Notes
Short pieces about the methodology and architecture decisions behind the AI systems I ship — specs, evals, multi-agent orchestration, LLM integration, and the discipline of directing coding agents.
June 3, 2026
Prompt engineering is dead. I never did it.
The industry spent two years hunting for magic words to whisper at the model. Now it's quietly declaring 'prompt engineering' dead and replacing it with context engineering and harness engineering. Here's the thing: those aren't new tricks — they're just engineering, the work real systems people were doing the whole time. Why the words were never the point, and what actually makes an agent work.
- agents
- methodology
- ai-native
June 3, 2026
The model was never your moat
A model you can run on a laptop now scores within a few percent of the best closed frontier model. That sounds like earth-shaking news, and for anyone building products the correct reaction is a shrug — because the model was never the thing defending you. Here's why the frontier going free changes almost nothing about how to build, and what actually compounds into an advantage.
- ai-native
- business
- agents
June 2, 2026
Building got cheap. Ideas didn't.
Coding agents removed the constraint that defined software for decades — the ability to build. When building gets cheap, the competition moves up the stack to the thing that was always the real bottleneck: taste, market judgment, and the nerve to ship. A field note on what actually wins now.
- agents
- ai-native
- business
June 2, 2026
Knowing how is cheap. Knowing what is everything.
A plain-language map of the engineering ladder, built on one idea: juniors know neither what to build nor how; middles know how but not what; seniors know what — the thing that actually solves the business problem. Why that ladder exists, how the rungs connect, and why AI is quietly sawing off the bottom of it first.
- careers
- ai-native
- business
May 15, 2026
Directing coding agents, not writing code
A short note on what changes when the implementation layer is an agent — what stays the same, what disappears, and where the new bottleneck lives.
- agents
- methodology
- ai-native