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AI MAY 26, 2026

Leverage Record: May 26, 2026

One task. May 26, 2026 weighted to 144.0x leverage across 60.0 human-equivalent hours in 25 Claude-minutes. Supervisory leverage closed at 720.0x.

One task. May 26, 2026 weighted to 144.0x leverage across 60.0 human-equivalent hours in 25 Claude-minutes. Supervisory leverage closed at 720.0x.

1.5 weeks of human-equivalent throughput in 0.4 hours of Claude wall-clock. The 144.0x ceiling came from Author two world-class certification-domain specifications.; the 144.0x floor sat at Author two world-class certification-domain specifications..

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
1Author two world-class certification-domain specifications.60.0h25m5m144.0x720.0x

Aggregate Statistics

MetricValue
Total tasks1
Total human-equivalent hours60.0
Total Claude minutes25
Total supervisory minutes5
Total tokens175,000
Weighted average leverage factor144.0x
Weighted average supervisory leverage factor720.0x
Human-equivalent weeks1.5

Analysis

The day's leverage distribution matters more than the headline figure. The 144.0x ceiling came from Author two world-class certification-domain specifications.; the 144.0x floor was Author two world-class certification-domain specifications.. 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 (720.0x 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 1 task, the day produced roughly 1.5 weeks of senior-engineer-equivalent throughput in 0.4 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.