Eleven tasks. May 6, 2026 weighted to 12.0x leverage across 189.5 human-equivalent hours in 951 Claude-minutes. Lab simulator dominated the day's volume. Supervisory leverage closed at 258.4x.
The day's ceiling was 160.0x (16h human in 6 Claude-minutes) on the an internal service: generate 11 application-domain hero images via an image model.1 Pro, wire into application.jinja hero + applications.jinja card grid, W. The floor was 0.8x on the marketing site courses page: cap provider card course list at 20 items + N more arrow row across all 4 card variants (live+heroed, live+plain, soon+heroed, . Median Claude-minutes per task: 45; median human-equivalent hours per task: 16.
Task Log
| # | Task | Human Est. | Claude | Sup. | Factor | Sup. Factor |
|---|---|---|---|---|---|---|
| 1 | the an internal service: generate 11 application-domain hero images via an image model.1 Pro, wire into application.jinja hero + applications.jinja card grid, WebP optimization (13MB→1.2MB) | 16.0h | 6m | 3m | 160.0x | 320.0x |
| 2 | Open-items batch 2: mass terminal-wait-output pattern fix (2158 patterns / 454 labs broken by escape mismatch — 13 labs recovered to full-score), 124 unsupported terminal-runs stripped, content cleanup, 3 audit residuals retired (one demoted to AUDIT_STRICT-only), TS/TSX/JSX support via Sucrase in node resolver, Phase-1 SIEM Workbench (search bar + alerts + investigations), Phase-1 SQL Workbench (sqlite-wasm + result grid + saved scripts), Phase-1 Project Board (Kanban + Gantt with critical-path + RAID with risk scoring), Phase-1 Notebook (Pyodide cell runner with kernel state persistence). 8 commits pushed. | 80.0h | 95m | 1m | 50.5x | 4800.0x |
| 3 | Three more Phase-1 simulators: Network Topology Sandbox (BFS reachability + static routes + ping with simulated latency, 8 tests), Device Manager Panel (default A+ fleet + Settings + BIOS, 7 tests), Policy/Architecture Editor (5 document templates with required-section validation + diagram node/edge graph, 6 tests). All 3 wired into App routes; 21 new SDK resource types registered. Inventory now 15 of 16 Phase-1 shipping (only Vendor Console - Salesforce/SAP/Oracle - remains). | 24.0h | 30m | 1m | 48.0x | 1440.0x |
| 4 | Custom the product AI sound effect library: 28 a TTS service-generated sounds (incl. Apple-style branded startup), SoundProvider+useSound hook, volume/preview settings UI, design-system event dispatches (Button/Modal/Drawer/Toast), integration into Exam + QuestionBank flows, online/offline cues | 16.0h | 30m | 3m | 32.0x | 320.0x |
| 5 | Designed Phase E launch sprint orchestrator (75 specs across ISC2/ISACA/PMI/ScrumAlliance/Cisco/CompTIA-backfill), auto-chained from Phase D, ramped parallelism 2→3→4-way as labs session freed memory. Diagnosed Meta phase D failures as cross-spec prereq referential integrity violations, wrote fixmetacrossspecprereqs.py to strip dangling prereqs and seed 6 specs to DigitalMarketingAssociate. Wrote Phase F (Meta recovery) orchestrator and chained it after Phase E. Updated the platform/CLAUDE.md and content corpus/CLAUDE.md with permanent Trivia/Renkara exclusion + 51-suggestion free-tier expansion plan to clear 200 | 12.0h | 45m | 12m | 16.0x | 60.0x |
| 6 | Open-items burn-down: VFS reset across labs (memory leak fix), QuickJS node resolver (CDN-loaded, ~3MB lazy), shell stdout redirection (echo > file), Monaco editor listener leak fix, multi-editor-create-file DOM driver hardening, actionassertiongap audit revert + content reverts (8 labs back to full-score), 7 conceptual itil4/togaf labs flagged shipping:false, 255 control-flow terminal-run uiSteps cleanup across 30 labs, 3 gql multi-create labs flagged shipping:false. 4 commits pushed. | 16.0h | 90m | 1m | 10.7x | 960.0x |
| 7 | the platform Decoy memory fix: opt-in fake-embedder + thread caps cuts worker RSS ~10x (168 GB calibration sweep blow-up reduced to ~15 GB). Tests for fake-embedder contract + SentenceTransformer-not-imported guard. | 4.0h | 30m | 3m | 8.0x | 80.0x |
| 8 | the platform engine a flagship cert exam cold-start 500 fixes: UnboundLocalError on avgperq (lifted assignment to function scope) + null examstructure coercion (.get default does not fire on explicit null). AST-based regression tests in testaudit_regressions.py. | 2.0h | 25m | 2m | 4.8x | 60.0x |
| 9 | the platform predictor calibration: harness RNG decouple (separate observation/exam streams), [PREDICT/COLD] log, calibration-only answerkey endpoint, n-aware verdict bands, multi-select-bug-unmask. Five sweep iterations Phase A-E (45 to 225 journeys) producing definitive predictor calibration verdict at acc92 (wellcalibrated, Brier=0.003), acc65 (calibrated within sampling noise), and uncovering ~12pp acc80 underconfidence as remaining model signal. | 16.0h | 360m | 12m | 2.7x | 80.0x |
| 10 | the marketing site courses page: 5 provider reorders + CNCF hero generation (an image model) + template refactor to honor slug order over live-first split, deployed across 2 prod + 2 staging build cycles | 2.5h | 165m | 4m | 0.9x | 37.5x |
| 11 | the marketing site courses page: cap provider card course list at 20 items + N more arrow row across all 4 card variants (live+heroed, live+plain, soon+heroed, soon+plain), deployed to Production + Staging with CloudFront invalidation | 1.0h | 75m | 2m | 0.8x | 30.0x |
Aggregate Statistics
| Metric | Value |
|---|---|
| Total tasks | 11 |
| Total human-equivalent hours | 189.5 |
| Total Claude minutes | 951 |
| Total supervisory minutes | 44 |
| Total tokens | 3,453,000 |
| Weighted average leverage factor | 12.0x |
| Weighted average supervisory leverage factor | 258.4x |
Analysis
The day's leverage distribution is the part that matters more than the headline figure. 4 tasks cleared the 30x threshold; 4 tasks ran below 5x. The 30x+ tier is what produces the impression that AI changes the time-cost curve; the sub-5x tier is what reminds anyone watching that some work is still gated by human review and cannot speed up arbitrarily.
Top-of-distribution tasks tend to share a shape: tightly-scoped, well-specified, with no integration ambiguity. On May 6, 2026 the 160.0x ceiling came from the an internal service: generate 11 application-domain hero images via an image model.1 Pro, wire into applic. The work fit cleanly into 6 Claude-minutes because the inputs and the success criterion were both explicit; the AI was not required to discover anything new. That shape is repeatable; tasks like it post 30x to 60x consistently across the recent log.
Bottom-of-distribution work runs differently. The 0.8x floor on the marketing site courses page: cap provider card course list at 20 items + N more arrow row across all 4 car reflects a near-1:1 ratio that reflects bounded review-heavy work where the human watches each step. The supervisory ratio (258x weighted today) tracks differently: it captures how much human prompt-writing time the day's output consumed, and it stays high even on lower-leverage days because supervisory minutes scale roughly with task count, not with human-equivalent hours.