DHH's Rust Benchmark Measured the Agent, Not Elixir
DHH's Campfire benchmark has Rust far ahead of Elixir and Go. The repos show Rust got 398 commits and 16 merged performance PRs. The others got three.
Writing · Tag
Posts tagged AI tools
31 posts on AI tools. Or browse the full writing index →
Posts tagged AI tools
Where AI Belongs in a One-Person Content Operation
The agent pipeline that runs this blog, stage by stage: where AI is safe because its output is checkable, and where a human has to stay in the loop.
Linux Setup Was a Hazing Ritual. Agents Changed It.
Linux setup used to cost me hours per problem. Six things broke across my two machines, most fixed in minutes with an agent, and two that took longer.
I Built the Distribution Tools My Blog Needed
Ten skills my coding agent runs to fact-check drafts and find where my posts stop reaching people, tested on my own site before I sold them.
Would I Trust Agents to QA My Daily Driver?
Omarchy's new Agentic QA swarm tests every release. I run Omarchy on two machines and update within days. Here's what the design catches, and what it can't.
Omarchy Runs Your Coding Agent With the Safety Off
Omarchy's launcher gives every coding agent a skip-approval flag by default. The attack surface a security lead inherits, and what Omarchy gets right.
I Read Omarchy's AGENTS.md So You Don't Have To
Omarchy's own AGENTS.md, skills, and a design doc reviewed by two other vendors' agents, read from the quattro branch instead of the README.
Agents Are Already Writing a Language You Can't Read
Compression toward machine-preferred notation isn't a future bet. It's already landing in context formats, agent protocols, and the files your harness reads.
Structured LLM Output in Elixir: Which Library, When
Four Elixir options for schema-validated LLM output, scored on maintenance, provider coverage, retry behavior, and escape hatches.
What Elixir Gives a Coding Harness for Free
José Valim's case for Elixir as a coding-agent harness holds up on the runtime. The tax is the ecosystem around it: sandboxing, plugins, and SDKs.
AIOS v2: The Scope Is the Filesystem
A restructure log: what broke in the AIOS v1 tree at multi-scope scale, why identity-first beats type-first, and what shipped in v2.
The One File Where Your AI Model Names Live
Model names scattered across every repo's config rot the day a model gets deprecated or repriced. One git-versioned markdown table fixes it for good.
The Four Claude Code Hooks I Run on Every Project
The exact hooks in this repo settings.json: a .env guard, a draft-post warn, mix format, a JSON validator, and the real matcher and exit-code mechanics.
TDD With Claude Code in Elixir: What Holds Up
Where TDD with Claude Code actually holds up in an Elixir/Phoenix codebase (ExUnit async, mix precommit, Ecto.Multi idempotency) and where it breaks.
What I Put in CLAUDE.md After 50 Commits With It
The CLAUDE.md entries that actually earned their place on a real project: mistake-driven rules, not a speculative template you copy once and forget.
The 17x Discount Hiding in Your AI Coding Bill
My team's $200 AI coding seats consume $1,800–$3,500 of API-priced tokens a month. The 10–17x arbitrage nobody prices in, and how to budget for it.
AIOS: An AI Operating System in Plain Markdown
I open-sourced the AI operating system I run daily: a git-versioned markdown vault, cross-repo wiring, and a nightly ingest loop. Fifteen minutes to set up.
Building an AI Memory That Outlives Any Single Agent
Your accumulated agent memory is a bet on one vendor's format. Build a portable, git-versioned knowledge layer any agent can read instead.
The Claude Code Plugin Stack I Actually Run
The Claude Code plugins that earn a permanent slot in my stack, sorted by what they actually change: my process, my domain expertise, or just friction.
Programming Sucks, Now With Agents
An homage to Peter Welch's Programming Sucks, updated for agents: a genius intern with amnesia, hallucinated packages, and a closet that eats your auth layer.
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.
Your CLAUDE.md Is the Onboarding Doc You Never Wrote
A CLAUDE.md is executable tribal knowledge: the onboarding doc you never wrote for humans, finally read by something that acts on it.
The AI Coding Agent Bugs I Catch Every Week
Eight failure patterns I see running AI coding agents daily: the confident wrong answers, the lost context, and the bugs they reliably ship.
15 Elixir Libraries I Reach For in 2026
The Hex packages I install on day one of a new Elixir project in 2026, what each one earns its place doing, and the ones I dropped along the way.
Elixir Is the Language AI Codes Best
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 are the same boring properties that have always made Elixir pleasant, now compounded by AI.
Prompt Skills, Not Claude: Four Rules from Anthropic's Engineers
Most engineers prompt Claude one sentence at a time. Anthropic's own engineers prompt skills. Four rules from their recent talks, with the operator nuance the talks left out.
How I Prompt Claude as a Staff Engineer (50 Prompts I Actually Use)
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): An Honest Deep Dive on the Multi-Agent Orchestration Platform
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...
The Claude Code Resource Bible: 46 Tools Worth Knowing in 2026
The 46 Claude Code tools worth installing in 2026, and the ones to skip, sorted by category with a recommended starter stack at the end.
AI-Assisted Engineering Isn't Faster Coding. It's a New Workflow.
Most engineers using Claude Code see a 10–15% speedup. The teams seeing 40–55% sequence work differently. The four modes I use AI in, what to never delegate, and how to get a skeptical team across the line.
My Daily Agentic AI Workflow
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.