat('ja-JP', { dateStyle: 'long', timeStyle: 'short' }).format(date));

// "2025年6月27日 14:30"

The flexibility of options for DateTimeFormat is vast, allowing control over year, month, day, weekday, hour, minute, second, time zone, and more.

2. Intl.NumberFormat: Numbers With Cultural Nuance

Beyond simple decimal places, numbers require careful handling: thousands separators, decimal markers, currency symbols, and percentage signs vary wildly across locales.

const price = 123456.789;

// Currency formatting
console.log(new Intl.NumberFormat('en-US', { style: 'currency', currency: 'USD' }).format(price));

// "$123,456.79" (auto-rounds)

console.log(new Intl.NumberFormat('de-DE', { style: 'currency', currency: 'EUR' }).format(price));

// "123.456,79 €"

// Units
console.log(new Intl.NumberFormat('en-US', { style: 'unit', unit: 'meter', unitDisplay: 'long' }).format(100));

// "100 meters"

console.log(new Intl.NumberFormat('fr-FR', { style: 'unit', unit: 'kilogram', unitDisplay: 'short' }).format(5.5));

// "5,5 kg"

Options like minimumFractionDigits, maximumFractionDigits, and notation (e.g., scientific, compact) provide even finer control.

3. Intl.ListFormat: Natural Language Lists

Presenting lists of items is surprisingly tricky. English uses “and” for conjunction and “or” for disjunction. Many languages have different conjunctions, and some require specific punctuation.

This API simplifies a task that would otherwise require complex conditional logic:

const items = ['apples', 'oranges', 'bananas'];

// Conjunction ("and") list
console.log(new Intl.ListFormat('en-US', { type: 'conjunction' }).format(items));

// "apples, oranges, and bananas"

console.log(new Intl.ListFormat('de-DE', { type: 'conjunction' }).format(items));

// "Äpfel, Orangen und Bananen"

// Disjunction ("or") list
console.log(new Intl.ListFormat('en-US', { type: 'disjunction' }).format(items));

// "apples, oranges, or bananas"

console.log(new Intl.ListFormat('fr-FR', { type: 'disjunction' }).format(items));

// "apples, oranges ou bananas"

4. Intl.RelativeTimeFormat: Human-Friendly Timestamps

Displaying “2 days ago” or “in 3 months” is common in UI, but localizing these phrases accurately requires extensive data. Intl.RelativeTimeFormat automates this.

const rtf = new Intl.RelativeTimeFormat('en-US', { numeric: 'auto' });

console.log(rtf.format(-1, 'day'));    // "yesterday"
console.log(rtf.format(1, 'day'));     // "tomorrow"
console.log(rtf.format(-7, 'day'));    // "7 days ago"
console.log(rtf.format(3, 'month'));   // "in 3 months"
console.log(rtf.format(-2, 'year'));   // "2 years ago"

// French example:
const frRtf = new Intl.RelativeTimeFormat('fr-FR', { numeric: 'auto', style: 'long' });

console.log(frRtf.format(-1, 'day'));    // "hier"
console.log(frRtf.format(1, 'day'));     // "demain"
console.log(frRtf.format(-7, 'day'));    // "il y a 7 jours"
console.log(frRtf.format(3, 'month'));   // "dans 3 mois"

The numeric: 'always' option would force “1 day ago” instead of “yesterday”.

5. Intl.PluralRules: Mastering Pluralization

This is arguably one of the most critical aspects of i18n. Different languages have vastly different pluralization rules (e.g., English has singular/plural, Arabic has zero, one, two, many...). Intl.PluralRules allows you to determine the “plural category” for a given number in a specific locale.

const prEn = new Intl.PluralRules('en-US');

console.log(prEn.select(0));    // "other" (for "0 items")
console.log(prEn.select(1));    // "one"   (for "1 item")
console.log(prEn.select(2));    // "other" (for "2 items")

const prAr = new Intl.PluralRules('ar-EG');

console.log(prAr.select(0));    // "zero"
console.log(prAr.select(1));    // "one"
console.log(prAr.select(2));    // "two"
console.log(prAr.select(10));   // "few"
console.log(prAr.select(100));  // "other"

This API doesn’t pluralize text directly, but it provides the essential classification needed to select the correct translation string from your message bundles. For example, if you have message keys like item.one, item.other, you’d use pr.select(count) to pick the right one.

6. Intl.DisplayNames: Localized Names For Everything

Need to display the name of a language, a region, or a script in the user’s preferred language? Intl.DisplayNames is your comprehensive solution.

// Display language names in English
const langNamesEn = new Intl.DisplayNames(['en'], { type: 'language' });

console.log(langNamesEn.of('fr'));      // "French"
console.log(langNamesEn.of('es-MX'));   // "Mexican Spanish"

// Display language names in French
const langNamesFr = new Intl.DisplayNames(['fr'], { type: 'language' });

console.log(langNamesFr.of('en'));      // "anglais"
console.log(langNamesFr.of('zh-Hans')); // "chinois (simplifié)"

// Display region names
const regionNamesEn = new Intl.DisplayNames(['en'], { type: 'region' });

console.log(regionNamesEn.of('US'));    // "United States"
console.log(regionNamesEn.of('DE'));    // "Germany"

// Display script names
const scriptNamesEn = new Intl.DisplayNames(['en'], { type: 'script' });

console.log(scriptNamesEn.of('Latn'));  // "Latin"
console.log(scriptNamesEn.of('Arab'));  // "Arabic"

With Intl.DisplayNames, you avoid hardcoding countless mappings for language names, regions, or scripts, keeping your application robust and lean.

You might be wondering about browser compatibility. The good news is that Intl has excellent support across modern browsers. All major browsers (Chrome, Firefox, Safari, Edge) fully support the core functionality discussed (DateTimeFormat, NumberFormat, ListFormat, RelativeTimeFormat, PluralRules, DisplayNames). You can confidently use these APIs without polyfills for the majority of your user base.

The Intl API is a cornerstone of modern web development for a global audience. It empowers front-end developers to deliver highly localized user experiences with minimal effort, leveraging the browser’s built-in, optimized capabilities.

By adopting Intl, you reduce dependencies, shrink bundle sizes, and improve performance, all while ensuring your application respects and adapts to the diverse linguistic and cultural expectations of users worldwide. Stop wrestling with custom formatting logic and embrace this standards-compliant tool!

It’s important to remember that Intl handles the formatting of data. While incredibly powerful, it doesn’t solve every aspect of internationalization. Content translation, bidirectional text (RTL/LTR), locale-specific typography, and deep cultural nuances beyond data formatting still require careful consideration. (I may write about these in the future!) However, for presenting dynamic data accurately and intuitively, Intl is the browser-native answer.

Further Reading & Resources

• MDN Web Docs:
  • Intl namespace object
  • Intl.DateTimeFormat
  • Intl.NumberFormat
  • Intl.ListFormat
  • Intl.RelativeTimeFormat
  • Intl.PluralRules
  • Intl.DisplayNames
• ECMAScript Internationalization API Specification: The official ECMA-402 Standard
• Choosing a Language Tag

I’ll be honest: there was a time when privacy compliance felt overwhelming.

Between GDPR, CCPA, VCDPA, and other regulations, it seemed like I needed a law degree just to run a simple WordPress site.

But after spending a lot of time helping website owners figure this out, I’ve learned that compliance doesn’t have to be complicated. In most cases, just a few simple changes can protect your website and show visitors that you take their privacy seriously.

That’s why I created this ultimate guide to WordPress privacy compliance. I’ve researched dozens of laws, tested different tools, and seen firsthand what works (and what causes problems) across different WordPress websites.

Why Does Privacy Compliance Matter for Your WordPress Website?

Online privacy laws are designed to give people more control over how websites, businesses, and online stores collect and use their personal information.

“Personal information” can mean more than you think. It includes names and email addresses—but also things like browsing history, preferences, location, and even biometric data.

That’s why most WordPress websites are affected by privacy laws, even if they only collect basic data like form submissions or cookies.

Following these laws is important for two reasons:

• Avoiding legal trouble: Some laws, like the Virginia Consumer Data Protection Act (VCDPA), can issue fines of up to $7,500 per violation. Other laws impose even higher penalties, sometimes reaching millions.
• Building trust with your audience: When visitors see that you respect their privacy, they’re more likely to engage with your site, join your email list, and make purchases.

In other words: privacy compliance isn’t just a legal requirement. It’s a smart move for long-term success.

In this guide, I’ll walk you through 12 key tips for WordPress privacy compliance. After that, I’ll break down the most important privacy laws that might affect your site.

Keep reading for the ultimate checklist to comply with international data privacy laws.

12 Tips for Achieving WordPress Privacy Compliance

No single guide can guarantee full compliance with every privacy law. But these tips will give you a strong foundation. You can think of this section as your privacy checklist for WordPress.

After reading through these best practices, I recommend scrolling down to the legal section to see which laws may apply to your site.

1. Perform a Data Audit

Before you can follow any privacy law, you need to know what personal data your website collects and how it’s used.

Start by reviewing all the tools and plugins on your site that interact with visitors. These often include:

• Analytics tools (like Google Analytics)
• Contact or quote forms
• SEO and marketing plugins

Once you’ve identified those tools, take a closer look at what they do.

For each one, ask yourself:

• What data does this tool collect?
• Why do I need this data?
• Where is the data stored?
• How long is it kept?
• Is it shared with anyone else?

Be sure to document your answers. This record helps you stay organized and gives you a way to prove your compliance if you’re ever audited or asked by one of your users.

2. Collect Less Data

One of the easiest ways to improve privacy on your WordPress site is to collect less data in the first place.

Most privacy laws require you to collect only personal data that’s relevant and necessary for a specific task. This principle is known as data minimization.

Take a look at the forms, plugins, and tools you use. For each one, you should ask yourself:

• What personal information am I asking for?
• Do I truly need this data?
• Could I achieve the same result with fewer form fields or information?

If the answer is “no” or “not sure,” it’s a good idea to stop collecting that data.

This approach not only reduces your legal risk. It also makes your site feel safer and more respectful to visitors, which can improve trust and conversions.

3. Create a Privacy Policy

A privacy policy tells visitors what data your website collects, how it’s used, and whether it’s shared with anyone.

Most privacy laws require you to have a policy like this. It helps users understand how their personal data is handled, which many laws refer to as the “Right to Know.”

Thankfully, WordPress has a built-in tool to help you create a privacy policy. To access this tool, simply go to Settings » Privacy in the WordPress dashboard. 

Want more detailed instructions? We also have a complete, step-by-step guide on how to add a privacy policy in WordPress.

4. Add a Cookie Popup

Some privacy laws require you to get consent before placing cookies on a visitor’s device. This includes laws like the GDPR.

A cookie popup makes this easy. It gives visitors a clear message about the types of cookies your site uses, what data is being collected, and why. It should also give them a simple way to opt out.

And this is easy to set up with a privacy compliance plugin like WPConsent.

For example, we use WPConsent to display cookie banners and manage user choices on WPBeginner.

For step-by-step instructions, check out our full guide on how to add a cookie popup in WordPress.

5. Write a Separate Cookie Policy 

A cookie popup is important, but it’s also a good idea to create a dedicated cookie policy page. This gives visitors a place to learn more about how cookies work on your site.

Your cookie policy should include:

• The types of cookies your site uses (such as essential, analytics, or marketing)
• What each cookie does
• What personal data it collects (like IP addresses or browsing history)

To build trust, try to keep your cookie policy easy to understand. This means you should avoid technical terms or legal words that are hard to follow. 

Luckily, a tool like WPConsent can create this policy for you. After installing and activating the plugin, go to WPConsent » Settings. 

In the plugin’s settings, choose the page where you want to display the cookie policy, and add the shortcode provided by the plugin.

WPConsent will then add this policy to your chosen page. 

If you’re using WPConsent to display a cookie popup, then visitors can now access this policy directly by clicking on the dropdown.

This will reveal a link that takes them straight to your policy page.

6. Block Third-Party Scripts

Many privacy laws also apply to third-party tools like analytics, advertising pixels, and social media trackers. If you use services such as Google Analytics or Facebook Pixel, then you’re responsible for how those tools collect data.

That means you should only allow scripts from these tools to run after the user gives permission.

The good news is that WPConsent includes a built-in script blocker that helps with this. It can detect common tracking tools and stop them from loading until the visitor agrees.

Once consent is given, the script runs automatically without needing to reload the page.

This is one of the easiest ways to improve compliance with laws like the GDPR and CCPA.

7. Track and Log Visitor Consent

There’s always a chance your data handling could be questioned, especially if you’re ever audited or someone asks about their rights.

That’s why it’s a good idea to keep a clear record of user consent. It helps show that your site takes privacy seriously.

The good news is, WPConsent creates this log for you automatically.

You can check it any time by going to WPConsent » Consent Logs in your WordPress dashboard.

If someone asks for proof, just head to the ‘Export’ tab, choose a date range, and download the log as a CSV file.

You can now share it directly with the user. Additionally, having this kind of record can give you peace of mind and help protect your business if questions ever come up.

8. Provide an Easy Opt-Out for Data Sales

Some privacy laws, including the CCPA and VCDPA, require you to give users a way to opt out of having their personal data sold or shared with third-party tools.

