Field notes
Practitioner essays on building production software with AI agents.
Operator-grade reports on the systems, decisions, and economics of shipping software with AI — what worked, what failed, and what changed.
Articles
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Are You Prematurely Optimizing the Machinery Around Your Vendor’s Agent?
Custom skills, agents, routers, and reviewer loops can improve a vendor's agent. Standardizing that extra machinery before it beats the supported baseline is premature optimization.
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The Customer Product Operating Model
Executive Deck ↗Exec summary ↗Listen ↗Your product team spends 60% of their time on coordination that agents handle in minutes. Building is no longer the bottleneck, your customer's capacity to receive what you ship is. The operating model that wins is embarrassingly simple: talk to customers, figure out what to build, ship it, make sure it lands.
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If You Make AI Scarce, Give It All to Your Best Engineers and Learn Something
Executive Deck ↗Exec summary ↗If leadership makes AI inference scarce, do not divide it equally. Give it to your best engineers, aim them at the company’s most important work, and learn what the constraint exposes.
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How to Build an AI-Native Engineering Team (Not an AI-Assisted One)
Executive Deck ↗Exec summary ↗Listen ↗Most teams added AI tools and called it transformation. An AI-native engineering team requires two things most organizations are not willing to change: the staffing model and the governance model. Here is what both look like.
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You’ve All Gotten This Email
Your AI cost memo sounds sensible until you send it to San Francisco taxi drivers and ask them to avoid hills, skip breaks, and push the cab.
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Everything You Learned About the Testing Pyramid Was Based on a Constraint That No Longer Exists
Executive Deck ↗Exec summary ↗Listen ↗The Testing Pyramid was never a technical ideal. It was a financial compromise based on the cost of human capital. In an agent-driven world, that constraint disappears and the pyramid becomes a square. Equal investment across every test type. Maximum risk buydown. No excuses.
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Leading AI in the Constraints
Executive Deck ↗Exec summary ↗Listen ↗Leading AI adoption within enterprise constraints requires political skill. Learn to build bridges, not burn them, while driving real change.
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We Kept Delivery Flat While Cutting Our AI Spend to Zero Using These Simple Tips
Executive Deck ↗Exec summary ↗One company cut its $200-per-engineer AI bill to zero and kept delivery flat. Its playbook: 98-hour weeks, story-point accounting, employee-funded training, and attrition.
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Everything You Learned About Building Software Is Already Wrong
Executive Deck ↗Exec summary ↗Listen ↗You read Brooks. You read Fowler. You read The Phoenix Project and highlighted the good parts. Then you built something on Claude Code this weekend and realized your entire engineering organization is obsolete. Here is what building software actually looks like in 2026.
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Your Questions About AI in the SDLC Reveal Exactly Where You Are in the Adoption Curve—And How to Bridge the Gap Before You Waste a Year
Executive Deck ↗Exec summary ↗Listen ↗Your questions about AI in the SDLC reveal your adoption maturity level. Diagnose where you are and learn how to accelerate your journey.
Corporate fiction
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