Selected thinking
Essays, experiments, architecture notes, and research about systems that have to work in the real world.
2026-09-20
What Building Real Software With AI Actually Taught Me
Ten things a year of shipping AI-written production code actually taught me, minus the hype.
2026-09-12
The Budgeting Mistake That's Quietly Wrecking Your Software Team
Companies price developer hires against a market salary band. What they should be pricing is expected impact within a fixed window — and the difference is where hiring budgets bleed out.
2026-09-10
Why Navier-Stokes Actually Matters
OpenAI says an AI system proved a fluid equation can break down in finite time. Here's the actual Navier-Stokes problem, precisely.
2026-08-25
AI Agents That Actually Work: How to Combine Judgment, Code, and Control
A practical case for combining probabilistic models with deterministic workflows and human judgment.
2026-08-26
The Conflict That Moves a Team Forward: How to Disagree Without Breaking It
Why productive disagreement can reduce rework, improve decisions, and protect team trust without romanticizing conflict.
2026-08-19
Why Building Software Is Hard: The Cost of Ambiguity
Software fails in the gaps between goals, communication, system states, and real-world behavior. A founder-focused lesson from a real-time hardware integration.
2026-08-19
Most AI Agents Should Not Be Agents
A practical boundary between useful probabilistic systems and workflows that need certainty.
2026-08-19
Fast Shipping Is an Engineering Constraint, Not an Excuse
Shipping quickly is a technical requirement—but speed still needs judgment about irreversible risk.
2026-08-19
Optimize the Work Before Optimizing the Code
The highest-leverage performance optimization is often deleting work the system never needed to do.
2026-08-19
Your Startup Probably Does Not Need Microservices
Microservices are a trade: exchange local complexity for distributed complexity only when the benefits are real.