It’s also important to know that under laws like the CCPA, ‘selling’ can also mean sharing personal data with third-party advertising or analytics partners in exchange for their services, not just for money.

The easiest way to allow users to opt out in WordPress is by adding a clear, dedicated opt-out page.

WPConsent includes a Do Not Track add-on that makes this simple.

It enables you to generate a form where users can submit their opt-out request.

Once the page is live, visitors can use the form to stop their data from being sold or shared, all without needing to contact you directly.

This creates a smoother experience for your audience and helps you stay compliant with important data laws.

For full setup instructions, see our step-by-step guide on how to create a Do Not Sell My Info page in WordPress.

9. Export and Erase Personal Data in WordPress

Privacy laws like the GDPR give users the right to access their personal data, and the right to ask for that data to be deleted.

One of the easiest ways to support these rights is by adding data request and deletion forms to your WordPress site.

This is where WPForms comes in. It’s a user-friendly form builder that lets you create all kinds of forms using a simple drag-and-drop editor.

WPForms even has a ready-made Right to Erasure Request Form template.

What if visitors want to see their data instead? WPForms also has a Data Request template.

These templates are a fantastic starting point for accepting data erasure and data access requests on your site.

For a step-by-step guide to getting started with WPForms, check out our post on how to create a contact form in WordPress. 

After adding these forms to your site, WPForms will automatically log and display all submissions in your WordPress dashboard. This makes it easy to see new requests as they come in.

You can then act on these requests using WordPress’ built-in Export Personal Data and Erase Personal Data tools.

For step-by-step instructions on how to use these powerful tools, see our detailed guide on how to export and erase personal data in WordPress.

10. Create Compliant Forms

Contact forms, quote forms, and surveys often collect personal information. That means that they also need to comply with privacy laws.

If you’re using WPForms, there’s a built-in GDPR Agreement field that helps you with this. You can add it to any form and get a user’s explicit consent to store their personal information before collecting it.

Simply drag this field into any form using the visual builder.

It will add a checkbox and consent message so that visitors can agree to how their data will be used.

Apart from the GDPR, this field helps you stay compliant with other laws that require clear consent before collecting or storing personal data.

Want a complete walkthrough? Just see our guide on how to create GDPR compliant forms in WordPress. 

11. Use Data Privacy Compliance Plugins

If you’ve been following along with this guide so far, then you already have a solid foundation for privacy compliance. But the tools you install on your website matter too.

The WordPress plugins you choose can either make compliance harder or give you built-in features that simplify the process.

Let’s look at one common example.

Tracking your visitors with analytics helps you improve your site and understand how people interact with your content. This might include tracking page views, link clicks, purchases, or time spent on each page.

But depending on your setup, analytics tools can also collect personal data—like IP addresses, geographic location, and behavioral profiles. That’s where things get tricky.

At WPBeginner, we use MonsterInsights to handle this responsibly. It includes settings to anonymize user data or disable user tracking when consent hasn’t been given.

These options help reduce your legal risk while still giving you the insights you need to grow your site.

Of course, analytics are just one part of the puzzle. Plugins like WPConsent and WPForms also help you manage cookie banners, collect data responsibly, and process requests like opt-outs and deletions.

You’ll find more options in our expert roundup of the best WordPress GDPR plugins.

12. Add a Comment Privacy Opt-in Checkbox

When someone leaves a comment on your WordPress site, they usually need to enter their name, email address, and possibly a website URL. That’s personal data, so it’s covered by privacy laws.

WordPress includes a privacy checkbox for comments by default. This gives users a chance to agree to the storage of their information before submitting a comment.

However, some themes use a custom comment form that might not include this checkbox by default.

If you don’t see the checkbox on your site, then it’s a good idea to add it manually. You can use a plugin like Thrive Comments or add some custom code to your website.

For step-by-step instructions, check out our guide on how to add a GDPR comment privacy opt-in checkbox.

Key Regulations Impacting WordPress Sites

WordPress privacy compliance often depends on which laws apply to your website, and that’s not always easy to figure out.

Some laws apply to specific locations. Others apply only if you collect a certain amount of data or meet a business-size threshold.

In this section, I’ll walk you through the most common privacy laws that affect WordPress site owners.

You don’t need to become a legal expert, but it’s helpful to know which rules you may need to consider so that you can take the right steps.

The General Data Protection Regulation (GDPR)

The General Data Protection Regulation (GDPR) is a European Union (EU) law designed to give EU citizens more control over their personal data.

Simply put, you must get explicit, specific, and clear permission before collecting personal data from anyone living in the European Union.

You must also clearly tell EU residents where, why, and how you’ll process and store their data.

Under the GDPR, individuals also have the right to download their personal data and the “right to be forgotten.” This means they can ask you to delete their data at any time. 

For more information, our ultimate guide to WordPress and GDPR compliance is a must-read resource.

California Consumer Privacy Act (CCPA)

The CCPA is a privacy law that gives California residents more control over their personal information. It allows them to see what data is collected, how it’s used, and who it’s shared with.

This law applies to for-profit businesses that meet at least one of these criteria:

• Have annual gross revenue over $25 million.
• Buy, sell, or share personal data from 100,000 or more California residents per year.
• Make at least 50% of their revenue from selling or sharing personal data.

It doesn’t matter where your business is located. If your WordPress site serves people in California and meets one of these thresholds, then the CCPA may apply.

The law also requires you to provide an opt-out for data sharing and to respond to requests to view or delete personal information.

You can learn more in our ultimate guide to CCPA compliance for WordPress.

The Personal Data Protection Law (PDPL) – Saudi Arabia

Personal Data Protection Law (PDPL) is a privacy law that sets clear rules for how businesses can collect, use, and store the personal data of Saudi residents.

Ignoring the PDPL carries substantial risks. Fines can reach up to SAR 5 million (about $1.3 million USD) per violation, and this amount can double for repeat offenses. 

If any of your customers or users live in Saudi Arabia, then you should check out our beginner’s guide to PDPL compliance. It shows you how to navigate this important law and avoid those steep fines.

The Utah Consumer Privacy Act (UCPA)

The Utah Consumer Privacy Act (UCPA) is designed to protect the personal information of Utah residents. 

Like some other privacy regulations, the UCPA’s reach extends beyond Utah’s borders. If your site targets users in Utah—for example, through marketing or services—then the law might apply, even if you’re located elsewhere.

However, don’t worry if you’re a smaller blog or website. Just like the CCPA, the UCPA is mainly aimed at larger businesses.

First, your business needs to operate in Utah or offer products or services targeting Utah residents. Next, your business must have an annual revenue of $25 million or more.

You’ll also need to meet at least one of these data thresholds: 

• Control or process the personal data of 100,000 or more Utah consumers annually.
• Get over 50% of your gross revenue from selling personal data and control or process data from 25,000 or more Utah consumers.

For more information, I recommend checking out our ultimate beginner’s guide to UCPA compliance in WordPress.

The Virginia Consumer Data Protection Act (VCDPA)

The Virginia Consumer Data Protection Act (VCDPA) is a state-level privacy law. 

However, the VCDPA doesn’t apply to every single website. It’s another law that mainly targets big businesses.

In fact, you typically only need to comply with the VCDPA if your business meets one of these conditions: 

• You control or process the personal data of 100,000 or more Virginia consumers in a year.
• You control or process the personal data of at least 25,000 Virginia consumers and get more than 50% of your total income from selling personal data.

Our beginner’s guide to VCDPA compliance covers a lot of different tips on how you can comply with this law.

WordPress Privacy Compliance: Frequently Asked Questions

I know this is a lot to take in, especially if you’re just getting started with WordPress privacy compliance. So before we wrap up, I want to quickly answer some of the most common questions I hear from beginners.

These answers aren’t meant to replace legal advice, but they’ll help you understand what matters most when it comes to running a privacy-friendly WordPress site.

Do I need a privacy policy if my site doesn’t collect data? 

Yes, even if your site doesn’t seem to collect user data directly, it’s still a good idea to have a privacy policy.

That’s because your site may be collecting information in ways that aren’t immediately obvious. For example, your hosting provider might log visitor IP addresses, or third-party scripts could be tracking behavior in the background.

In those cases, having a privacy policy helps keep you on the safe side of the law.

It also shows your visitors that you’re being transparent, which can go a long way toward building trust.

What are the penalties for non-compliance?

Privacy laws can carry serious penalties if you don’t follow them.

Some regulations include fines of thousands or even millions of dollars. You may also be charged per violation.

For example, under the CCPA, penalties range from $2,500 to $7,500 for each affected user. That can add up fast if the issue affects a large number of people.

But money isn’t the only concern. If users find out their data wasn’t protected, they may lose trust in your site. That kind of damage is hard to repair and can lead to fewer visits, lower engagement, and lost sales.

How often should I review my website’s compliance?

It’s a good idea to review your website’s compliance at least once a year.

You’ll also want to check whenever a privacy law changes or a new one goes into effect. Staying proactive can help you catch small issues early and avoid bigger problems later.

I hope this ultimate guide to WordPress privacy compliance has helped you take the first steps towards creating a compliant site. Next, you may want to see our expert picks for the best security plugins to protect your site or our guide on how to know if your site uses cookies.

If you liked this article, then please subscribe to our YouTube Channel for WordPress video tutorials. You can also find us on Twitter and Facebook.

The post The Ultimate Guide to WordPress Privacy Compliance first appeared on WPBeginner.

When you start thinking about Agentic AI in the right way, you begin to see that it’s not a piece of technology to be wielded; it’s part of a business strategy that sequences various technologies to automate tasks and processes in ways that surpass what humans alone are capable of. This post debunks five common myths about Agentic AI that can hold organizations back in a moment when they absolutely need to surge ahead.

Starting with the misconception that Agentic AI is similar to the ways we’ve been building and experiencing software. Organizations also often feel pressure to start with big, audacious buildouts, when starting small on internal use cases can forge scalable growth. It’s also important to identify use cases for automation that are truly high-value and find ways to orchestrate multi-agent AI systems to complete objectives dynamically, rather than following predefined routes.

Myth #1: Agentic AI is software as usual

With so many apps and SaaS solutions quickly tacking large language models (LLMs) onto their existing user interfaces (UIs), it’s tempting to want to believe that Agentic AI can simply be added to traditional software. In reality, the successful implementation of Agentic AI requires an entirely different approach to software creation.

The linear, staggered waterfall approach to software creation has sprung countless leaks over the years, and applying it within the framework of designing Agentic solutions is a surefire way to drown. Rather than spending months guessing what users want and initiating a laborious and rigid buildout around perceived needs, Agentic AI begins with building. AI agents are quickly propped up around a use case using low- and no-code building tools. The solution is tested and iterated on right away, with multiple iteration cycles taking place over the course of a single day.

Another key distinction is that Agentic AI works around objectives, rather than following predefined routes. In that sense, the work of creating and evolving AI agents is a bit like the process pharmaceutical companies use when developing a new drug. A new medication that’s being investigated as a cure for gout might turn out to be a promising hair growth solution. These kinds of high-value surprises are uncovered through trial and error, fast iteration, and testing.

When it comes to Agentic AI vs chatbot capabilities, traditional approaches to conversational AI fall perilously short. In the not-too-distant past, chatbots used tools like natural language processing (NLP) to understand user requests and automate responses. With the advent of generative tools like LLMs, chatbots are better at disambiguating user requests and can deliver more dynamic responses, but they lack agency. AI agents use LLMs to interact with users and then communicate with other agents, knowledge bases, and legacy software to do real work. Beware of bolt-on solutions calling themselves AI agents. They are chatbots in disguise.

Myth #2: It’s imperative to start big

In order to get moving with Agentic AI, most organizations don’t need a large-scale, public-facing deployment. The key is to think big and start small. It’s often more effective to begin within your organization, automating internal tasks with help from the people who understand them best. This allows orgs to get a handle on sequencing technology in ways that are more efficient and rewarding what humans are able to do on their own.

Stating internally allows orgs to form the groundwork for an ecosystem of Agentic AI that can grow to include customers once they’ve figured out how to optimize Agentic experiences. Starting small and internally requires more than just giving teams access to a sanctioned LLM. At a minimum, there should be a strategy in place for connecting AI agents to some sort of knowledge management system, such as retrieval-augmented generation (RAG).

In one example, an enterprise organization used an agentic system to reduce ticket resolution times from six weeks to one, and cut inbound calls by 35%. They were also able to lower CTS (cost to serve) by 40% and — by reducing the workload of human agents in their contact centers — increase productivity and improve their CSAT (customer satisfaction) score to 83%.

Myth #3: Operations are improved by automating existing workflows

The first move organizations often make when developing use cases for Agentic AI is to try and automate the workflows and processes that humans are already using. While this approach can often get the ball rolling, the real value comes with creating automations that surpass what humans alone are capable of.

Someone placing a call to the IRS (Internal Revenue Service) to follow up on a letter they received in the mail usually encounters a fragmented approach to automation that lumbers along in well-worn ruts. The first hurdle is figuring out which of the unintelligible clusters of voice-automated options most closely applies to their situation. They might repeat that process a few more times as they move through murky layers of the IRS phone tree, unsure if they’re headed to the right department and expecting to wait on hold for hours to find out.

