Essays on engineering delivery
Long-form pieces on the systems behind predictable shipping — metrics, bottlenecks, WIP, and the operator practices that move them.
AI coding agents: give them the periphery, keep humans on the core
AI coding agents are brilliant at some work and dangerous at other work. A fractional CTO's rule for what to delegate — give them the periphery, keep humans on the core — with the enterprise access problem and where agents actually earn their place.
AI made starting work nearly free. Finishing is still expensive.
Why AI-assisted teams start more work than ever and ship about the same: waiting queues, context limits, and Little's Law applied to agents. A fractional CTO's case for one-thread-one-task and WIP limits in the AI era.
Vibecoded MVP stopped shipping? Manage your AI like a junior
A vibecoded MVP stalls the way junior-built codebases always have: code ships fast and nothing catches mistakes. A fractional CTO's playbook for managing AI coding agents with junior-developer practices — with a real rescue case and numbers.
Average lead time is lying to you — how to forecast delivery with percentiles
Average lead time hides what your delivery system actually does. A fractional CTO's guide to median, spread, and p95 forecasting — how to commit to delivery dates you can hit instead of estimates that keep slipping.
How to diagnose where engineering delivery is actually broken
A fractional CTO's metrics playbook: decomposing T2M into Lead Time and Cycle Time, the role of WIP, Little's Law, and how to introduce WIP limits without team revolt.