26 tasks. April 5, 2026 closed at 51.7x weighted leverage across 401.0 human-equivalent hours in 465 minutes of wall-clock time. Supervisory leverage came in at 216.8x.
That is 10.0 weeks of human-equivalent throughput in 7.8 hours. The ceiling was 200.0x; the floor was 15.0x. 21 of the 26 entries came from a single project.
Task Log
| # | Task | Human Est. | Claude | Sup. | Factor |
|---|---|---|---|---|---|
| 1 | Generate 180 lab definition JSON files for 12 free-tier AI/ML/Data Engineering domains with Python script | 40.0h | 12m | 5m | 200.0x |
| 2 | Build P0 unit test suite for avian-app-web: setup.ts, predict.test.ts, persistence.test.ts, engine.test.ts, auth-legacy.test.ts — 151 tests | 12.0h | 8m | 5m | 90.0x |
| 3 | Coding | 40.0h | 30m | 5m | 80.0x |
| 4 | Testing strategies + 263 P0 unit tests across avian-app-web (151) and avian-app-electron (112) | 40.0h | 30m | 5m | 80.0x |
| 5 | Client repos audit (7 repos: lint/types/security/parity/sourcemaps) | 4.0h | 3m | 2m | 80.0x |
| 6 | P1 unit tests: 233 tests across avian-app-web (111) and avian-app-electron (122) — UI components, IPC handlers, auth, profiles | 32.0h | 25m | 2m | 76.8x |
| 7 | Build P1 test suite for avian-app-web: 10 test files (6 UI component, 3 API, 1 integration), 111 new tests, all 262 passing | 16.0h | 15m | 5m | 64.0x |
| 8 | P2 tests: 262 tests across avian-app-web (138) and avian-app-electron (124) — screens, hooks, integration, persistence roundtrip | 32.0h | 30m | 1m | 64.0x |
| 9 | Build P0 unit tests for avian-app-electron: engine-client (61 tests), store (30 tests), predict (20 tests) | 8.0h | 8m | 5m | 60.0x |
| 10 | Build P1 test suite for avian-app-electron: 6 test files, 122 tests covering IPC handlers, auth-client, secure-storage, Library screen, daily-rings, useAuth hook | 12.0h | 12m | 5m | 60.0x |
| 11 | Full deployment readiness audit — 47 repos 200+ checks 5004 tests + auto-fix all findings | 20.0h | 22m | 5m | 54.5x |
| 12 | Build P2 test suite for avian-app-web: 11 test files, 138 tests (UI components, hooks, integration) | 16.0h | 18m | 5m | 53.3x |
| 13 | avian-admin command center: 6 new backend endpoints (engine session stats/heatmap + purchase revenue/subs/alerts) + wire all dashboard cards to live data | 16.0h | 20m | 2m | 48.0x |
| 14 | Build AVIAN infrastructure MCP server with 10 tools (health checks, DNS, CloudFront, CodePipeline, EC2, RDS, ALB, SSM, ECR) | 6.0h | 8m | 5m | 45.0x |
| 15 | AccelaStudy infrastructure: assess 3 legacy projects, prepare infinite-web for deployment (fix build, add buildspec, assign port), create full Terraform module for accelastudy-cloud2 (dedicated EC2, ECR, ALB,… | 40.0h | 55m | 10m | 43.6x |
| 16 | Build 10 P2 test files for avian-app-electron (124 new tests): Dashboard, ExamInfoLanding, QuestionBankSession, Settings, Onboarding, Welcome, WelcomeLetterModal, ChatPanel, study-plan, session-lifecycle… | 10.0h | 14m | 5m | 42.9x |
| 17 | Debugging | 8.0h | 12m | 3m | 40.0x |
| 18 | Infrastructure | 3.0h | 5m | 3m | 36.0x |
| 19 | Fix admin engine URL + build AVIAN infra MCP server (10 diagnostic tools) | 8.0h | 15m | 3m | 32.0x |
| 20 | Documentation | 2.0h | 5m | 3m | 24.0x |
| 21 | Testing | 4.0h | 12m | 3m | 20.0x |
| 22 | Lambda@Edge API proxy for engine auth across web/Electron/iOS + Terraform infra + architecture docs | 24.0h | 75m | 10m | 19.2x |
| 23 | Documentation | 1.5h | 5m | 3m | 18.0x |
| 24 | Infrastructure | 1.5h | 6m | 5m | 15.0x |
| 25 | Testing | 3.0h | 12m | 3m | 15.0x |
| 26 | Audit and review | 2.0h | 8m | 3m | 15.0x |
Aggregate Statistics
| Metric | Value |
|---|---|
| Total tasks | 26 |
| Total human-equivalent hours | 401.0 |
| Total Claude minutes | 465 |
| Total supervisory minutes | 111 |
| Total tokens | 3,575,500 |
| Weighted average leverage factor | 51.7x |
| Weighted average supervisory leverage factor | 216.8x |
| Human-equivalent weeks | 10.0 |
Analysis
The highest factor of the day came in at 200.0x and the lowest at 15.0x, a spread of 13.3 times between the two. That is a wide range for a single day, and it usually means the day mixed mechanical work with work that needed real judgement.
The largest single entry accounted for 40.0 of the 401.0 human-equivalent hours, or 10 percent of the day. No single task dominated the total, so the weighted average is representative.
Supervisory time was 111 minutes against 465 minutes of execution, a ratio of about 1 to 4. Supervisory leverage of 216.8x is the figure I find most honest, because it measures the hours I actually spent rather than the hours a machine spent on my behalf.
Every figure here is recorded at the time the work is done rather than reconstructed afterwards. The human estimate is my own judgement and carries the uncertainty that implies; the minutes and tokens are measured. The full dataset, including this day, is available for download.