Stop drip-feeding scenarios: extend the harness to cover the latencies that
actually dominate perceived speed, and measure them on a REAL production build.
- --prod: build a production renderer with the probe included (VITE_PERF_PROBE=1,
off in normal builds) and launch it from dist/. Measures minified React, so
numbers are representative shipped figures instead of ~3x-inflated dev ones.
- cold-start scenario (tier "cold"): launch → CDP → driver → first paint, via a
fresh isolated spawn per run. Captures spawn_to_cdp_ms, spawn_to_driver_ms, fcp_ms.
- first-token scenario (backend tier): Enter → first assistant token painted —
the TTFT latency an agent app is uniquely judged on.
- run.mjs gained --prod (build once), cold-start fresh-spawn loop, and gates
ci+cold tiers against the baseline.
Baseline re-captured on a PRODUCTION build (median of 5), darwin-arm64 — all
green. Representative numbers:
cold-start spawn→interactive ~1.6s, FCP ~0.5s
stream frame p95 22ms, 1 longtask
keystroke p50 2ms, p95 8.7ms
transcript mount 145ms, 82ms longtask (400-msg open)
The prod build also settled the open question from the dev numbers: the
transcript-mount "lead" (221ms longtask in dev) is only ~72-82ms in prod — not
actionable. Measurement did its job.
