Verify the description, not the effect
How does a closed-loop coding agent verify a side effect it can't cheaply or totally observe? By checking the effect's description against a fixed contract, not the effect itself.
How does a closed-loop coding agent verify a side effect it can't cheaply or totally observe? By checking the effect's description against a fixed contract, not the effect itself.
From the creator of Hack, the language behind Facebook’s business logic, comes a closed-loop coding agent that turns one prompt into running software.
Closed-loop control requires a feedback signal trustworthy enough to act on. Most AI coding agents close their loops on lossy sensors, tests, unsound types, model judgment, and inherit the instability that follows. Skipper is built on sound signals with SKJS, deterministic execution, and reactive computation.
A follow-up to "Treat Agent Output Like Compiler Output" — addressing the responses, why determinism isn't the point, and what static analysis actually buys you.
We spent decades making languages readable. Agents don't care. Why we'll resist this shift — and why we'll embrace it anyway.
Why our discomfort with AI-generated code reveals exactly what we haven't built yet, and what the compiler analogy teaches us about trusting coding agents.