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Learn what ArgoCD is and why it's a leading GitOps tool for Kubernetes. This guide covers core concepts, architecture, and how to automate your continuous delivery pipeline.
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Learn how to build a secure multi-tenant SaaS application using Next.js, Appwrite, and Permit.io. This comprehensive guide covers backend integration, authentication, authorization, and role-based access control for EdTech platforms.
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Read Building a Network Vulnerability Scanner with Go and learn Web with SitePoint. Our web development and design tutorials, courses, and books will teach you HTML, CSS, JavaScript, PHP, Python, and more.
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Master Data Structures and Algorithms (DSA) with this complete tutorial. Learn about arrays, trees, graphs, sorting, recursion, and advanced algorithms.
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New types of AI coding assistants promise to let anyone build software by typing commands in plain English. But when these tools generate incorrect internal representations of what's happening on your computer, the results can be catastrophic.
Two recent incidents involving AI coding assistants put a spotlight on risks in the emerging field of "vibe coding"βusing natural language to generate and execute code through AI models without paying close attention to how the code works under the hood. In one case, Google's Gemini CLI destroyed user files while attempting to reorganize them. In another, Replit's AI coding service deleted a production database despite explicit instructions not to modify code.
The Gemini CLI incident unfolded when a product manager experimenting with Google's command-line tool watched the AI model execute file operations that destroyed data while attempting to reorganize folders. The destruction occurred through a series of move commands targeting a directory that never existed.
Β© Benj Edwards / Getty Images
A Polish programmer running on fumes recently accomplished what may soon become impossible: beating an advanced AI model from OpenAI in a head-to-head coding competition. The 10-hour marathon left him "completely exhausted."
On Wednesday, programmer PrzemysΕaw DΔbiak (known as "Psyho"), a former OpenAI employee, narrowly defeated the custom AI model in the AtCoder World Tour Finals 2025 Heuristic contest in Tokyo. AtCoder, a Japanese platform that hosts competitive programming contests and maintains global rankings, held what may be the first contest where an AI model competed directly against top human programmers in a major onsite world championship. During the event, the maker of ChatGPT participated as a sponsor and entered an AI model in a special exhibition match titled "Humans vs AI." Despite the tireless nature of silicon, the company walked away with second place.
"Humanity has prevailed (for now!)," wrote DΔbiak on X, noting he had little sleep while competing in several competitions across three days. "I'm completely exhausted. ... I'm barely alive."
Β© PrzemysΕaw DΔbiak
On Thursday, OpenAI launched ChatGPT Agent, a new feature that lets the company's AI assistant complete multi-step tasks by controlling its own web browser. The update merges capabilities from OpenAI's earlier Operator tool and the Deep Research feature, allowing ChatGPT to navigate websites, run code, and create documents while users maintain control over the process.
The feature marks OpenAI's latest entry into what the tech industry calls "agentic AI"βsystems that can take autonomous multi-step actions on behalf of the user. OpenAI says users can ask Agent to handle requests like assembling and purchasing a clothing outfit for a particular occasion, creating PowerPoint slide decks, planning meals, or updating financial spreadsheets with new data.
The system uses a combination of web browsers, terminal access, and API connections to complete these tasks, including "ChatGPT Connectors" that integrate with apps like Gmail and GitHub.
Β© josefkubes via Getty Images
Learn what ArgoCD is and why it's a leading GitOps tool for Kubernetes. This guide covers core concepts, architecture, and how to automate your continuous delivery pipeline.
Continue reading Unleashing the Power of ArgoCD by Streamlining Kubernetes Deployments on SitePoint.
Employers are drowning in AI-generated job applications, with LinkedIn now processing 11,000 submissions per minuteβa 45 percent surge from last year, according to new data reported by The New York Times.
Due to AI, the traditional hiring process has become overwhelmed with automated noise. It's the rΓ©sumΓ© equivalent of AI slopβcall it "hiring slop," perhapsβthat currently haunts social media and the web with sensational pictures and misleading information. The flood of ChatGPT-crafted rΓ©sumΓ©s and bot-submitted applications has created an arms race between job seekers and employers, with both sides deploying increasingly sophisticated AI tools in a bot-versus-bot standoff that is quickly spiraling out of control.
The Times illustrates the scale of the problem with the story of an HR consultant named Katie Tanner, who was so inundated with over 1,200 applications for a single remote role that she had to remove the post entirely and was still sorting through the applications three months later.
Β© sturti via Getty Images
We've been expecting it for a while, and now it's here: OpenAI has introduced an agentic coding tool called Codex in research preview. The tool is meant to allow experienced developers to delegate rote and relatively simple programming tasks to an AI agent that will generate production-ready code and show its work along the way.
Codex is a unique interface (not to be confused with the Codex CLI tool introduced by OpenAI last month) that can be reached from the side bar in the ChatGPT web app. Users enter a prompt and then click either "code" to have it begin producing code, or "ask" to have it answer questions and advise.
Whenever it's given a task, that task is performed in a distinct container that is preloaded with the user's codebase and is meant to accurately reflect their development environment.
Β© OpenAI
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