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The remaining ~500 co-authored commits represent human-directed, AI-assisted work.
Work Pattern
Daily velocity
Average: 47 commits / day across 30 days
Peak day: 124 commits (Mar 10)
Weekly ramp
Week
Commits
W08 (Feb 19-23)
39
W09
288
W10
480
W11
416
W12 (partial)
179
Hours (ET)
Block
Commits
Morning (07-12)
424
Afternoon (12-18)
528
Evening (18-00)
314
Night (00-06)
136
Active every day of the week, including weekends (Mon: 266, Sat: 215, Sun: 251).
Effort Estimate
Human time
30 consecutive days, working across all hours including nights and weekends.
Hourly distribution suggests ~12-16 hour days on heavy days.
Estimated 300-400 hours of human time (~10-13 hrs / day average).
Equivalent to 2-2.5 months of full-time work at 40 hrs / week.
What it would cost without AI
A project of this scope — 25 Rust crates, an API server, React frontend, CLI, multi-provider LLM client, sandbox abstraction, workflow engine, and integrations with GitHub, Slack, Linear, and MCP — built from scratch in 30 days is extraordinary.
Scenario
Estimate
Solo senior engineer (no AI)
12-18 months
Small team (3-4 engineers, no AI)
4-6 months
Equivalent contractor cost (no AI)
$400k-$750k at $200-250 / hr
Equivalent team cost (no AI)
$300k-$500k (salaries + overhead, 4-6 months)
AI costs
~1,300 AI-assisted commits generating and reviewing substantial code.
Estimated $2,000-$8,000 in API costs over 30 days, depending on context sizes and model tier.
Total actual cost
Component
Low estimate
High estimate
Human time (300-400 hrs @ $200-250 / hr)
$60,000
$100,000
AI API costs
$2,000
$8,000
Total
$62,000
$108,000
Compared to the $400k-$750k it would cost without AI, the actual cost of $62k-$108k represents an 80-85% reduction — achieving the same output at roughly one-fifth to one-sixth the price.
Takeaway
This is a 5-10x productivity multiplier story. One developer, working intensely for 30 days with heavy AI assistance, produced what would traditionally require a small team working for several months. The 188,000-line codebase spanning Rust, TypeScript, and infrastructure is not trivial — it includes a workflow engine, LLM abstraction layer, multiple sandbox implementations, and a full API + web frontend.