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AI JUN 20, 2026

Leverage Record: June 20, 2026

Eighteen tasks. June 20, 2026 weighted to 36.9x leverage across 481.0 human-equivalent hours in 782 Claude-minutes. Supervisory leverage closed at 390.0x.

Eighteen tasks. June 20, 2026 weighted to 36.9x leverage across 481.0 human-equivalent hours in 782 Claude-minutes. Supervisory leverage closed at 390.0x.

12.0 weeks of human-equivalent throughput in 13.0 hours of Claude wall-clock. The 90.0x ceiling came from Build an infrastructure-provisioning tool missing content: +117 conformance packs (12->129), +68 discoverers (56->124), +42 advisor checks (59->101) incl service_limits, +DomainPer...; the 5.7x floor sat at Full content audit + a third-party model pluggable LLM provider migration + content remediation (amplify/scenarios/distractors/recall) on updated provider.

About These Records
These time records capture personal project work done with Claude Code (Anthropic) only. They do not include work done with ChatGPT (OpenAI), Gemini (Google), Grok (xAI), or other models, all of which I use extensively. Client work is also excluded, despite being primarily Claude Code. The actual total AI-assisted output for any given day is substantially higher than what appears here.

Task Log

#TaskHuman Est.ClaudeSup.FactorSup. Factor
1Build an infrastructure-provisioning tool missing content: +117 conformance packs (12->129), +68 discoverers (56->124), +42 advisor checks (59->101) incl service_limits, +DomainPermissionsPolicy resource; 15-agent workflow, all tested60.0h40m2m90.0x1800.0x
2Backfill an infrastructure-provisioning tool backend coverage 53%->95% (28-agent workflow + straggler round, ~1950 new tests, every module >=80%)100.0h75m3m80.0x2000.0x
3Metrics-tracker v2 build: scaffold a desktop client + a launchd sync daemon + v2 cost/capture backend spine (pricing/ingest/classify/quality/schema/migration/ingest API/CLI); 254 backend + 32 frontend tests; committed 3 repos100.0h78m4m76.9x1500.0x
4Metrics-tracker v2 completion: MCP v2 tools + a knowledge base parser + subscription amortization + yield git-correlation + Recharts viz + desktop client daemon-control-panel/tray + live-DB integration tests35.0h32m2m65.6x1050.0x
5Metrics-tracker v2 phase 2: cost/model/activity/yield analytics + optimizer + widget endpoints + v2 client wiring + Drafts/Cost frontend screens in both shells40.0h42m3m57.1x800.0x
6Infrastructure-provisioning tool structural items: drift detection, Step Functions org-scan fan-out, live deployment.progress push, deployment cancel/list/get + stack.update + resource.refresh + fleet import recipes, DomainPermissionsPolicy resource, frontend button wiring + WebSocket-client tests35.0h40m3m52.5x700.0x
7Metrics-tracker v2 cost+capture: review prior implementation, update 4 docs (requirements/design/README/CLAUDE) + write phased implementation plan10.0h14m4m42.9x150.0x
8Metrics-tracker desktop plan: design a desktop client (shared UI package parity) + a launchd sync daemon; study desktop client and prior precedents; write plan + requirements FRs9.0h13m5m41.5x108.0x
9Metrics-tracker v2 final phases: runnable SQLite functional flow tests + sanctioned OIDC callback plumbing + macOS signing/notarization config + CodeBuild CI buildspec12.0h18m1m40.0x720.0x
10Run full platform content audit: 27-phase audit scripts + spec validation + canonical validation across 973 specs/289 packages/2196 labs; wrote timestamped report4.0h6m2m40.0x120.0x
11Leverage reconciliation + backfill for a personal website: synced one month of metrics-tracker records bidirectionally (CSV<->cloud, 13 deltas resolved, 0 dups), then generated 17 sanitized daily leverage blog posts via a deterministic template + 6-agent sanitization fan-out (173 tasks), bumped about-page count, built+deployed staging and production16.0h40m3m24.0x320.0x
12Researched the CloudFront WebSockets-over-VPC-origins launch + AWS docs and wrote a ~3700-word architecture deep-dive article: 3 rendered Mermaid diagrams, generated on-brand hero image, matched house style, dual-published source, bumped about-page counts, built+verified on staging10.0h28m2m21.4x300.0x
13Fix 9 correctness bugs + 15 regression tests in an infrastructure-provisioning tool (IAM Policy stub, Cognito client update, Events Rule stale targets, CUR pagination, advisor ClientError, governance enforcement+cost-allocation, ip-space SG fields)7.0h25m1m16.8x420.0x
14Built pluggable multi-provider LLM layer (a third-party model + Anthropic, sync+batch) for platform synthesis; wired amplify scripts; validated third-party model; submitted 1412-request fleet pair-amplification batch across 59 packages8.0h40m4m12.0x120.0x
15Metrics-tracker WS1: extract shared UI package with injectable client transport seam; rewire web shell; fix React-dedup + tests; tsc+32 tests+build green7.0h38m6m11.1x70.0x
16NLI validation of third-party-model-amplified pairs (DeBERTa-v3 NLI): verified working, built validate+prune+regenerate pipeline, ran loop to convergence (weak rate 10.5%->1.9% across 14,384 pairs/59 pkgs)8.0h45m6m10.7x80.0x
17Novel background analysis and continuity review; 11 files read; full plot/dependency/risk/dates report4.0h38m8m6.3x30.0x
18Full content audit + a third-party model pluggable LLM provider migration + content remediation (amplify/scenarios/distractors/recall) on updated provider16.0h170m15m5.7x64.0x

Aggregate Statistics

MetricValue
Total tasks18
Total human-equivalent hours481.0
Total Claude minutes782
Total supervisory minutes74
Total tokens9,395,000
Weighted average leverage factor36.9x
Weighted average supervisory leverage factor390.0x
Human-equivalent weeks12.0

Analysis

The day's leverage distribution matters more than the headline figure. The 90.0x ceiling came from Build an infrastructure-provisioning tool missing content: +117 conformance packs (12->129), +68 discoverers (56->124), +42 advisor checks (59->101) incl servic...; the 5.7x floor was Full content audit + a third-party model pluggable LLM provider migration + content remediation (amplify/scenarios/distractors/recall) on updated provider. 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 (390.0x 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 18 tasks, the day produced roughly 12.0 weeks of senior-engineer-equivalent throughput in 13.0 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.