Three tasks. May 21, 2026 weighted to 36.3x leverage across 69.0 human-equivalent hours in 114 Claude-minutes. Supervisory leverage closed at 318.5x.
1.7 weeks of human-equivalent throughput in 1.9 hours of Claude wall-clock. The 55.4x ceiling came from Math Content Rollout Phases 0-4: v2 pipeline verification, AP Precalc spec fixes (61->69 leaves, CED practices, broken topicsandobjectives), math content schemas (workedexample/...; the 8.6x floor sat at an API gateway native-mode wiring (bcrypt pin, settings hardening, certs->certifications fix, native entitlement path, commit-on-exit deps, eventtype kwarg drift, secure-cookie to....
Task Log
| # | Task | Human Est. | Claude | Sup. | Factor | Sup. Factor |
|---|---|---|---|---|---|---|
| 1 | Math Content Rollout Phases 0-4: v2 pipeline verification, AP Precalc spec fixes (61->69 leaves, CED practices, broken topicsandobjectives), math content schemas (workedexample/misconception/representationpack pydantic + 3 LLM generators), 2 hand-curated static files (52 formulas + 17 function families),... | 60.0h | 65m | 6m | 55.4x | 600.0x |
| 2 | AP Precalc spec audit + math content rollout plan (spec issue identification, activity catalog inventory, 8-phase plan covering spec fixes, math-specific content shapes, 5 new Tier A activities, v2 atom synthesis, full math family rollout) | 4.0h | 14m | 3m | 17.1x | 80.0x |
| 3 | an API gateway native-mode wiring (bcrypt pin, settings hardening, certs->certifications fix, native entitlement path, commit-on-exit deps, eventtype kwarg drift, secure-cookie toggle) + seedtestuser.py + PlaywrightDriver.primeauthsession + JourneyOrchestrator.seedauthenticatedsession | 5.0h | 35m | 4m | 8.6x | 75.0x |
Aggregate Statistics
| Metric | Value |
|---|---|
| Total tasks | 3 |
| Total human-equivalent hours | 69.0 |
| Total Claude minutes | 114 |
| Total supervisory minutes | 13 |
| Total tokens | 360,500 |
| Weighted average leverage factor | 36.3x |
| Weighted average supervisory leverage factor | 318.5x |
| Human-equivalent weeks | 1.7 |
Analysis
The day's leverage distribution matters more than the headline figure. The 55.4x ceiling came from Math Content Rollout Phases 0-4: v2 pipeline verification, AP Precalc spec fixes (61->69 leaves, CED practices, broken topicsandobjectives), math content sche...; the 8.6x floor was an API gateway native-mode wiring (bcrypt pin, settings hardening, certs->certifications fix, native entitlement path, commit-on-exit deps, event_type kwarg dri.... Tasks at the top of the distribution share a shape: tightly-scoped specifications, clear success criteria, and minimal integration ambiguity. The AI doesn't need to discover anything new; it executes against an explicit target.
Tasks at the bottom run differently. They're either bounded by review-heavy work where every step gets verified, or they involve ambiguity that demands several rounds of trial and adjustment. The factor is real and informative, not a failure mode.
The supervisory leverage figure (318.5x today) tracks something orthogonal to wall-clock leverage. It's the ratio of human-equivalent output to human prompt-writing time. It stays high even on lower-leverage days because supervisory minutes scale with task count, not with the human-hour estimate; a 20-minute task and a 4-hour task can both be specified in two minutes of human prompt-writing.
Across the 3 tasks, the day produced roughly 1.7 weeks of senior-engineer-equivalent throughput in 1.9 hours of model wall-clock. That ratio is the practical answer to the question of how much output a single operator can move per day when the model handles the execution and the operator handles the direction.