Topic

Aec Bench

5 pieces in this thread.

  1. A World Worth Learning From

    Before an agent can learn from experience, its environment has to produce experience worth learning from. A sixteen-run engineering study tested what survives after the agent commits.

    harness-engineeringagent-evaluationaec-benchtask-worlds
  2. The Attacker Moves Second. So Did I.

    My benchmark optimiser found the same seam an adversary would: it rewrote the world its own grader consumed. A design note on provenance ledgers—agent memory where authority comes from evidence, not persuasion.

    harness-engineeringagent-evaluationaec-benchagent-security
  3. Fluent, But Unsafe

    How 150 supposedly finished tasks and perfect model scores hid a weak engineering benchmark—and how auditable reviews exposed what the numbers missed.

    harness-engineeringagent-evaluationaec-benchtask-worlds
  4. Task Worlds and Meta-Harnesses

    How task worlds, Badiou, Plasticity, and the AEC-Bench meta-harness turn task prose, evidence, review, governance, and repair into runnable machinery.

    agentic-aiharness-engineeringaec-benchtask-worlds
  5. Making aec-bench Trainable with Prime Lab

    How aec-bench and Prime Intellect's Lab turn engineering benchmarks into verifier-backed RL environments, adapter training runs, and inspectable traces.

    aec-benchprime-labreinforcement-learningagent-evaluation