Technical articles about AI coding agents, context engineering, and developer productivity.
Without a code graph, AI agents navigate blind and read 15 files to answer a 3-file question. Here's why it happens and how graph-based context selection fixes it.
The practical 2026 MCP stack for Claude Code: the few servers that actually reduce friction, cut token costs, and stay out of your way.
Claude Code feels expensive because context is cumulative — you pay for the full conversation history on every turn. Here's what's burning your budget and how to cut it.
Context rot is the gradual degradation of AI coding output quality as conversations accumulate noise. Learn to spot it, prevent it, and fix it.
Your AI coding agent is only as good as the context it receives. Learn how CLAUDE.md files, memory dir, and graph-based retrieval to eliminate re-explanation overhead and boost first-attempt accuracy.
A real-money breakdown of Claude Code API vs Pro vs Max plans, with benchmarked data on how to cut your bill in half without sacrificing output quality.
Most AI coding sessions waste 80%+ of tokens on irrelevant context. Here’s why it happens, how it hurts cost and quality, and how dependency graphs fix it.
Claude Code is stateless between sessions. Learn how to add scalable, code-linked session memory using CLAUDE.md and vexp.
Learn how AI context windows work, why long coding sessions degrade, and practical strategies and tools like vexp to keep Claude effective and costs low.