I’m John Young.
I run engineering at Combine Capital and Infrared, and write research-backed essays on running AI coding agents in production — every claim traced to a primary source.
github.com/johnayoung linkedin.com/in/jyoung1985 john.anto.young@gmail.com rss
Ledger
Essays29
Pillars6
Evidence base verified2026-10-19
Recent Essays
- Self-Improving AI Software Factory: Govern the Harness Loop Agent Runtime A self-improving AI software factory edits its own harness. Ask for gains on tasks the optimizer never saw, and keep the evaluator and promotion outside its reach.
- Loop Engineering Examples: Harden One Loop, Control by Control Agent Runtime Most published agent loops ship without a cap, a ledger, or a gate. Harden one loop.sh control by control, each line tied to a documented default or incident.
- Comprehension Debt Is an On-Call Problem for Agent Code Team & Process Comprehension debt comes due when someone gets paged. Decide before merge who owns agent-written code, what they must understand, and how you prove it later.
- Claude Code Memory Usage: How Many Sessions Fit on One Machine Production Operations Claude Code memory usage, measured: three sessions ran 32 processes and MCP servers outweighed Claude in two. A RAM budget for running sessions in parallel.
- Agent Tool Design Belongs in Your Harness Audit, Not Prompt Tips Agent Runtime Agents that sent the same write twice reported success 90% of the time. The fix was one tool parameter. Audit what a tool call means, not just whether it runs.