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When an agent output strays, you retain the original objective while supplying the exact observed mismatch. Rather than giving vague rejections, you feed back command output, screenshots, and concrete artifacts that make the next iteration clear.

When a path fails in deployment, you reverse the failing approach immediately and ask for a safer replacement backed by newly observed evidence.

You consistently start by defining what a behavior should become before authorizing code changes. You give agents broad room to run on routine slices, but lock down explicit checkpoints around credentials, deployments, and public documentation.

This keeps execution aligned with the core goal while protecting production stability at key decision boundaries.

Your agent runs currently keep research, building, and review inside a single long conversation. Over time, extensive implementation history ends up consuming the primary context window.

Handing off independent research or review tasks to dedicated subagent threads keeps your primary thread lean and preserves context for complex implementation slices.