What if, instead:

1. The IRS greeted callers with an AI agent that could verify their personal information while simultaneously cross-referencing recent activity.
2. The AI agent could infer that the taxpayer is calling about a letter that was sent last week.
   The AI agent sees that a payment was received after the letter was sent.
3. The system confirms the reason for the call and relays that information, providing a confirmation number.
4. The user ends the call (fully satisfied) in under five minutes.

Most organizations are teeming with hobbled processes that humans set up to work around disparate systems. Rather than automating those workflows, savvy business and IT leaders are looking for better ways to complete the objectives buried at the center of the mess.

As Robb Wilson (OneReach.ai CEO and founder) wrote in our bestselling book on Agentic AI, Age of Invisible Machines, “not only can Agentic AI running behind the scenes in an organization handily obscure the mess of systems (and graphical UIs), it also binds your ecosystem by standardizing communications, creating a feedback loop that can evolve automations for all your users — customers and employees.”¹

Myth #4: All it takes is some AI Agents

The hype around AI agents often obscures a fundamental truth about what they really are. “AI agents” are not a distinct kind of technology. Rather, they are part of a broader approach for using LLMs as a conversational interface. LLMs have made it far easier for users to initiate action with conversational prompts and for agents to either execute existing code or write their own code. These actions happen within a defined scope, ostensibly to both protect the user and indemnify the organization, but also to create something more guided and specific than the “ask me anything” experience of using something like ChatGPT.

Agents with real agency will have an objective, and they will either complete their objective or look for another agent to hand the objective off to (either if they can’t complete it or after they complete it). It can also hand off to a human agent. To reiterate the point from earlier, this requires more than bolting AI onto existing software. Agentic AI won’t thrive in any single tech provider’s black box. The goal of Agentic AI is not to accumulate separate agents for individual tasks, but to orchestrate multiple AI agents to collaborate around objectives.

Looking at the example of Contract Lifecycle Management (CLM), AI Agent Orchestration begins by examining each phase in a contract lifecycle and thinking through its component steps. If the negotiation process is happening asynchronously, for example, an AI agent might be used to notify parties on both sides when terms have been revised or updates have been requested. Using a design pattern like “nudge,” the agent can keep negotiations moving forward by giving gentle reminders when people need to make decisions. Another AI agent might maintain a change log that’s available to all parties with the ability to create custom views of updates and requests based on user requests (i.e., “show me all of the changes that the client has requested that will require approval from our partners”). There are multiple agents collaborating at each step in the lifecycle.

Agentic AI can streamline the approval process by handling things like scheduling, identity verification, and knowledge management. Additionally, the skills that individual agents specialize in, such as scheduling, identity verification, and knowledge management, are not exclusive to any of the stages related to CLM. Scheduling, identity verification, and knowledge management are functions that have value across departments and processes within an organization. All of it, however, hinges on the orchestration of AI agents.

Myth #5: There is one platform to rule all AI Agents

To give AI agents actual agency requires an orchestration and automation platform that is open and flexible. Organizations need to be able to build AI agents quickly, using no- and low-code tools. They need those agents to communicate with their legacy software systems. AI agents also need to be able to share information with other AI agents, and they all need to be connected to secure knowledge bases that align with the goals of their organization.

These are just the table stakes. To fully embrace Agentic AI, orgs need a technology ecosystem that can quickly integrate the best new technologies as they appear in the marketplace. The marketplace is already headed in this direction, as evidenced by the surge of interest in Model Context Protocol (MCP). Released by Anthropic last November, MCP makes it far easier for AI agents to access the systems where data lives. MCP servers exist in an open-source repository, and Anthropic has shared pre-built servers for enterprise systems, such as Google Drive, Slack, GitHub, Git, Postgres, and Puppeteer.

Sam Altman announced that OpenAI will support MCP across its products, and Google has also released their own Agent2Agent (A2A) protocol as a complement to MCP with support from 50+ partners, including Atlassian, Intuit, PayPal, Salesforce, ServiceNow, and Workday; and leading service providers, such as Accenture, BCG, Capgemini, Cognizant, Deloitte, McKinsey, and PwC.

Microsoft also announced that its Windows Subsystem for Linux (WSL) is now fully open source, which they see as part of the “Agentic Web.” As part of the opening keynote at Microsoft Build 2025, their CTO, Kevin Scott, said, “You need agents to be able to take actions on your behalf … and they have to be plumbed up to the greater world. You need protocols, things like MCP and A2A … that will help connect in an open, reliable, and interoperable way.”² In this moment, organizations need to find platforms that can help them build an open framework for Agentic AI that allows them to integrate new tools as they emerge and grow freely alongside the marketplace.

Sources:

¹Robb Wilson and Josh Tyson, “Age of Invisible Machines”
²Microsoft Build 2025

The article originally appeared on OneReach.ai.

Featured image courtesy: Josh Tyson.

The post Five Myths Debunked: Why Agentic AI Is Much More Than Chatbots appeared first on UX Magazine.

People tend to believe that companies are going to use AI to eliminate as many jobs as possible. It stands to reason that some businesses will try this approach—even though it’s a complete misuse of the technology. What we’re currently seeing, however, is individuals picking up generative tools and running with them, while companies are dragging their feet into integration efforts.

What might happen as a result of this is that consumers will be the ones to bring down companies. There are laws that prevent companies from spamming people with unwanted outbound messages, but there are none stopping consumers from flooding contact centers with AI agents.

It’s basically free for people to cobble together agents that can robocall service centers and flood systems with data designed to get them discounts, or worse, to confuse and deceive. Customers might start hammering a company because word gets out that they give a credit for certain circumstances. This could create a snowball effect where their call centers are flooded with millions of inbound inquiries that are lined up to keep calling, all day long.

Whatever their intentions, it’s free and easy for consumers to scale ad hoc efforts to levels that will overwhelm a company’s resources. So what are companies going to do when their customers go outbound with AI? 

I asked this question recently on the London Fintech Podcast and the host, Tony Clark, had the response I’ve been looking for: “You may have let the genie out of the bottle now, Robb,” he said, looking a bit shocked. “I’m sure the tech is available. I imagine my 14-year-old could probably hook up 11 Labs or something with the GPT store and be off on something like that.”

The truth is, most companies that are evaluating agentic AI are thinking myopically about how they will use these tools offensively. They are ignoring the urgent need for agentic systems that can provide defensive solutions. 

These systems must allow AI agents to detect and stop conversations that are just meant to burn tokens. They need human-in-the-loop (HitL) functionality to make sure agents’ objectives are validated by a person who takes responsibility for the outcomes. This environment also needs canonical knowledge—a dynamic knowledge base that can serve as a source-of-truth for AI agents and humans.

These are the base requirements of an agent runtime. A critical component to integration, an agent runtime is an environment for building, testing, deploying, and evolving AI agents.

• Runtimes maintain agent memory and goals across interactions
• Runtimes enables access to external tools like MCPs, APIs, and databases
• Runtimes allow multi-agent coordination
• Runtimes operates continuously in the background

And in terms of helping businesses use AI defensively, runtimes handle input/output across modalities like text and voice, so AI agents can spot bad actors and alert humans. In UX terms, it’s the backstage infrastructure that transforms your product’s assistant from a button-press chatbot into a collaborative, contextual, goal-oriented experience designed that can proactively protect organizations and their customers. However companies choose to frame it, there’s emerging risk in sitting back and waiting to see what will happen next with AI. It just might be the end of your company.

The post Companies Aren’t Prepared for Outbound AI in the Hands of Consumers appeared first on UX Magazine.

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On the podcast today we have Karla Campos.

Karla has been involved in the WordPress community for over 10 years, starting out in Miami and taking part in meetups and WordCamps before stepping into larger organisational roles. With a background in media and marketing, Karla brings plenty of experience in both web and events to the world of WordPress.

Karla joins us today as a lead organiser for the upcoming WordCamp US 2025, which will take place in Portland at the end of August. Remarkably, this is her first flagship WordCamp, she’s organising before ever attending.

We discuss what motivated Karla to take on this major responsibility, how she balances the volunteer work with her professional life, and the challenges, expected and unexpected, along the way.

We discuss the organisation of such a huge event, from working with a professional production company to handling the logistics, communications, accessibility requests, visas, and more for a thousand-plus attendees. Karla shares how the community side of the event is managed, the late-night worries, and what it really takes, both in time and personal commitment, to make WordCamp US happen, especially as a volunteer.

She also highlights some new initiatives for this year’s event, renewed efforts to welcome students and first-time attendees, including student ticket pricing and the WP Trail Buddy’s program to help newcomers feel at home. She also teases the introduction of a hackathon-style Contributor Day and new remote collaboration options.

If you’ve ever wondered what goes on behind the scenes of WordCamp US, how it’s organised, how volunteers are supported, and what motivates people like Karla to invest their own time and resources, this episode is for you.

Useful links

WordCamp US 2025

 WP Trail Buddy

A design system is more than just a set of colors and buttons. It’s a shared language that helps designers and developers build good products together. At its core, a design system includes tokens (like colors, spacing, fonts), components (such as buttons, forms, navigation), plus the rules and documentation that tie all together across projects.

If you’ve ever used systems like Google Material Design or Shopify Polaris, for example, then you’ve seen how design systems set clear expectations for structure and behavior, making teamwork smoother and faster. But while design systems promote consistency, keeping everything in sync is the hard part. Update a token in Figma, like a color or spacing value, and that change has to show up in the code, the documentation, and everywhere else it’s used.

The same thing goes for components: when a button’s behavior changes, it needs to update across the whole system. That’s where the right tools and a bit of automation can make the difference. They help reduce repetitive work and keep the system easier to manage as it grows.

In this article, we’ll cover a variety of tools and techniques for syncing tokens, updating components, and keeping docs up to date, showing how automation can make all of it easier.

Let’s start with the basics. Color, typography, spacing, radii, shadows, and all the tiny values that make up your visual language are known as design tokens, and they’re meant to be the single source of truth for the UI. You’ll see them in design software like Figma, in code, in style guides, and in documentation. Smashing Magazine has covered them before in great detail.

The problem is that they often go out of sync, such as when a color or component changes in design but doesn’t get updated in the code. The more your team grows or changes, the more these mismatches show up; not because people aren’t paying attention, but because manual syncing just doesn’t scale. That’s why automating tokens is usually the first thing teams should consider doing when they start building a design system. That way, instead of writing the same color value in Figma and then again in a configuration file, you pull from a shared token source and let that drive both design and development.

There are a few tools that are designed to help make this easier.

Token Studio

Token Studio is a Figma plugin that lets you manage design tokens directly in your file, export them to different formats, and sync them to code.

Specify

Specify lets you collect tokens from Figma and push them to different targets, including GitHub repositories, continuous integration pipelines, documentation, and more.

NameDesignTokens.guide

NamedDesignTokens.guide helps with naming conventions, which is honestly a common pain point, especially when you’re working with a large number of tokens.

Once your tokens are set and connected, you’ll spend way less time fixing inconsistencies. It also gives you a solid base to scale, whether that’s adding themes, switching brands, or even building systems for multiple products.

That’s also when naming really starts to count. If your tokens or components aren’t clearly named, things can get confusing quickly.

Note: Vitaly Friedman’s “How to Name Things” is worth checking out if you’re working with larger systems.

From there, it’s all about components. Tokens define the values, but components are what people actually use, e.g., buttons, inputs, cards, dropdowns — you name it. In a perfect setup, you build a component once and reuse it everywhere. But without structure, it’s easy for things to “drift” out of scope. It’s easy to end up with five versions of the same button, and what’s in code doesn’t match what’s in Figma, for example.

Automation doesn’t replace design, but rather, it connects everything to one source.

The Figma component matches the one in production, the documentation updates when the component changes, and the whole team is pulling from the same library instead of rebuilding their own version. This is where real collaboration happens.

Here are a few tools that help make that happen:

A lot of the work starts right inside your design application. Once your tokens and components are in place, tools like Supernova help you take it further by extracting design data, syncing it across platforms, and generating production-ready code. You don’t need to write custom scripts or use the Figma API to get value from automation; these tools handle most of it for you.

But for teams that want full control, Figma does offer an API. It lets you do things like the following:

• Pull token values (like colors, spacing, typography) directly from Figma files,
• Track changes to components and variants,
• Tead metadata (like style names, structure, or usage patterns), and
• Map which components are used where in the design.

The Figma API is REST-based, so it works well with custom scripts and automations. You don’t need a huge setup, just the right pieces. On the development side, teams usually use Node.js or Python to handle automation. For example:

• Fetch styles from Figma.
• Convert them into JSON.
• Push the values to a design token repo or directly into the codebase.

You won’t need that level of setup for most use cases, but it’s helpful to know it’s there if your team outgrows no-code tools.

• Where do your tokens and components come from?
• How do updates happen?
• What tools keep everything connected?

The workflow becomes easier to manage once that’s clear, and you spend less time trying to fix changes or mismatches. When tokens, components, and documentation stay in sync, your team moves faster and spends less time fixing the same issues.

