Build an LLM Wiki Your Coding Agent Actually Reads
A markdown knowledge base your AI agent reads and maintains — the three-layer architecture, the ingest/query/lint loop, and the rules that stop it rotting.
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Writing · Tag
11 posts on AI tools. Or browse the full writing index →
A markdown knowledge base your AI agent reads and maintains — the three-layer architecture, the ingest/query/lint loop, and the rules that stop it rotting.
A CLAUDE.md isn't config — it's executable tribal knowledge. The onboarding doc you never wrote for humans, finally read by something that acts on it.
Eight failure patterns I see running AI coding agents daily — the confident wrong answers, the lost context, and the bugs they reliably ship.
The Hex packages I install on day one of a new Elixir project in 2026 — what each earns its place doing, and the ones I dropped along the way.
A Tencent benchmark across 20 languages found Elixir at the top of LLM code-completion rates — Claude Opus 4 hit 80.3% on Elixir vs 74.9% on C#. The reasons aren't an accident; they're the same boring properties that have always made Elixir pleasant, now compounded by AI.
Most engineers prompt Claude one sentence at a time. Anthropic's own engineers don't — they prompt skills. Four rules from their recent talks, with the operator nuance the talks left out.
Fifty prompts I use to ship production AI features, debug distributed systems, and write docs that don't rot. Code review, debugging, refactoring, system design, and PR-quality writing — with five full examples.
Ruflo (formerly Claude Flow) is a hive-mind orchestration layer for Claude Code and friends. 45,000+ GitHub stars, 700,000+ npm downloads, three queen-types...
46 tools across the Claude Code ecosystem, organized by category (official, directories, MCP servers, skills, multiplexers, agent frameworks, automation)...
Most engineers using Claude Code see a 10–15% speedup. The teams seeing 40–55% aren't typing faster — they're sequencing work differently. The four modes I use AI in, what to never delegate, and how to get a skeptical team across the line.
A walkthrough of how I run 4–7 agent sessions in parallel through a normal engineering day. Morning background tasks, mid-morning pair programming, afternoon reviews, end-of-day ops. The interaction modes that work, the handoff protocol, and the trap that makes most agent workflows produce slop.