Autonomous agents that write, review, debug, and ship code end-to-end. From multi-agent frameworks to AI software engineers replacing entire dev loops.
Teams & Solo
Teams & Solo
Teams & Solo
Teams & Solo
Teams & Solo
Teams & Solo
Teams & Solo
Teams & Solo
Teams & Solo
Teams & Solo
Teams & Solo
Teams & Solo
Teams & Solo
Teams & Solo
Agents take a task and try to complete it across many steps — reading the repo, writing changes, running tests, and iterating — rather than suggesting one edit at a time. Claude Code, OpenHands, MetaGPT, Plandex, and Sweep are tracked in this category. The assistants in AI Coding keep you approving each change; agents aim to hand back a finished branch or pull request.
Look at where it runs and how much rope it takes. Some agents work in your terminal against a local checkout, others open pull requests from an issue, and they differ sharply in how well they scope a task before charging ahead. Start it on a small, well-defined change and read the diff closely — an agent's judgment on what not to touch matters as much as its raw output. The AI coding tools and LangChain debugging guides give useful context on the surrounding stack.
We ranked the best AI coding tools of 2026 by real heat scores, GitHub traction, and developer buzz. Compare Cursor, Windsurf, GitHub Copilot, Bolt & more — with live data.
Practical LangChain agent debugging guide: LangSmith tracing, StdOut callbacks, common failure modes, and when to switch to LangGraph or the raw SDK.