Figma is a collaborative design tool used to create UIs: buttons, layouts, styles, components, everything that makes up the visual language of the product. It’s also where all your design data lives, which includes the tokens we talked about earlier. This data is what we’ll extract and eventually connect to your codebase. But first, you’ll need a setup.

To follow along:

1. Go to figma.com and create a free account.
2. Download the Figma desktop app if you prefer working locally, but keep an eye on system requirements if you’re on an older device.

Once you’re in, you’ll see a home screen that looks something like the following:

From here, it’s time to set up your design tokens. You can either create everything from scratch or use a template from the Figma community to save time. Templates are a great option if you don’t want to build everything yourself. But if you prefer full control, creating your setup totally works too.

There are other ways to get tokens as well. For example, a site like namedesigntokens.guide lets you generate and download tokens in formats like JSON. The only catch is that Figma doesn’t let you import JSON directly, so if you go that route, you’ll need to bring in a middle tool like Specify to bridge that gap. It helps sync tokens between Figma, GitHub, and other places.

For this article, though, we’ll keep it simple and stick with Figma. Pick any design system template from the Figma community to get started; there are plenty to choose from.

Depending on the template you choose, you’ll get a pre-defined set of tokens that includes colors, typography, spacing, components, and more. These templates come in all types: website, e-commerce, portfolio, app UI kits, you name it. For this article, we’ll be using the /Design-System-Template--Community because it includes most of the tokens you’ll need right out of the box. But feel free to pick a different one if you want to try something else.

Once you’ve picked your template, it’s time to download the tokens. We’ll use Supernova, a tool that connects directly to your Figma file and pulls out design tokens, styles, and components. It makes the design-to-code process a lot smoother.

Step 1: Sign Up on Supernova

Go to supernova.io and create an account. Once you’re in, you’ll land on a dashboard that looks like this:

Step 2: Connect Your Figma File

To pull in the tokens, head over to the Data Sources section in Supernova and choose Figma from the list of available sources. (You’ll also see other options like Storybook or Figma variables, but we’re focusing on Figma.) Next, click on Connect a new file, paste the link to your Figma template, and click Import.

Supernova will load the full design system from your template. From your dashboard, you’ll now be able to see all the tokens.

Design tokens are great inside Figma, but the real value shows when you turn them into code. That’s how the developers on your team actually get to use them.

Here’s the problem: Many teams default to copying values manually for things like color, spacing, and typography. But when you make a change to them in Figma, the code is instantly out of sync. That’s why automating this process is such a big win.

Instead of rewriting the same theme setup for every project, you generate it, constantly translating designs into dev-ready assets, and keep everything in sync from one source of truth.

Now that we’ve got all our tokens in Supernova, let’s turn them into code. First, go to the Code Automation tab, then click New Pipeline. You’ll see different options depending on what you want to generate: React Native, CSS-in-JS, Flutter, Godot, and a few others.

Let’s go with the CSS-in-JS option for the sake of demonstration:

After that, you’ll land on a setup screen with three sections: Data, Configuration, and Delivery.

Data

Here, you can pick a theme. At first, it might only give you “Black” as the option; you can select that or leave it empty. It really doesn’t matter for the time being.

Configuration

This is where you control how the code is structured. I picked PascalCase for how token names are formatted. You can also update how things like spacing, colors, or font styles are grouped and saved.

Delivery

This is where you choose how you want the output delivered. I chose “Build Only”, which builds the code for you to download.

Once you’re done, click Save. The pipeline is created, and you’ll see it listed in your dashboard. From here, you can download your token code, which is already generated.

So, what’s the point of documentation in a design system?

You can think of it as the instruction manual for your team. It explains what each token or component is, why it exists, and how to use it. Designers, developers, and anyone else on your team can stay on the same page — no guessing, no back-and-forth. Just clear context.

Let’s continue from where we stopped. Supernova is capable of handling your documentation. Head over to the Documentation tab. This is where you can start editing everything about your design system docs, all from the same place.

You can:

• Add descriptions to your tokens,
• Define what each base token is for (as well as what it’s not for),
• Organize sections by colors, typography, spacing, or components, and
• Drop in images, code snippets, or examples.

You’re building the documentation inside the same tool where your tokens live. In other words, there’s no jumping between tools and no additional setup. That’s where the automation kicks in. You edit once, and your docs stay synced with your design source. It all stays in one environment.

Once you’re done, click Publish and you will be presented with a new window asking you to sign in. After that, you’re able to access your live documentation site.

Automation is great. It saves hours of manual work and keeps your design system tight across design and code. The trick is knowing when to automate and how to make sure it keeps working over time. You don’t need to automate everything right away. But if you’re doing the same thing over and over again, that’s a kind of red flag.

A few signs that it’s time to consider using automation:

• You’re using the same styles across multiple platforms (like web and mobile).
• You have a shared design system used by more than one team.
• Design tokens change often, and you want updates to flow into code automatically.
• You’re tired of manual updates every time the brand team tweaks a color.

There are three steps you need to consider. Let’s look at each one.

Step 1: Keep An Eye On Tools And API Updates

If your pipeline depends on design tools, like Figma, or platforms, like Supernova, you’ll want to know when changes are made and evaluate how they impact your work, because even small updates can quietly affect your exports.

It’s a good idea to check Figma’s API changelog now and then, especially if something feels off with your token syncing. They often update how variables and components are structured, and that can impact your pipeline. There’s also an RSS feed for product updates.

The same goes for Supernova’s product updates. They regularly roll out improvements that might tweak how your tokens are handled or exported. If you’re using open-source tools like Style Dictionary, keeping an eye on the GitHub repo (particularly the Issues tab) can save you from debugging weird token name changes later.

All of this isn’t about staying glued to release notes, but having a system to check if something suddenly stops working. That way, you’ll catch things before they reach production.

Step 2: Break Your Pipeline Into Smaller Steps

A common trap teams fall into is trying to automate everything in one big run: colors, spacing, themes, components, and docs, all processed in a single click. It sounds convenient, but it’s hard to maintain, and even harder to debug.

It’s much more manageable to split your automation into pieces. For example, having a single workflow that handles your core design tokens (e.g., colors, spacing, and font sizes), another for theme variations (e.g., light and dark themes), and one more for component mapping (e.g., buttons, inputs, and cards). This way, if your team changes how spacing tokens are named in Figma, you only need to update one part of the workflow, not the entire system. It’s also easier to test and reuse smaller steps.

Step 3: Test The Output Every Time

Even if everything runs fine, always take a moment to check the exported output. It doesn’t need to be complicated. A few key things:

• Are the token names clean and readable?
  If you see something like PrimaryColorColorText, that’s a red flag.
• Did anything disappear or get renamed unexpectedly?
  It happens more often than you think, especially with typography or spacing tokens after design changes.
• Does the UI still work?
  If you’re using something like Tailwind, CSS variables, or custom themes, double-check that the new token values aren’t breaking anything in the design or build process.

To catch issues early, it helps to run tools like ESLint or Stylelint right after the pipeline completes. They’ll flag odd syntax or naming problems before things get shipped.

Once your automation is stable, there’s a next layer that can boost your workflow: AI. It’s not just for writing code or generating mockups, but for helping with the small, repetitive things that eat up time in design systems. When used right, AI can assist without replacing your control over the system.

Here’s where it might fit into your workflow:

Naming Suggestions

When you’re dealing with hundreds of tokens, naming them clearly and consistently is a real challenge. Some AI tools can help by suggesting clean, readable names for your tokens or components based on patterns in your design. It’s not perfect, but it’s a good way to kickstart naming, especially for large teams.

Pattern Recognition

AI can also spot repeated styles or usage patterns across your design files. If multiple buttons or cards share similar spacing, shadows, or typography, tools powered by AI can group or suggest components for systemization even before a human notices.

Automated Documentation

Instead of writing everything from scratch, AI can generate first drafts of documentation based on your tokens, styles, and usage. You still need to review and refine, but it takes away the blank-page problem and saves hours.

Here are a few tools that already bring AI into the design and development space in practical ways:

• Uizard: Uizard uses AI to turn wireframes into designs automatically. You can sketch something by hand, and it transforms that into a usable mockup.
• Anima: Anima can convert Figma designs into responsive React code. It also helps fill in real content or layout structures, making it a powerful bridge between design and development, with some AI assistance under the hood.
• Builder.io: Builder uses AI to help generate and edit components visually. It's especially useful for marketers or non-developers who need to build pages fast. AI helps streamline layout, content blocks, and design rules.

This article is not about achieving complete automation in the technical sense, but more about using smart tools to streamline the menial and manual aspects of working with design systems. Exporting tokens, generating docs, and syncing design with code can be automated, making your process quicker and more reliable with the right setup.

Instead of rebuilding everything from scratch every time, you now have a way to keep things consistent, stay organized, and save time.

Further Reading

• “Design System Guide” by Romina Kavcic
• “Design System In 90 Days” by Vitaly Friedman

When talking about job interviews for a UX position, we often discuss how to leave an incredible impression and how to negotiate the right salary. But it’s only one part of the story. The other part is to be prepared, to ask questions, and to listen carefully.

Below, I’ve put together a few useful resources on UX job interviews — from job boards to Notion templates and practical guides. I hope you or your colleagues will find it helpful.

As you are preparing for that interview, get ready with the Design Interview Kit (Figma), a helpful practical guide that covers how to craft case studies, solve design challenges, write cover letters, present your portfolio, and negotiate your offer. Kindly shared by Oliver Engel.

The Product Designer’s (Job) Interview Playbook (PDF) is a practical little guide for designers through each interview phase, with helpful tips and strategies on things to keep in mind, talking points, questions to ask, red flags to watch out for and how to tell a compelling story about yourself and your work. Kindly put together by Meghan Logan.

From my side, I can only wholeheartedly recommend to not only speak about your design process. Tell stories about the impact that your design work has produced. Frame your design work as an enabler of business goals and user needs. And include insights about the impact you’ve produced — on business goals, processes, team culture, planning, estimates, and testing.

Also, be very clear about the position that you are applying for. In many companies, titles do matter. There are vast differences in responsibilities and salaries between various levels for designers, so if you see yourself as a senior, review whether it actually reflects in the position.

Catt Small’s Guide To Successful UX Job Interviews, a wonderful practical series on how to build a referral pipeline, apply for an opening, prepare for screening and interviews, present your work, and manage salary expectations. You can also download a Notion template.

In her wonderful article, Nati Asher has suggested many useful questions to ask in a job interview when you are applying as a UX candidate. I’ve taken the liberty of revising some of them and added a few more questions that might be worth considering for your next job interview.

1. What are the biggest challenges the team faces at the moment?
2. What are the team’s main strengths and weaknesses?
3. What are the traits and skills that will make me successful in this position?
4. Where is the company going in the next 5 years?
5. What are the achievements I should aim for over the first 90 days?
6. What would make you think “I’m so happy we hired X!”?
7. Do you have any doubts or concerns regarding my fit for this position?
8. Does the team have any budget for education, research, etc.?
9. What is the process of onboarding in the team?
10. Who is in the team, and how long have they been in that team?
11. Who are the main stakeholders I will work with on a day-to-day basis?
12. Which options do you have for user research and accessing users or data?
13. Are there analytics, recordings, or other data sources to review?
14. How do you measure the impact of design work in your company?
15. To what extent does management understand the ROI of good UX?
16. How does UX contribute strategically to the company’s success?
17. Who has the final say on design, and who decides what gets shipped?
18. What part of the design process does the team spend most time on?
19. How many projects do designers work on simultaneously?
20. How has the organization overcome challenges with remote work?
21. Do we have a design system, and in what state is it currently?
22. Why does a company want to hire a UX designer?
23. How would you describe the ideal candidate for this position?
24. What does a career path look like for this role?
25. How will my performance be evaluated in this role?
26. How long do projects take to launch? Can you give me some examples?
27. What are the most immediate projects that need to be addressed?
28. How do you see the design team growing in the future?
29. What traits make someone successful in this team?
30. What’s the most challenging part of leading the design team?
31. How does the company ensure it’s upholding its values?

Before a job interview, have your questions ready. Not only will they convey a message that you care about the process and the culture, but also that you understand what is required to be successful. And this fine detail might go a long way.

Interviewers closer to business will expect you to present examples of your work using the STAR method (Situation — Task — Action — Result), and might be utterly confused if you delve into all the fine details of your ideation process or the choice of UX methods you’ve used.

• Situation: Set the scene and give necessary details.
• Task: Explain your responsibilities in that situation.
• Action: Explain what steps you took to address it.
• Result: Share the outcomes your actions achieved.

As Meghan suggests, the interview is all about how your skills add value to the problem the company is currently solving. So ask about the current problems and tasks. Interview the person who interviews you, too — but also explain who you are, your focus areas, your passion points, and how you and your expertise would fit in a product and in the organization.

A final note on my end: never take a rejection personally. Very often, the reasons you are given for rejection are only a small part of a much larger picture — and have almost nothing to do with you. It might be that a job description wasn’t quite accurate, or the company is undergoing restructuring, or the finances are too tight after all.

Don’t despair and keep going. Write down your expectations. Job titles matter: be deliberate about them and your level of seniority. Prepare good references. Have your questions ready for that job interview. As Catt Small says, “once you have a foot in the door, you’ve got to kick it wide open”.

