peltier.io

Spot cooling for hot paths. A profile-guided optimization agent that only ships wins it can prove.

hotpath finds the 10–90% left on the floor between "the compiler" and "hire a perf consultant," with two properties no consultant offers: verified equivalence (a change provably preserves behavior or is discarded) and self-verifying ROI (the value claim is a stopwatch on trusted infrastructure, not a survey).

Full design: SPEC.md.

Layout

crates/            Trust layer (agent has NO write access — SPEC §10)
  bench-runner/    Interleaved A/B timing, bootstrap CIs, A/A calibration
  diff-test/       Equivalence gates, corpus hash-pinning, per-target policy
  ledger/          Append-only SQLite attempt ledger (enforced by triggers)
  report/          ROI math: speedup CI → cores → dollars, caveats included
agent/             Untrusted proposer (Claude Agent SDK, Python)
playbook/          Optimization classes 1–7, tried strictly cheapest-first
config/            accept.toml (thresholds), pricing.toml (ROI inputs)
targets/           Per-target checkouts — the only agent-writable path
corpora/           Hash-pinned golden-replay inputs (read-only to agent)
results/           Calibration evidence, per-engagement outputs

Quick start

cargo test --workspace          # trust-layer unit tests
just aa                         # A/A self-test: must yield a null verdict
just compare "cmd-a" "cmd-b"    # interleaved A/B with bootstrap CI

Status

Phase 0–1 scaffold (see SPEC §5 for the phase plan and exit criteria).

Done:

• Workspace with the four trust-layer crates; core statistics (interleaved scheduling, bootstrap ratio CIs, CI-lower-bound accept rule), append-only ledger schema with mutation-refusing triggers, corpus hash-pin verifier, equivalence-policy parser, ROI formulas — all unit-tested.
• bench-runner CLI: whole-program compare and aa modes with env fingerprinting.
• Playbook classes 1–7; agent tool contract and prompting spine.

Next (Phase 1 exit criteria):

• perf stat counters + max RSS + RAPL capture per run.
• Automated A/A calibration sessions and regression-injection self-test recorded to results/calibration/ (<5% FP, ≥95% detection).
• diff-test orchestration end-to-end on two real targets; harness IPC for the agent tool surface.

License

GPL-3.0-or-later — see LICENSE.