Skip to content
Legible AI

Build the test that decides whether verification belongs in the loop.

The programme does not need a larger collection of monitor scores. It needs measurements that change a concrete choice: use this checker, choose another evidence mode, or abstain.

  1. Build the reference-composition ladder firstFirst experiment. Measure the same verifier across ordered levels of answer access, from a supplied answer through partial references to full recomputation.
    Deliverable: A curve showing which reference forms buy reliable checking and where extra inference cannot compensate for missing access.
  2. Publish a model-pair scorecardEvaluation. Estimate verifier competence and generator-verifier error overlap on one paired task set, with false alarms and catches reported separately.
    Deliverable: A decision record for choosing a checker by observed fit rather than parameter count or brand tier.
  3. Turn monitor inversion into a release testSafety control. Keep a small bank of grounded sentinel tasks spanning the known difficulty boundary and compute signed discrimination on every monitor release.
    Deliverable: A release gate that fails when a monitor becomes evidence against correct work, even if its other health metrics improve.
  4. Route by evidence modeSystem design. Choose among sampling, model verification, executable tests, retrieval, human review, and abstention according to available reference access and consequence.
    Deliverable: A local router that names why a check was selected and refuses when no available mode clears its threshold.
  5. Make every result reproducible without provider accessResearch infrastructure. Freeze prompts, raw responses where publication is permitted, graders, seeds, manifests, and a standard-library reproduction script for every public result.
    Deliverable: Small evidence bundles a reviewer can rerun without an API key, a private harness, or the author present.
  6. Give self-reports an explicit claim ceilingInterface contract. Separate observed behavior, system-generated explanation, inferred mechanism, and unresolved cause in logs and user-facing reports.
    Deliverable: A result format that keeps a useful explanation from being mistaken for independent evidence about the system that wrote it.

The ordering rule

Measure access before optimizing inference. Measure model-pair behavior before choosing a verifier. Establish a grounded failure signal before automating a release gate. Build the router only after those thresholds exist.

Read the questions behind the sequence