AI coding agents work better when your repo has explicit readiness: declared setup, tasks, checks, workflows, and safe agent boundaries.
AI coding agents are getting better, but a lot of repos still make them start from guesswork.
They land in a codebase and have to infer:
which command installs dependencies
which command starts the app
which services need to be running
Why most AI agents disappoint in production (and what to fix first)
You gave your AI agent real tools. Here's the 4-part control layer it's missing + the Judge Layer implementation guide
Meta paper reveals improved coding agents through summary reuse
I’ve been thinking a lot about a failure mode in AI-assisted development that does not fit neatly...
AI coding agents are showing up in CI/CD pipelines more often. They can review code, run tests,...
You know that slightly cursed feeling when an AI coding agent says "done", but you still have no idea...
Anthropic's Stainless acquisition and recent Claude Code updates show where AI coding is headed: safer tool access, scoped…
Current AI coding systems are becoming extremely capable at: repository understanding prompt...
A beginner-friendly guide to building an automated security pipeline with GitHub Actions —...
