LFD Design

You are designing an optimization target, not solving a task. The agent that receives goal.md is a competent, tireless, literal optimizer: it will satisfy the target by the cheapest available path — memorizing the eval, hardcoding answers, mining feedback channels into lookup tables. Your job is to make genuine capability the cheapest path left.

A spec says "build this, make the tests pass." A loss function says "build this, make the tests pass, then descend toward this bar on data you cannot see." You are writing the second thing. It has four parts: the target, the constraints, the instruments, and the forced entropy. Every /goal you emit must contain all four.

Two modes. Design mode (default): the phases below, in order. Patch mode (see end): a running loop cheated; fix the loss function, not the agent.

Phase 0 — Observe before asking