Effective AI Code Development
Field-tested practices, prompting discipline, and design-first methods for shipping with AI tools.
Articles
An AI-Based Coding Assistant Needs Boundaries, Not Just a System Prompt
A general-purpose model does not become a dedicated coding product because of a system prompt. Reliable assistants need scope, routing, policy, and evaluation.
The 183k-Token Mistake I Made Because the Agent Lacked Context
A small AI infrastructure presentation reached 183k active-context tokens because I left source scope, tooling, and verification boundaries undefined.
Why AI Won't Build Secure Software Unless You Instruct It How
One security requirement in a planning document changed an entire database design. A field note on engineering requirements driving AI-assisted development.
One Line That Saved Me 20,000 Tokens in Claude
One sentence added to a Claude Code prompt cut roughly 20,000 tokens in a single sprint by stopping redundant file reads on a large compliance project.
How to Avoid Context Burnout in AI Coding Workflows
AI coding works better when teams treat context as a managed working buffer, not infinite memory, and preserve rules, state, and milestones outside the chat.
Two Years of AI-Assisted Code Development. Here Is What I Learned and Built.
Field notes from two years of building 50+ production apps with AI tools — and how every lesson from that journey shaped the blog you are reading right now.