Autonomous multi-step coding and debugging
AI agents use Claude Sonnet 5 to plan work, use developer tools such as browsers and terminals, sustain coding across messy codebases, and debug complex technical issues with less manual prompting.
Why the human is still essential here
Engineers still define goals, review architecture tradeoffs, verify correctness, and decide whether proposed changes should ship.
How people use this
Repo-aware feature implementation
An AI coding agent scans a large repository, plans the required edits across files, implements a feature, and runs local checks before handing the branch back to the engineer.
Claude Code / CursorTerminal-driven build and test debugging
AI works in the terminal to inspect logs, rerun failing commands, patch the code, and iterate until the build or test suite passes.
Claude Code / OpenAI Codex CLIMulti-file legacy refactor
AI updates old modules, imports, and interfaces across a messy codebase while preserving behavior and reducing the manual effort needed for broad refactors.
Cursor / GitHub CopilotNeed Help Implementing AI in Your Organization?
I help companies navigate AI adoption -- from strategy to production. Whether you are building your first LLM-powered feature or scaling an agentic system, I can help you get it right.
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