There are few areas where AI has seen more robust deployment than the field of software development. From "vibe" coding to GitHub Copilot to startups building quick-and-dirty applications with support from LLMs, AI is already deeply integrated.

However, those claiming we're mere months away from AI agents replacing most programmers should adjust their expectations because models aren't good enough at the debugging part, and debugging occupies most of a developer's time. That's the suggestion of Microsoft Research, which built a new tool called debug-gym to test and improve how AI models can debug software.

Debug-gym (available on GitHub and detailed in a blog post) is an environment that allows AI models to try and debug any existing code repository with access to debugging tools that aren't historically part of the process for these models. Microsoft found that without this approach, models are quite notably bad at debugging tasks. With the approach, they're better but still a far cry from what an experienced human developer can do.

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OpenAI today announced a significant expansion of ChatGPT's customization and memory capabilities. For some users, it will now be able to remember information from the full breadth of their prior conversations with it and adjust its responses based on that information.

This means ChatGPT will learn more about the user over time to personalize its responses, above and beyond just a handful of key facts.

Some time ago, OpenAI added a feature called "Memory" that allowed a limited number of pieces of information to be retained and used for future responses. Users often had to specifically ask ChatGPT to remember something to trigger this, though it occasionally tried to guess at what it should remember, too. (When something was added to its memory, there was a message saying that its memory had been updated.)

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