You are a bright shining star — don’t you ever forget that.

• Remote + In-person
• IXDA
• Who Is Still Hiring?
• UXPA Job Bank
• Otta
• Boooom
• Black Creatives Job Board
• UX Research Jobs
• UX Content Jobs
• UX Content Collective Jobs
• UX Writing Jobs

Useful Resources

• “How To Be Prepared For UX Job Interviews,” by yours truly
• “UX Job Search Strategies and Templates,” by yours truly
• “How To Ace Your Next Job Interview,” by Startup.jobs
• “Cracking The UX Job Interview,” by Artiom Dashinsky
• “The Product Design Interview Process,” by Tanner Christensen
• “10 Questions To Ask in a UX Interview,” by Ryan Scott
• “Six questions to ask after a UX designer job interview,” by Nick Babich

You can find more details on design patterns and UX in Smart Interface Design Patterns, our 15h-video course with 100s of practical examples from real-life projects — with a live UX training later this year. Everything from mega-dropdowns to complex enterprise tables — with 5 new segments added every year. Jump to a free preview. Use code BIRDIE to save 15% off.

If you regularly collect form submissions in WordPress, then exporting that data manually can quickly become a chore. Whether you’re tracking leads, orders, or feedback, downloading all those entries one by one takes time, and it’s easy to miss something important.

Unfortunately, WordPress doesn’t offer a built-in way to auto export form entries. But with WPForms, I discovered that I could automate the entire process using their export tool—no need to install extra plugins or mess with custom code.

Instead of manually downloading CSV files or copying data from the dashboard, WPForms saves entries in clean, structured files on a schedule you can control.

In this guide, I’ll show you how to set up automatic form exports in WPForms so that your submissions stay organized without any extra effort.

Why Auto Export WordPress Form Entries?

Automatically exporting WordPress form entries lets you save and organize data from those form submissions without any manual effort.

Instead of logging in to download submissions every time someone fills out a form, you can automatically send the data to your email, cloud storage account, or another connected app.

It’s a simple way to keep everything sorted, backed up, and accessible, without having to think about it.

Most WordPress website owners rely on forms to collect leads, orders, feedback, or bookings. But once submissions start adding up, manually managing them takes more and more time. That’s where auto export becomes really useful.

With automatic exports, you can:

• Back up form entries to a location you control.
• Cut down on repetitive admin work.
• Keep your data organized and easy to access.
• Avoid missing or overlooking submissions.
• Simplify your reporting and follow-up process.

Once it’s running, auto export takes care of everything in the background, so you can focus on the work that actually moves your site forward.

Now, I’ll show you how to auto export form entries using WPForms:

How to Auto Export WordPress Form Entries

The best way to auto export WordPress form entries is by using WPForms, which is the best contact form plugin for WordPress.

It comes with a powerful Entry Automation addon designed exactly for this purpose.

Whether you want to email reports regularly, back up submissions to Google Drive, or automatically delete entries after they’re processed, this addon quietly handles everything in the background—no manual steps required.

At WPBeginner, we use WPForms ourselves to create all kinds of forms, from simple contact forms to our annual reader survey.

We’ve also tested all its features thoroughly and included them in our detailed WPForms review.

It’s one of those tools that just works and saves us time behind the scenes, which is why I confidently recommend it to beginners and pros alike.

Plus, getting started with it is quick and easy.

Step 1: Install and Activate the WPForms Plugin

First, you need to install and activate the WPForms plugin.

If you’re not sure how to do this, then we have a step-by-step guide on how to install a WordPress plugin to help you out.

Upon plugin activation, you have to activate your license key. To do this, go to the WPForms » Settings page in your WordPress dashboard and add your license key.

You can get this information from your account area on the WPForms website. This will unlock all the features available in your plan, including access to premium addons like Entry Automation.

Now that your license is active, head over to the WPForms » Addons page from your WordPress admin sidebar.

Here, look for the ‘Entry Automation Addon’ in the list. Once you find it, click the ‘Install Addon’ button to activate it on your website.

Step 2: Set Up the Form You’ll Use for Automatic Exports

Now that WPForms and the Entry Automation addon are active, it’s time to create the form with the entries you want to export automatically.

To get started, visit the WPForms » Add New page in your WordPress dashboard and a name for your form.

Then, you can either choose a premade template like a contact form, registration form, or feedback form—or build one from scratch using the drag-and-drop builder.

If you want to speed things up even more, WPForms includes an AI Form Builder that can generate a complete form for you in seconds.

All you have to do is type in a short prompt, like ‘a simple customer feedback form,’ and the AI will instantly create a form with the right fields, layout, and structure. I’ve tested this feature myself, and it works really well.

Now, you will be taken to the visual builder where you can easily customize your form by dragging fields from the left panel into your form layout on the right.

You can add fields like Name, Email, Dropdowns, Checkboxes, File Upload, and more based on the type of information you need to collect.

If you’d like more help building the right form, I’ve got you covered. At WPBeginner, we’ve written step-by-step tutorials to walk you through different form types:

• How to Create a Contact Form in WordPress (Step by Step)
• How to Create a User Registration Form in WordPress
• Beginner’s Guide to Creating an Online Order Form in WordPress
• Ways to Use Conditional Logic in WordPress Forms (Use Cases)
• How to Create a WordPress Form with Payment Options (Easy Way)

Once your form looks good, you can configure its confirmation email settings. Then, click the ‘Save’ button at the top to store your changes.

Step 3: Set Up Automatic Export for Your Form Submissions

Now that your form is ready, it’s time to automate your exports so that you don’t have to manually download form entries ever again.

To do this, switch to the Settings » Entry Automation tab in the WPForms builder. This is where you’ll manage everything related to automatic exporting and deleting entries.

To begin, click the ‘Add New Task’ button.

Once you do that, a prompt will open up, where you have to give a name to your task. I recommend choosing something clear like ‘Weekly Contact Form Export to Email’ so it’s easy to remember later.

This task will be like setting up a small workflow for your form. You can even create multiple tasks for one form, such as one task to send weekly email reports and another to back up entries to Google Drive.

After entering the name, click the ‘OK’ button to move forward.

Next, you’ll be asked to choose a task type.

WPForms gives you two options: Export Entries and Delete Entries. For now, you need to select the ‘Export Entries’ option.

You can always come back later and set up a deletion task if needed. For example, to automatically remove old submissions after 30 days.

After choosing to export entries, you’ll see a few settings related to how your export file should be named. You can type a name manually, but I recommend using Smart Tags.

These tags can automatically pull in things like the form name or the date, which helps keep your files organized without any extra work on your part.

Just click the Smart Tag icon to see your options and insert the ones that make sense for you.

Next, let’s talk about how your form entries will be exported and where they’ll end up. I recommend choosing your file format first — this determines how your data will be organized when it’s sent out.

WPForms gives you several file types to pick from, and each one has its own advantages:

• CSV – The default option, perfect for spreadsheet tools like Microsoft Excel or Google Sheets.
• Excel (XLSX) – This format preserves basic styling and structure, making reports look cleaner and more professional right out of the box. I recommend this option if you plan to share the file directly with clients or non-techy people who use Microsoft Excel.
• PDF – Great for clean, printable summaries. I like this option when I want something polished to share in a meeting.
• JSON – Best suited for developers or users integrating the data into other systems or apps.

Once that is done, it’s time to decide where the exported file should go.

WPForms lets you automate this too, so you don’t have to manually send or upload anything. Here are your destination options:

• Email – Send the export to one or more email addresses.
• Google Drive – Save a copy of the export directly to your Google Drive account.
• Dropbox – Store the file in your Dropbox folder for easy sharing and access.
• FTP – Upload the export to a server using FTP. This option is designed for more advanced users or developers who need to send data to a custom application or a separate server.

Once you select your destination, WPForms will walk you through the connection steps.

For example, if you choose ‘Email’, then you will need to add the email address where the entries would be sent. On the other hand, if you choose Dropbox, then you will have to integrate it with WPForms.

However, you don’t need to worry, since the plugin makes the process super beginner-friendly. Just follow the steps on the screen.

Step 4: Choose Form Fields and Apply Entry Filters Before Exporting

After setting your export format and destination, scroll down to configure what data should be included in the export and whether you want to filter the entries.

First, you’ll see the ‘Entry Information’ section. This area is neatly divided into two parts: Form Fields and Additional Information, giving you full control over what gets shared.

Under ‘Form Fields’, you’ll see the actual fields from your form—like Name, Email, and Comment or Message. Just check the boxes for the fields you want to include.

If you’re exporting a longer form with multiple inputs, you can use the ‘Select All’ option to save time.

Then there’s the ‘Additional Information’ section. This includes extra details that WPForms tracks automatically, like Entry ID, Entry Date, Entry Notes, and Type.

You can select any combination of these fields to customize your export. I’ve found this especially useful if you only need a few key pieces of information for a weekly report or want to hide internal notes before sharing a file externally.

Below that is the ‘Filter’ section. This is where you can narrow down your export to include only the entries that meet certain conditions—for example, submissions from a certain date range or entries that include specific responses.

By default, WPForms sets the filter to ‘Any Field contains’, but you can customize this to narrow down entries based on specific form fields and values.

For example, if your contact form includes a dropdown like ‘Reason for Contact’, you could filter to only export entries where the reason is ‘Support Request’ or ‘Business Inquiry’.

This helps keep your exports focused on the types of messages you care about most.

You can also filter based on the status of the entry. WPForms lets you choose whether to include entries that are Published, Abandoned, or marked as Spam.

I recommend this filter if you want clean, finalized submissions in your export, or if you want to analyze incomplete or flagged messages separately.

Additionally, you can choose to export all contact form entries or just the new submissions since your last export. This is a useful option for automating reports without duplicating data.

Once you’ve chosen which fields and filters to apply, WPForms will tailor the export exactly to your needs.

Step 5: Schedule WordPress Form Entries Export

Once your export settings and filters are in place, the final step is to schedule when you want WPForms to run the export automatically.

For this, scroll down to the ‘Schedule’ section.

You can start by choosing how often the export should happen. You can set it to run daily, weekly, or monthly, depending on how often you need updates.

Next, pick the specific day(s) you want the export to run—like every Monday or the 1st of each month. You also need to add a start date and, optionally, an end date if you’re only exporting for a limited time.

WPForms will run the export at midnight by default, but you can customize the time of day to fit your team’s workflow or reporting schedule.

Once that’s done, the plugin takes care of the rest—automatically generating and sending the export file exactly as you configured.

Step 6: Add a Task to Delete Form Entries After Export (Optional)

Once your form is live and the automation is running, you can go one step further by setting up a separate task to delete the entries after they’ve been exported.

WPForms doesn’t bundle this into the export task itself. Instead, you’ll need to create a new task with the ‘Delete Entries’ option and configure it to run after the export.

Don’t forget to toggle the ‘Run After Previous Task’ switch to make sure the tasks run in sequence.

You can even drag to reorder the tasks, so deletion only happens once the data has been safely exported.

This is a great way to keep your WordPress database lean and prevent data bloat. A smaller database helps your site run smoothly and makes your website backups smaller and faster to complete.

It’s also a good data privacy practice. 

By not storing user data on your website longer than necessary, you reduce risk and can more easily comply with privacy regulations like GDPR.

Step 7: Monitor Everything from the Automation Dashboard

If you’re managing multiple forms or scheduling regular exports, then having a clear overview of all your automated tasks is a game-changer.

The Automation Dashboard in WPForms makes this easy by showing all active tasks in one place.

I found this incredibly helpful when testing the feature because it gave me instant visibility into what was running, when, and whether everything was working as expected.

You can access it by going to the WPForms » Tools » Entry Automation page, where you’ll be able to:

• View all forms with automation tasks configured.
• Review task types, schedules, and current status.
• Confirm whether export or delete tasks have run successfully.

It’s the simplest way to stay organized and ensure everything is running exactly as planned.

🔄 Bonus: Take Automation Even Further with Uncanny Automator

Automatically exporting data from your WordPress forms is just one way you can save time. I also recommend setting up more automated workflows with Uncanny Automator.

It is the best WordPress automation plugin and comes with built-in integration for WPForms, so you can trigger powerful workflows the moment someone submits a form.

While WPForms’ Entry Automation is perfect for managing the entries themselves (like exporting or deleting them), Uncanny Automator lets you use a form submission as a trigger to perform actions in other plugins or apps.

For example, you can automatically send a notification to Slack, create a new user account, enroll someone in a course, or even generate a WooCommerce coupon when someone fills out a form.

This can save you tons of time and streamline tasks that used to take hours. It’s a great way to level up your site’s automation without writing any code.

To get started, just see our tutorial on how to create automated workflows in WordPress with Uncanny Automator.

Frequently Asked Questions About WordPress Form Entries

Here are some questions that are frequently asked by our readers about auto exporting WordPress form entries:

What are the limitations of using email to auto export form data?

The main limitation is that the data isn’t stored in a central dashboard. Instead, it lives in your email inbox. That means you’ll need to manually sort, organize, or back up the data if you want to keep records long-term.

