AI coding tools often feel like magic. But behind the scenes, even the best agents rely on three simple steps:
- Look — reads your codebase and error logs
- Think — plans the best change
- Do — edits code and runs tests to verify
If a test fails, it adjusts and tries again. If it passes, it moves forward. This iterative loop is why agents succeed in complex codebases where a single prompt fails.
Next time an agent solves a tough problem, notice the loop:
- What context did it analyze?
- How did it decide?
- How did it verify the fix?
It isn't magic - just a thoughtful, tight loop executed with patience.