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Build with AI Agents

Tightening the Loop

When to turn advice into gates

Not every improvement should become a gate. Gates add friction. The question is whether the friction is worth the protection.

The goal is to find the sweet spot: enough enforcement to prevent repeated mistakes, not so much that it slows down legitimate work.

The Rubric

Use this rubric to evaluate whether an improvement should tighten from guidance to enforcement.

Should this become a gate?

Check the criteria that apply to this improvement.

Keep as improvement task

Address it, but enforcement overhead may not be worth it yet.

0/10

Types of Gates

Advisory gates

Warn but don't block. Good for new rules where you're still calibrating the threshold. The agent sees the warning, humans see it in logs, but work continues.

Blocking gates

Fail the build, commit, or deploy. Use for high-confidence rules with clear remediation. The failure message should tell you exactly what to fix.

Human-in-the-loop gates

Require explicit approval to proceed. Good for high-stakes changes where automation can flag but shouldn't decide. Examples: schema migrations, permission changes, dependency updates.

Implementation Patterns

Pre-commit hooks

Fastest feedback loop. Run linters, formatters, and quick checks before the commit is created. Keep these fast (<5s) or developers will bypass them.

CI checks

More thorough validation. Run tests, build verification, and slower checks. Can block merge but not local commits.

Deploy gates

Final validation before production. Health checks, smoke tests, and approval workflows. Most important for high-stakes environments.

The Loop

  1. 1

    Miss

    Capture what went wrong

  2. 2

    Diagnosis

    What didn't it see?

  3. 3

    Primitive

    Which lever to pull

  4. 4

    Artifact

    Encode the fix

  5. 5

    Gate

    Enforce when ready