From the braid team
Essays on context engineering, AI coding standards, and the systems behind better AI coding output.
We write about the patterns and systems that make AI coding agents more reliable. That includes context engineering for large codebases, cross-tool prompt management across Cursor, Claude Code, Codex, Gemini, and other agents, and the operational work required to turn prompts into reusable systems instead of scattered text files.
Expect posts for solo builders creating a personal prompt system, engineering leaders rolling out team prompt management, and creators packaging proven workflows into installable standards packs. Every post draws from real-world experience building braid and shipping with AI coding tools. New posts land as we find patterns worth operationalizing.
Why Workflows + Agents + Skills Beat Prompts Alone
Prompts are the right start, not the finish line. Teams shipping reliably with AI combine specialist agents, reusable workflows, and on-demand skills.
What is Context Engineering for AI Coding Agents?
Context engineering is the practice of curating exactly what information your AI coding agent receives. Learn why it matters and how to do it right.