There’s also a higher risk of missing something important if your inbox gets cluttered.

In my experience, this setup works well for smaller sites or solo business owners who just want a quick way to check form entries without logging into WordPress.

But as your site grows, you might need something more scalable.

When that time comes, WPForms makes it easy to switch to cloud storage options like Dropbox or Google Drive, so your entries are always backed up and easy to manage.

Is there a way to stop form spam from being exported?

Yes. WPForms includes built-in spam protection tools like Google reCAPTCHA, hCaptcha, and its own smart honeypot feature that help block junk submissions before they ever reach your inbox.

On top of that, WPForms also has a form entry filter that ignores abandoned or partial form submissions. That means your exports only include complete and legitimate entries, which saves time and keeps your records clean.

For details, see our guide on how to block contact form spam in WordPress.

Can exporting form entries reduce database bloat?

Yes, this helps keep your database clean and optimized. When you export entries and then delete them from WordPress, you avoid unnecessary data buildup. This makes backups faster and your admin area more responsive.

Will auto-exporting form entries slow down my WordPress site?

No, auto-exporting form entries won’t affect your site’s speed if set up correctly.

The export process happens in the background, so visitors won’t notice any slowdown when submitting a form. Think of it like a scheduled task on your computer—it runs quietly at a set time without interrupting what you’re doing. 

I didn’t experience any performance issues during testing, even on a site with multiple forms running.

I hope this article helped you learn how to auto export WordPress form entries. You may also be interested in our beginner’s guide on how to create GDPR compliant forms in WordPress and our list of best practices for contact form page design.

If you liked this article, then please subscribe to our YouTube Channel for WordPress video tutorials. You can also find us on Twitter and Facebook.

The post How to Auto Export WordPress Form Entries (The Easy Way) first appeared on WPBeginner.

A few years ago, I got my first data deletion request from a user. I’ll admit, I panicked a little. I knew I needed to respect their privacy rights, but I had no idea how to actually remove their data from my WordPress site without breaking anything.

That experience led me to discover something helpful: WordPress has built-in tools made for exactly this situation. Once you know where to find them, they make handling data requests surprisingly easy.

In this guide, I’ll walk you through how to use Export and Erase Personal Data tools in WordPress.

Whether you’re preparing for GDPR, building trust with your users, or just want to be ready for future requests, this tutorial will help you do it with confidence.

What is Personal Data?

Personal data is any information that can be used to identify a person, either directly or indirectly.

On a WordPress site, this includes obvious details like names, usernames, and email addresses.

These are often collected when someone creates an account on your website, submits a contact form, subscribes to your email newsletter using a plugin like WPForms, or leaves a comment on a blog post.

It also includes technical data like IP addresses, which can reveal a visitor’s general location. Analytics tools, comment systems, and security plugins often collect this by default.

Personal data can also include behavioral information, such as page views, session activity, or form responses that show user preferences. Even metadata—like the time someone submitted a comment or logged in—counts as personal data under most privacy laws.

All of this information can help build a profile of your users, which is why it’s important to manage it carefully.

Ready to learn how to export and erase user data in WordPress? Simply use the quick links below to jump to the section you want to read first:

How to Accept Data Export and Deletion Requests

If someone wants to access or delete their personal data, then you’ll need a simple way for them to send that request.

The easiest method is to add a form to your WordPress site that collects their name, email address, and any extra details you need to identify them.

I recommend using WPForms for this. It’s beginner-friendly and includes ready-made templates like ‘Right to Erasure Request Form’ and ‘Data Request Form’, so you don’t need to start from scratch.

WPForms includes drag-and-drop templates that make it easy to build your form without starting from scratch. You can customize the fields and publish the form in just a few clicks.

There is a WPForms Lite version that is 100% free to use. However, we’ll be using WPForms Pro in this guide because it comes with the ‘Right to Erasure Request Form’ and ‘Data Request’ templates.

First, you’ll need to install and activate WPForms Pro. If you need help, please see our guide on how to install a WordPress plugin.

Once the plugin has been activated, head over to WPForms » Settings in your WordPress dashboard.

From here, the first thing you have to do is enter your license key into the ‘License Key’ field. You can find this information in your WPForms account.

That done, head over to WPForms » Add New.

Here, type a name for your form into the ‘Name Your Form’ field.

Your site visitors won’t see the name, so it’s just for your reference.

Now, you’ll need to select the template you want to use.

In the search field, start typing in either ‘Right to Erasure Request Form’ or ‘Data Request’, depending on the kind of form you want to create.

When you find the template you want to use, simply click its ‘Use Template’ button.

This will launch WPForms’ drag-and-drop form builder.

Here, you’ll see a live preview on the right and form fields in the left-hand menu.

To customize any of the template’s built-in fields, simply click to select that field. The left-hand menu will then show all the settings you can use to customize it.

Want to add more fields to your form?

Just find the field you want on the left side of your screen and drag and drop it right into your form’s live preview.

For more detailed instructions, see our tutorial on how to create a contact form in WordPress.

Once you’re happy with your form, simply click the ‘Save’ button at the top to close the form builder.

Next, open the page or post where you want to add the form that you just created.

From here, click the add block ‘+’ button.

In the popup that appears, start typing in ‘WPForms.’

When the right block appears, simply click to add it to the page or post.

Once you’ve done that, you need to open the block’s dropdown menu and select the form you just created.

You can now publish or update this page as normal to make the form live on your site.

Now, simply repeat this process to create separate forms for data access requests and data erasure requests.

How to Monitor Data Access and Erasure Requests

Once your forms are live, you’ll need a way to track incoming data request submissions from your users.

Fortunately, WPForms makes this easy by storing every form entry in your WordPress dashboard.

To find these requests, just go to WPForms » Entries.

Simply click on the form you want to review.

You’ll now see a list of submissions, including any data access or erasure requests users have sent.

To stay compliant with privacy laws like the General Data Protection Regulation (GDPR), it’s important to review and respond to these requests promptly.

Now, I’ll show you how to export and erase personal data in WordPress.

How to Export Personal Data in WordPress

When someone requests a copy of their personal data, WordPress has a built-in tool that lets you export that information and send them a link to download it.

This step is required under privacy laws like the Personal Data Protection Law (PDPL). It’s also a good way to build trust with your users by showing them exactly what data you’ve collected from them.

To begin, you need to go to Tools » Export Personal Data in your WordPress dashboard.

From here, you’ll enter the user’s email address or username and choose how to handle the request.

At this point, you have two options: you can either create the request directly in your WordPress dashboard, or you can send the user an email asking them to confirm that they want to export their data.

Let’s explore both options.

Option 1: Request Confirmation via Email

If you want to make sure the request is genuine, WordPress lets you send a confirmation email first. This is a good option when you’re unsure about the user’s identity.

To do this, check the box next to ‘Send personal data export confirmation email.’ Then click on ‘Send request.’

The user will receive an email with a confirmation link.

They simply need to click on it.

Then, they’ll see the following message:

“The site administrator has been notified. You will receive a link to download your export via email when they fulfil your request.”

WordPress will now notify you via email.

This email includes some basic information about the user who made the request.

You can click the link in this email to go straight to the Tools » Export Personal Data screen.

Here, you’ll see the user’s request is now marked as ‘Confirmed.’

To go ahead and process this request, click on ‘Send export link.’

With that done, the user will receive an email containing a link to download their data as a ZIP file.

Now, WordPress will mark the request as ‘Completed’ in your dashboard. The request will also appear in a separate ‘Completed’ tab, along with all your other completed data export requests. 

In this way, WordPress creates a complete record of all your completed requests. This means you can prove your compliance if you’re ever audited or someone questions your privacy practices. 

With that in mind, I recommend keeping a complete log. 

However, if you want to remove a completed request at any point, just click its ‘Remove Request’ link.

Option 2: Export the Data Immediately

Alternatively, you can create a data request directly in your WordPress dashboard without sending a confirmation email first.

This is helpful if you need to process the data request immediately or if you’re confident that the person making the request is genuine.

For example, they might use an email address that’s already linked to their account or contact you through a support channel where you’ve verified their identity.

In these cases, make sure to uncheck the box next to ‘Send personal data export confirmation email.’

Then, go ahead and click ‘Send request.’ 

This creates the request in your WordPress dashboard, with the status ‘Confirmed.’

To send this person an email with a link to download their data, just click ‘Send export link.’

You can see an example of how this email looks in the previous section.

As I mentioned before, WordPress will now mark this request as ‘Completed’ in your dashboard. Once again, this is proof that you acted on the visitor’s request, which will be invaluable if you ever need to prove your compliance. 

How to Erase Personal Data in WordPress

If someone asks you to delete their personal data, then WordPress has a built-in tool that helps you do that safely.

This step is required under privacy laws like the Virginia Consumer Data Protection Act (VCDPA), and it’s a key part of staying compliant with GDPR, PDPL, and other international regulations.

The process is similar to exporting data: you create a request, optionally confirm it by email, and then erase the data from your WordPress dashboard.

To begin, go to Tools » Erase Personal Data in your WordPress admin area.

In the ‘Username or email address’ field, just type in the email address or username of the person who has asked you to delete their personal data. 

At this point, you can either send a confirmation email to the user or go ahead and create the request in your WordPress dashboard.

Option 1: Send a Confirmation Email

To start, you can ask the user to confirm that they truly want to delete all their personal data.

Erasing a user’s data is a big step, so I suggest sending this email even if the request seems genuine because it gives the user a chance to change their mind.

To request confirmation, check the box next to ‘Send personal data erasure confirmation email.’

You can then click the ‘Send request’ button.

The user will now get an email about the data deletion request with a link to confirm that they want to delete their data.

If they click this link, they’ll see a screen with this message:

“The site administrator has been notified. You will receive an email confirmation when they erase your data.”

You will now get an email confirming that the user wants to erase their data.

To fulfil this request, either click the URL in the email or head back to the Tools » Erase Personal Data screen in your WordPress dashboard. 

On this screen, you’ll see the user’s name with a ‘Confirmed’ status.

To go ahead and delete this person’s data, click on ‘Erase personal data.’

As soon as that’s done, WordPress will send the user an email confirming that you’ve removed their data.

This email also includes a link to your privacy policy, so the person can get more information if they want. 

In your WordPress dashboard, this request will now be marked as ‘Completed.’

As I’ve already mentioned, having a record of these requests will be helpful if you’re ever audited. 

Option 2: Delete the Data Immediately

Alternatively, you can create an erasure request directly in the WordPress dashboard without sending a confirmation email first. 

This is useful if you need to act on a request straight away. It can also be handy when you’re confident that the request is genuine and the user definitely wants to delete all their personal data.

For example, you might get the request through a secure, verified login area on your membership site, which confirms the user’s identity.

In that case, make sure you uncheck the box next to ‘Send personal data erasure confirmation email.’ You can then go ahead and click on ‘Send Request.’

WordPress will now create this request in your dashboard and mark it as ‘Confirmed.’

To go ahead and process this request, click on ‘Erase personal data.’

Now, WordPress will send the person an email confirming that you’ve deleted their data.

As with data exports, WordPress will mark this request as ‘Completed.’

Ensure Your Site is Fully GDPR Compliant

Exporting and erasing personal data is an important step, but it’s not the only thing you need to do to make your WordPress compliant with different privacy laws.

To fully meet privacy standards like the General Data Protection Regulation (GDPR), you’ll also want to:

• Use GDPR-friendly plugins. You need to make sure the plugins you install handle personal data responsibly. You can start with our list of the best GDPR plugins for WordPress.
• Install a privacy compliance plugin. With a plugin like WPConsent, you can display cookie consent popups, record and manage user consent, and automatically block tracking scripts before users give their consent.
• Display a detailed privacy policy and cookie policy on your website. For details, see our guide on how to add a privacy policy in WordPress.

To see all our tips, you can read our complete guide to GDPR compliance in WordPress.

Bonus Tip: Create a Do Not Sell or Share My Personal Info Page

If your website gets visitors from California or other places with strict privacy laws, then you may have extra legal responsibilities. One of those is giving users a way to opt out of having their personal information sold or shared.

The easiest way to do this is by creating a “Do Not Sell or Share My Personal Info” page. This gives users a clear place to make opt-out requests and helps your site stay compliant with laws like the California Consumer Privacy Act (CCPA).

Your opt-out page should include a short explanation of your data practices and a simple form where visitors can submit their request. And fortunately, it’s easy to create this page with WPConsent.

WPConsent also lets you log these requests for your records and include consent options in your cookie popup, making it a great all-in-one solution.

To see step-by-step instructions, check out our full guide: How to Create a Do Not Sell My Info Page in WordPress.

FAQs About Personal Data Management in WordPress

Knowing how to manage personal data isn’t just about legal compliance—it also helps build trust with your audience.

To make things easier, I’ve answered some of the most common questions WordPress users have about handling personal information.

I hope this guide has helped you learn how to export and erase personal data in WordPress. Next, you may want to see our expert picks of the best GDPR plugins to improve compliance, or our guide on how to keep personally identifiable info out of Google Analytics.

If you liked this article, then please subscribe to our YouTube Channel for WordPress video tutorials. You can also find us on Twitter and Facebook.

