The risky part of AI-assisted engineering is not a single wrong answer.
It’s a loop.
Generate a draft. Apply it. Run into an error. Paste the error back. Generate a fix. Apply it. Repeat.
That loop feels productive because something is always happening.
But loops compound mistakes. A small misunderstanding in step one can turn into a large, confident mess by step five, especially when the tool is optimizing for momentum instead of truth.
If you want speed and correctness, you need stop conditions and guardrails.
Guardrails that keep loops honest
- Time-box the loop: “Two retries, then reassess the approach.”
- Force diffs, not dumps: “Propose a minimal patch, not a full rewrite.”
- Pin the intent: “Restate the goal and constraints before changing code.”
- Add a verification step: “What tests or checks prove this fix is correct?”
- Escalate when the error repeats: “If the same symptom appears twice, stop and diagnose.”
The goal is not to slow the tool down.
It’s to keep the tool from dragging you forward in the wrong direction.