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Build with AI Agents

Turning misses into systemic improvements

The Improvement Loop

Every agent miss is a learning opportunity. The goal isn't to prevent all failures—it's to build systems that learn from them.

Agents don't fail because they're lazy. They fail because they can't see. Sometimes the information isn't present. Sometimes there's no feedback loop. Sometimes we gave them too much freedom.

So the job isn't to write the perfect prompt. The job is to design an environment where the easiest path is the correct one.

The Loop

When something goes wrong, the response pattern is:

  1. Capture the miss — What did the agent do? What did reality say?
  2. Diagnose — What didn't it see? Missing data, constraint, feedback, or boundaries?
  3. Choose a primitive — Observability, instructions, tooling, guardrails, or verification?
  4. Encode as artifact — Version-controlled, repeatable, not just memory.
  5. Promote to gate — When it's worth enforcing, make it a gate.

Explore the Framework

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