The post How to Export and Erase Personal Data in WordPress first appeared on WPBeginner.

July was a big month for WordPress, with major updates across AI, automation, and community initiatives. Several plugins rolled out real AI features right inside the dashboard, making content creation and SEO faster and easier.

On the community side, we saw exciting momentum. WordPress.org launched a new internship program for university students, WooCommerce introduced key accessibility improvements, and multilingual support expanded across popular tools.

In this edition of WPBeginner Spotlight, we’ll walk you through the biggest news, updates, and tools that stood out.

AIOSEO Launches Built-in AI Content Generator to Boost Content Creation 🪄

All in One SEO (AIOSEO) has launched a powerful AI Content Generator inside the WordPress editor. It’s designed to help you write faster, optimize your content, and overcome writer’s block.

The tool is integrated into the AIOSEO sidebar of the block editor, so you don’t need to switch between apps or tabs while writing.

You can use the AI generator to write optimized SEO titles and meta descriptions that improve click-through rates. It can also generate content sections like FAQs with schema or article summaries.

AIOSEO’s tool also helps with content promotion by generating tailored posts for Facebook, X, and LinkedIn. You can even rewrite specific sentences or entire paragraphs to better match your tone or target audience.

Additionally, the update includes support for llms.txt file, which is a new file that guides AI tools like ChatGPT and Gemini to your most useful content. This can help them understand your site better and link back to it in their answers.

WPForms Launches Entry Automation—Your Form Data Now Manages Itself

WPForms has introduced Entry Automation, a new feature that lets you create automated, scheduled workflows for your form entries.

You no longer have to manage form data by hand. With Entry Automation, you can export or delete entries automatically based on your own rules.

You can create a custom schedule for each form and set actions to run daily, weekly, or monthly—even down to the exact day and time.

When exporting entries, you can use smart filters to choose exactly which data to include, based on form fields or status. The CSV file is then emailed to you automatically, so you never miss an important lead.

Entry Automation is a big time-saver if you manage leads, registrations, or surveys. It also keeps your database clean by removing old or unnecessary entries on a schedule you control.

Overall, Entry Automation is a powerful upgrade for anyone who relies on form data. It reduces manual work and keeps your submissions organized and consistent.

WordPress AI Building Blocks Introduced—MCP, SDKs, and Smart APIs for the Future of Publishing

The WordPress project has officially unveiled its plan for integrating AI directly into the platform. This new initiative introduces several “Building Blocks” that aim to create a unified, ethical AI framework across the WordPress ecosystem.

For developers, the AI team is releasing new AI Software Development Kits (SDKs). These toolkits will make it much easier to build powerful AI features into plugins and themes, while keeping the user experience consistent.

At the center of the framework are Smart APIs, which let WordPress connect to different AI services. This gives users the freedom to choose the models they want instead of being locked into one provider.

A key part of this is the Abilities API. It creates a shared language that helps AI tools like ChatGPT and Claude understand what your site can do—and even perform tasks like creating content or managing media for you.

The overall goal is to democratize AI for website owners by making powerful tools accessible to everyone while maintaining user control and open-source principles. These building blocks lay the foundation for what’s next, including AI-powered editing tools and smarter media management.

WPBeginner Turns 16 Years Old

This month, WPBeginner celebrated our 16th birthday. Since our website was founded in 2009 by Syed Balkhi, WPBeginner has grown into the largest free WordPress resource for beginners.

Over the years, the mission has stayed the same: make it easy for anyone to create a website with WordPress, regardless of their technical skill level.

To celebrate, WPBeginner hosted our biggest giveaway yet—offering over $20,000 in prizes. A total of 87 winners received premium WordPress plugins and tools to help grow their websites.

We’re deeply grateful 🙏 for the community support that’s helped WPBeginner grow and thrive. We look forward to sharing helpful tutorials, guides, and resources for many years to come.

Free Recurring Payments Now Available on WP Simple Pay —No Upgrade Needed

WP Simple Pay has made recurring payments available to all users by adding the feature to its free Lite version. This feature was previously limited to Pro users, but now anyone can create and manage subscriptions without upgrading.

This is a big update for small businesses, creators, and nonprofits that rely on recurring revenue but don’t need a full eCommerce setup. You can now accept donations, membership fees, or payments for ongoing services right from your WordPress site.

Setup is still simple. You can create a Stripe subscription plan with preset weekly, monthly, or yearly billing, then link it to a payment form on your site in minutes.

The update also adds new form templates and improved security, powered by Stripe’s Unified Payment Element (UPE). By unlocking this key feature, WP Simple Pay helps more users build sustainable revenue directly on WordPress.

WordPress Credits Program Brings University Students Into Open Source

WordPress.org has launched the WordPress Credits program, a new initiative designed to bring university students into the world of open-source development. It works like a structured internship, connecting students with experienced mentors to work on real WordPress projects.

Through this program, students from all fields of study can contribute to WordPress core, themes, plugins, and community teams while earning academic credit from their universities. This provides a clear pathway for young developers, designers, and writers to gain valuable real-world experience.

The pilot program was developed in partnership with the University of Pisa and has already attracted significant interest. Now, the WordPress Foundation is inviting more universities and educational institutions to join the initiative.

The program helps bring new talent into the open-source community. By building a steady pipeline of contributors, WordPress is investing in the project’s long-term growth and innovation.

Charitable Unlocks Square Donations and Donor Trust to Add Social Proof to Your Fundraising Campaigns

Charitable has rolled out two major updates to improve fundraising in WordPress. The plugin now includes a direct, built-in integration with Square, which offers another major payment gateway option for collecting donations.

It’s available to both Lite and Pro users and supports credit cards, debit cards, Apple Pay, and Google Pay. Because it’s part of the core plugin, there’s no need for a separate add-on, and performance is smoother, too.

The second new feature is DonorTrust, a tool designed to increase conversions using social proof. It displays small, real-time notifications on your site whenever someone makes a donation.

These non-intrusive popups are fully customizable and can be configured to show donor names, locations, and donation amounts. Seeing other people donate builds trust and adds urgency, making visitors more likely to give to your cause.

BuddyBoss App Now Supports 20+ Languages With Multilingual App Interface

BuddyBoss has made its mobile app more accessible to global communities by adding full multilingual support. App users can now switch the entire interface to their preferred language from profile settings, creating a more inclusive experience

The app automatically detects a user’s device language on first launch and includes built-in translations for over 20 languages, including Spanish, French, German, and Japanese. This covers all core interface elements, including buttons and navigation menus.

For community owners, this is a big step forward for international SEO. It’s especially helpful in regulated markets like the EU and Canada, where native-language support is often required. The feature is available to all BuddyBoss App users at no extra cost.

While the app interface is automatically translated, community owners can use WPML’s AI-powered services to translate custom content like pages and posts. This creates a fully localized experience and helps you connect with members around the world.

WPCode Just Made Custom Snippets Smarter—38 Tags and a New Import Tool

WPCode has enhanced its popular code snippets plugin with powerful new smart tags and a migration tool. The latest version adds 38 smart tags that let you insert dynamic information into your snippets.

These tags work like dynamic placeholders, helping you create personalized, context-aware content without writing complex PHP. That means your snippets are easier to reuse and adapt across your site.

The smart tags can pull data from popular plugins like WooCommerce, Easy Digital Downloads, MemberPress, and All in One SEO. For example, you could automatically insert a product’s price or a post’s SEO title into a custom script.

The update also includes a new import tool specifically designed for users of the old Post Snippets plugin, which is no longer maintained. It helps you safely migrate your existing snippets to WPCode in just a few clicks.

SearchWP Adds Multiple Results Templates, Compatibility with Site Builders, and Promoted Search Ads

SearchWP has released a major update that gives site owners significantly more control over their website’s search results.

You can now create multiple search results templates to display different layouts for different types of content.

For example, you could show a grid layout for WooCommerce products, a list view for blog posts, and a unique design for documentation pages, all from the same search bar. This helps create a more intuitive experience for your visitors.

SearchWP has also improved compatibility with popular site builders like Elementor, Divi, Beaver Builder, and Bricks. You can now use dedicated blocks for adding search forms and results pages directly within your favorite WordPress page builder, without needing to mess with shortcodes.

The update also adds Promoted Search Ads—a way to feature specific content at the top of search results for certain keywords. It’s like an internal ad system, great for highlighting products, cornerstone content, or special offers.

In Other News

• WPConsent now includes one-click geolocation-based consent settings with built-in templates for GDPR, CCPA, and more. It also lets you block custom scripts and iframes before consent, helping your site stay compliant across regions.
• Easy Digital Downloads Pro now includes built-in EU VAT handling, making compliance much easier for digital product sellers in the EU and UK. The update adds automatic tax rates, real-time VAT number validation at checkout, and integrated reporting tools.
• Tickets are still available for WordCamp US 2025 (August 26–29 in Portland, Oregon). Don’t miss out on this opportunity to learn, network, and connect with WordPress professionals from around the world.
• Wholesale Suite now supports automatic invoicing and payment charging, which streamlines the checkout process for wholesale customers using Net 30/60/90 terms. It’s a big time-saver for managing recurring B2B payments.
• WooCommerce 10.0 was released on July 14 with major upgrades. These include WCAG 2.2 AA accessibility compliance, shareable checkout links, improved cart performance, and an experimental new Add to Cart block powered by the Interactivity API.
• WordPress 6.9 is on the proposed roadmap for release in December 2025. It will continue the focus on collaboration tools and design improvements introduced in earlier 6.x versions. Stay tuned for feature previews in the coming months.
• Formidable Forms now lets you embed dynamic graphs in emails and PDF reports—no JavaScript required. This new feature automatically converts interactive charts into images so that you can share visual data summaries easily.

New Plugins & Tools

• Envira Gallery CDN – A new service that automatically delivers your WordPress images through a Content Delivery Network (CDN). This makes your photo galleries load faster for visitors around the world.
• WPConsent (🔥trending) – The fastest growing WordPress cookie popup and compliance plugin. It allows you to easily manage cookie consent and privacy compliance on your WordPress website.
• User Comment Delete – Allows logged-in users to delete their own comments using a link next to their comment.

That’s a wrap for this month’s WPBeginner Spotlight! We hope you enjoyed catching up on the latest news and updates from the WordPress ecosystem.

Got a product launch, feature update, or cool project you think we should cover? Send us a message, and we might feature it in our next edition.

We’ll see you again next month with another round of WordPress news. Thanks for reading and being part of the WPBeginner family.

If you liked this article, then please subscribe to our YouTube Channel for WordPress video tutorials. You can also find us on Twitter and Facebook.

The post WPBeginner Spotlight 14: From Entry Automation to AI Building Blocks – The Future of WordPress is Here first appeared on WPBeginner.

Here’s something every CEO knows but won’t say out loud:

When the AI screws up, somebody human is going to pay for it.

And it’s never going to be the algorithm.

The board meeting reality

Picture this scene. You’re in a boardroom. The quarterly numbers are a disaster. The AI-powered marketing campaign targeted the wrong audience. The automated pricing strategy killed margins. The chatbot gave customers incorrect information that triggered a PR nightmare.

The board turns to the executive team and asks one question:

“Who’s responsible?”

Nobody — and I mean nobody — is going to accept “the AI made a mistake” as an answer.

They want a name. A person. Someone accountable.

This is the reality of AI deployment that nobody talks about in the hype articles and vendor demos.

Why human accountability becomes more critical, not less

Most people think AI reduces the need for human responsibility.

The opposite is true.

When AI can execute decisions at unprecedented speed and scale, the quality of human judgment becomes paramount. A bad decision that might have impacted dozens of customers can now impact thousands in minutes.

The multiplier effect of AI doesn’t just amplify results, it amplifies mistakes.

The new job description

In an AI-driven world, the most valuable skill isn’t prompt engineering or machine learning.

It’s defining clear objectives and owning the outcomes.

Every AI system needs a human owner. Not just someone who can operate it, but someone who:

• Defines what success looks like.
• Sets the guardrails and constraints.
• Monitors for unexpected outcomes.
• Takes responsibility when things go sideways.

This isn’t a technical role. It’s a leadership role.

The forensic future

When AI systems fail — and they will — the investigation won’t focus on the algorithm.

It’ll focus on the human who defined the objective.

“Why did the AI approve that high-risk loan?” “Because Sarah set the criteria and authorized the decision framework.”

“Why did the system recommend the wrong product to premium customers?” “Because Mike’s targeting parameters didn’t account for customer lifetime value.”

This isn’t about blame. It’s about clarity. And it’s exactly what executives need to feel confident deploying AI at enterprise scale.

The three levels of AI accountability

1. Level 1. Operational Accountability: Who monitors the system day-to-day? Who spots when something’s going wrong? Who pulls the plug when needed?
2. Level 2. Strategic Accountability: Who defined the objectives? Who set the success metrics? Who decided what tradeoffs were acceptable?
3. Level 3. Executive Accountability: Who authorized the AI deployment? Who’s ultimately responsible for the business impact? Who faces the board when things go wrong?

Every AI initiative needs clear owners at all three levels.

Why this actually accelerates AI adoption

You might think this responsibility framework slows down AI deployment.

It does the opposite.

