Writing / Architecture and systems
Notes from
production.
Practical notes on architecture, production reliability, AI-assisted engineering, and making complex systems easier to understand.
How I use AI agents without outsourcing engineering judgment
A practical AI-assisted architecture workflow using Codex, Claude Code, independent reviewers, evidence, and explicit human decision points.
READ NOTE.02A practical AI coding workflow with Codex, Claude Code, and reusable skills
How reusable skills, repository guidance, specialized agents, and review gates make AI-assisted engineering repeatable rather than improvisational.
READ NOTE.03From demo to production: what usually breaks first
A practical map of the first reliability, workflow, and observability gaps I look for.
READ NOTE.04The backend is where product decisions become real
Why unclear product behavior eventually shows up as queues, retries, state, and edge cases.
READ NOTE.05What I want to see before I trust an AI workflow
Evals, observability, review points, and the places where human judgment should stay explicit.
READ NOTE.06Discipline beats talent in production work
Why reliable systems come from boring loops: clear boundaries, observability, review points, and follow-through.
READ NOTE.07Technical cofounder, founding engineer, or software architect?
A practical guide for founders choosing between a technical cofounder, a founding engineer, and a fixed-scope software architecture engagement.
READ NOTE.08What a technical cofounder should decide before the first engineering hire
The product, architecture, delivery, and ownership decisions a technical cofounder should make before growing an early engineering team.
READ NOTE.09Architecture review before scaling a connected product
What to review across devices, mobile applications, cloud services, telemetry, and operations before a connected product scales.
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