LLMs still produce bugs, but those bugs are different than what they used to be.
- Source
- Boris Cherny
- Date
LLMs still produce bugs, but those bugs are different than what they used to be. It’s less off-by-ones and more about system design, ui usability, missing broader context. Some kinds of coding has been solved, but not all. While models continue to improve, adversarial code review has been an incredibly powerful tool to catch many of these kinds of bugs. It can be as simple as a one line prompt - “use a dynamic workflow to adversarial test every edge case in an iOS simulator”, or use Claude’s built in /code-review (or /code-review low, /code-review medium, etc.)
- LLM — A large language model — the neural network behind tools like Claude and ChatGPT, trained on huge amounts of text to predict what comes next.
- context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
- AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
It names the failure class that survives better models, which is design and rather than syntax. The adversarial review pattern is cheap to adopt and directly changes how you gate -written code.
- postAnthropic's Boris Cherny Signals Claude Chat and Cowork Are Merging
postI am pleased to see that OpenAI’s new model is roughly on par with Gemini Flash…- postClaude Tag moves to Fable 5.1 inside Slack for Team and Enterprise plans
postAnthropic previews Function Hooks, an unshipped Claude Code extension point
Checking sign-in…
Loading comments…