From principles to production
Why AI makes engineering fundamentals more important, not less, and how they shape real production decisions.
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18 pages
AI-Assisted Development
Practical guidance on coding agents, AI-assisted engineering workflows, code quality, and keeping human judgment at the center of software delivery.
How I improved AI-generated Python code by setting clear instructions
A reflection on turning one AI-generated Python prototype into reusable coding-agent guidance: clearer implementation boundaries, stronger quality expectations, and a shared quality bar before prototypes become real tools.
Shaping with AI
Parallel agents hit a human limit faster than a system limit
Running multiple coding agents in parallel feels like a speed win until the bottleneck becomes the person trying to supervise all of them.
Shaping with AI
How to set up a Claude Code agent team workflow: from parallel tasks to peer review
A practical walkthrough of setting up Claude Code agent teams with clear roles, task ownership, communication rules, review steps, and lightweight output contracts.
Shaping with AI
Creating agent-backed skills in Codex: a uv-first Python repo health check
I wanted Python repository health checks without flooding the main Codex thread with raw `uv`, `ruff`, `pytest`, and `ty` output. So I built a subagent-backed skill that inspects the repo, runs the usual commands, and returns a compact report with clear pass, warn, and fail signals.
Shaping with AI