CTO Field Notes
Concise, practical lessons from building and scaling engineering teams: the trade-offs, failures, and repeatable practices behind delivery, architecture, technical leadership, and AI-assisted software development.
Written for founders, CTOs, engineering leaders, and senior engineers responsible for turning product bets into reliable software.
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Code Review Is Risk Management
Code review should not treat every pull request equally. Review depth should follow the cost of being wrong, and the reviewer still owns that decision.
Read field noteHow AI Is Changing Engineering Team Structure
Teams are getting smaller and more senior while the pipeline that produces seniors is being cut. What is actually established, what is forecast, what would prove me wrong - plus an AI-era hiring rubric and the …
Read field noteEngineering Metrics in the Age of AI
Your board will ask whether AI made engineering more productive. Most available numbers answer a different question. A taxonomy separating diagnostic signals from performance measures, a paired scorecard, and …
Read field noteEvals Are the New Tests
In April 2025 OpenAI shipped a model update whose offline evals and A/B tests all looked good. It was sycophantic enough to roll back within days. A practical guide to building the measurement layer that would …
Read field noteCode Was Never the Bottleneck
Your engineers are producing more code and your delivery cadence has barely moved. The waiting did not disappear - it moved downstream to review and absorption, and that is where the constraint always was. …
Read field noteStaying One Step Ahead
The CTO’s job is not to see the future. It is to reduce surprise by building systems that detect weak signals early, convert ambiguity into decisions, and act before friction compounds.
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