Executives are willing to move fast when they know exactly who owns what. Clear accountability removes the “what if something goes wrong?” paralysis that kills AI projects.

When leaders know there’s a human owner for every AI decision, they’re comfortable scaling quickly.

The skills that matter now

Want to be indispensable in an AI world? Master these:

1. Objective Definition: learn to translate business goals into specific, measurable outcomes. “Improve customer satisfaction” isn’t an objective. “Reduce support ticket response time to under 2 hours while maintaining 95% resolution rate” is.
2. Risk Assessment: understand the failure modes. What happens when the AI makes a mistake? How quickly can you detect it? What’s the blast radius?
3. Forensic Thinking: when something goes wrong, trace it back to the human decision that created the conditions for failure. Build that feedback loop into your process.
4. Clear Communication: if you can’t explain your objectives clearly to a human, you can’t explain them to an AI either.

The uncomfortable questions

Before deploying any AI system, ask:

• Who owns this outcome?
• What happens when it fails?
• How will we know it’s failing?
• Who has the authority to shut it down?
• What’s the escalation path when things go wrong?

If you can’t answer these questions, you’re not ready to deploy.

The leadership opportunity

This shift creates a massive opportunity for the leaders who get it.

While everyone else is chasing the latest AI tools, the smart money is on developing the human systems that make AI deployable at scale.

The companies that figure out AI accountability first will move fastest. They’ll deploy more aggressively because they’ll have confidence in their ability to manage the risks.

(This pairs perfectly with the abundance potential I discussed in my recent piece on how AI amplifies human capability rather than replacing it. The organizations that master both the opportunity and the responsibility will dominate their markets.)

The bottom line

AI doesn’t eliminate the need for human accountability.

It makes it more critical than ever.

The future belongs to leaders who can clearly define what success looks like and own the results — good or bad.

The algorithm executes. Humans are accountable.

Make sure you’re ready for that responsibility.

References:

1. Anthony Franco, “AI First Principles“
2. Robb Wilson, “The Age of Invisible Machines“

The article originally appeared on LinkedIn.

Featured image courtesy: Anthony Franco.

The post The AI Accountability Gap appeared first on UX Magazine.

Welcome back to Invisible Machines. I’m Josh Tyson, a contributing editor here at UX Magazine, and I am joined by resident visionary, Robb Wilson, CEO and Co-founder of OneReach.ai. 

• Robb and I co-authored the bestselling book Age of Invisible Machines, and this podcast is where we continue our explorations of agentic AI.
• Today we’re excited to welcome Karen Hao, renowned tech journalist and author of the instant New York Times bestseller Empire of AI.
• In her book, Karen distills more than a decade’s worth of in-depth reporting into a detailed and highly readable account of OpenAI’s rise to power and why leadership at the company abandoned the promise to keep their research open.
• We also talk about why their target of reaching AGI, first is being undercut by a clear definition of what artificial general intelligence even is.
• This is another conversation where anthropomorphization comes into play, and why making these tools behave more like humans might actually make them less effective (and more dangerous).
• Robb and I were also intrigued by Karen’s reporting on a small nonprofit in New Zealand that used AI to preserve the Māori language. Their scaled back approach to establishing a clear goal and curating data in a responsible manner shows how more focused approaches to integrating AI into business operations might win out over the blunt force of large language models.

Now, get ready for a fascinating discussion with a real one, Karen Hao.

The post The Dark Side of Chasing AGI appeared first on UX Magazine.

Designers today are quick to praise how AI speeds up their workflows. And that makes sense — businesses now more than ever need fast drafts, rapid testing, and quick launches to keep users engaged.

Yet, many designers still miss the mark, not fully leveraging their expertise when working with AI in products. What’s the result? Lots of hyped AI-powered products are creating noise instead of value, resulting in experiences that feel shallow.

After 10 years in design, I’ve learned to take innovations with a grain of salt – and turn them from momentary trends into practical approaches. That’s why I want to share how AI really changes the daily work of designers, how it shifts interfaces, and what parts of the design process never change.

Throughout this article, I’ll share examples, practical advice, and insights from my experience, helping you understand where AI fits and where human skill is still key.

If you want a clear, honest take on AI’s real impact on design and business, keep reading.

Why AI became a core part of designers’ daily workflow

To better grasp how AI can enhance design at every stage, it helps to first outline how design work traditionally unfolds — before AI became part of the process.

Broadly, product designers have typically worked in two main ways:

Both approaches have been facing the same challenge: businesses are constantly tightening budgets and speeding up timelines. This has pushed many teams into making trade-offs. Designers, often spread thin, end up skipping deeper discovery work. At best, usability testing happens just before release — rushed and insufficient.

And then came artificial intelligence.

From my experience, AI can support designers across three key phases of the product iteration cycle:

• Input and product analysis.
• Research and exploration.
• Implementation and testing.

Let’s take a closer look at them.

1. Analysis

Plenty of tools now offer AI-generated summaries of dashboards, feedback, and user behaviour. They’re handy, especially when you’re scanning for trends. However, they are not always truly right.

It can highlight what’s visible, but not always what’s important. Sometimes the insights that actually drive results are buried deeper, and you won’t find them unless you look for yourself, because:

• AI generates dry, surface-level summaries based on available data.
• It doesn’t always distinguish between signal and noise, or highlight what affects outcomes.
• Some insights that impact the result can be entirely different from what AI flags.

Tip: Treat AI summaries as a starting point. If something catches your eye, dig deeper. Go back to the raw data, validate the insight, and confirm whether it’s grounded in actual user behaviour or just looks interesting on paper.

2. Research

Research is one of the most time-consuming (and often underappreciated) parts of product design. And it can often eat up hours. Thus, AI can assist you to:

• Pull key takeaways from customer interviews, docs, or Notion pages.
• Analyse mentions of a specific topic across multiple URLs or sources.
• Scan hundreds of App Store reviews without reading them one by one.
• Generate a quick list of competitors and extract what features they offer, how they’re positioning themselves, or what users praise/complain about.

However, don’t expect it to do all the job:) AI is more like an additional researcher in the team who needs to be guided, given clear direction, and double-checked.

Tip: Try to be more T-shaped specialists and learn how to write some scripts and prompts. Understanding how AI thinks will help you guide it better and speed up your workflow.

For example, instead of asking your analytics team to rebuild a dashboard, you can download a page with reviews ( as HTML, for example). Then have AI parse it, turn it into a table, and sort by sentiment or keywords. You’ll uncover patterns in minutes without waiting and saving your teammates time.

3. Implementation

In this board stage, you can speed up the creation of first drafts. At every step (from the landing page to the screen flows), designers have to generate a lot of material, which, let’s be honest, not everyone can keep up with. For example, during our interviews, only a third of 600 candidates knew the basic processes of this stage.

That’s why, with some AI guidance, you can stay afloat and:

• Generate early concepts and illustrations.
• Stress-test layout clarity or colour palettes.
• Explore UX patterns or flow variations without redrawing everything from scratch.

Tip: If you want to make your drafting collaboration more effective, feed it with 10+ reference visuals that reflect your brand style. Mind that AI is only as good as the data you give it. It doesn’t have an intuitive eye.

Take Figma’s AI launch as an example. It could create UI screens in seconds, which was great for quick drafts. But after a couple of weeks, they disabled the feature. The artificial assistant was trained on only a few companies’ design systems, so many screens ended up looking very similar.

Next practical tip: try to be clear and detailed in describing your visuals. Ideally, start by writing a clear prompt that describes the style and illustration details, and include some reference images. Then, ask the AI to generate JSON that explains the details of the prompt — this way, you can see how well it understood you.

If the result isn’t quite right, tweak the output or adjust it. For example, if you’re aiming for a thin line that resembles a bone, the AI might miss that subtlety, which is why some manual fine-tuning is necessary. Once you’ve got closer to your vision, you can use that refined JSON as a reference for further iterations.

4. Testing

During pre-AI testing, designers had to constantly ask developers to create something and release it, then wait for feedback just to launch it properly.

However, today, with the right processes in place and a good design system with code-ready components, it’s not that hard for a designer to build the front-end for a user flow on their own. Just enough to see how it works in practice. Sometimes, it doesn’t even need developers to add logic behind it — just a working prototype that feels close to real.

You can test in Figma with clickable flows, or go one step further and share a live, browser-based version where users actually input data. It’s more real, insightful, and users feel more comfortable using it.

Tip: Use AI tools to speed up your workflow and reduce dependency on other teams. Start simple: don’t wait for analysts to build a separate dashboard — generate the code and make the API request yourself. If you need to update a UI element, do it directly in Cursor and hand it off to developers for review. In many cases, this will be significantly faster.

AI won’t replace the craft or the collaboration between design and development. But it will remove friction. And in a world where business goals shift constantly, that saved time gives you more space for experimentation and better products.

How AI can help to make hard calls

AI can’t (and shouldn’t) make product decisions for you. Yet, it can help you make them faster and with more confidence by showing you a clearer picture of processes.

For instance, at TitanApps, we always analyse user feedback to decide on implementing a new feature. However, users don’t always ask for “the next big thing” within the product. So, most of their comments reflect current features. Luckily, being part of the Attlassian community gives us access to forums where people share pain points, recommend tools, and ask for help.

Before AI, we manually crawled forums, trying different keyword combinations, tracking synonyms, reviewing long threads, and collecting patterns. Sometimes it took an entire week just to build a case for or against a product direction.

Now it takes a couple of hours. Here is how the process looked for us:

• We prepared a structured JSON file that included forum thread links, topic clusters, and relevant metadata.
• AI scanned around 20 main links, each containing multiple subtopics, extracted key insights, and compiled the findings in about three hours.
• At the same time, we ran a parallel process using scraped HTML reviews from competitors that took 90 minutes. We wanted to see: Are users asking similar things? How are other products responding? Are they solving it better, or leaving gaps?

Surely, during both analyses, we verified the information and sources that were used.

While those two streams were running, we spent time mapping where our original idea wasn’t catching interest. And in doing so, our team noticed something more valuable. There was demand building around a related topic, one that competitors hadn’t addressed properly.

So, instead of spending a full week bouncing between forums and threads, we got a full directional snapshot in a single day.

How AI changes design interfaces

With AI becoming more integrated into products, it’s not just designers’ daily workflows that are changing — the interfaces themselves are evolving too. To understand the impact of AI, it helps to break it down into two categories:

• AI is a visible tool that users actively interact with.
• AI is an invisible layer that improves the user experience in the background.

In both cases, the final screen is no longer the most important outcome. What matters more is the designer’s ability to see the bigger picture and to understand the user’s journey. Here’s why that shift is important:

• If AI shows up as an assistant or a chatbot, you need to understand what users actually expect from it — what kinds of requests they’ll make, what problems they’re trying to solve. Only then can you think about how to present that information: in plain text, a GPT-style chat, or a dashboard.

You might start by giving users full freedom to type in anything and get a response. But to build a smarter, smoother experience and train your model more effectively, you need to identify the patterns. As some people may look for sprint summaries, others – backlog overviews or even pull request analysis.

Then, the next question pops up: What do the users do with the information once they extract it: use in the meetings, export, etc. This influences where and how you present the AI assistant, what kind of prompts or templates you provide, and how much of the process you can automate without needing users to ask manually.

Tip: Train your bird’s-eye view perspective. Even though this shift in design priorities is visible to many, from my own experience, candidates often rush to visualise the problem. They focus on individual screens, but don’t analyse the whole user interaction and journey.

If AI is operating silently behind the scenes, this perspective becomes even more essential. As a designer, you need to:

• Understand your audience deeply.
• Track feedback and analytics.
• Notice where AI can enhance the experience and where it might get in the way.

Take tools like Copilot for developers. One major complaint early on was that it didn’t adapt to each person’s style. It generated generic or awkward code that didn’t fit the context. Instead of helping, it disrupted the flow.

Or look at tools like Cursor. It became popular on Twitter, and people started experimenting with it for pet projects. Yet, many couldn’t even figure out how to get it working properly. So, not every AI tool is for everyone, and not every moment is the right one to introduce it.

To design well for this kind of AI, you need to know:

• When it’s helpful.
• What it should suggest.
• How users will actually operate it.

Tip: Remember that AI is a tool, not a silver bullet. These background assistants still have a kind of interface, even if it’s invisible. And designers now have to learn to design for that too.

Design principles that AI can’t change

Even though AI pushes designers to adapt — to think more like developers, balance business goals, and maintain a user-centric and unique approach — some principles remain unchanged, like Jakob’s Law.

Users become familiar with patterns, and they don’t want to relearn what already works. That’s why it’s crucial not to reinvent the wheel without a reason. If there are established best practices, use them. AI won’t decide this for you — it’s your role to understand what’s proven, when it’s worth innovating, and when it’s smarter to stick with what users already know.

So yes, being a designer today is more complex than ever. But if we improve our bird’s-eye view, stay T-shaped, and resist the urge to overcomplicate, we can use these tools — including AI — to do better work, not just faster work.

Ultimately, our goal is to design things that make sense.

Featured image courtesy: Oleh Osadchyi.

The post The Real Impact of AI on Designers’ Day-To-Day and Interfaces: What Still Matters appeared first on UX Magazine.