The agent does the work. You make the calls.
One scripted agent run, three judgment gates, and a consequences replay for every call you make. Most people rush at least one gate — see which one is yours.
One agent run. Three gates. Your calls.
You're an engineer at a SaaS company. The ticket reads: “Delete user accounts inactive for 24+ months to cut database costs.” You decide to hand it to an AI agent. Three gates stand between you and Friday evening.
What are the three gates?
Delegate (before the agent runs: frame the outcome, bound the blast radius, predict the result), Accept (verify output before adopting it — polish is not proof), and Deploy (the deed itself: premortem, reversibility, and a human name on the decision).
Is this based on a real methodology?
The gates are the framework of Miatz Tuukul, the structured-thinking strand of Miatz AI-Fluency. Cognitive-forcing checkpoints at decision moments are a well-studied alternative to debiasing lectures, which research shows largely don't transfer.
Why does the simulator use a mundane scenario?
Because that's where agent incidents actually happen — routine tickets with real blast radius, not sci-fi. The deletion-script scenario compresses the most common failure modes: vague delegation, verification theater, and unowned deploys.
The other half of judgment is calibration — measure yours in five minutes
Run the gates on your real work
Miatz Tuukul installs these three gates in your actual tools — with a daily check-in, drills on your own backlog, and a calibration curve computed from real outcomes.