Tagged: AI agents
5 articles on ai agents.
Penpal: Dispatch Tool Today, RPG Interface Tomorrow
I built a tool that turns GitHub issues into pull requests using a three-agent pipeline. That's the boring part. The interesting part is what happens when you stop thinking about AI agents as productivity tools and start thinking about them as a workforce, and build a world for them to live in.
Table Stakes for Pragmatic Development Using LLMs
Updated for 2026: lessons from two years using Claude Code in production. Context engineering, real eval frameworks, model economics, and agent workflows. What works.
Context Engineering: The Skill That Replaced Prompt Engineering
Prompt engineering is a symptom, not a skill. The engineers shipping better agents aren't writing better instructions. They're designing better information spaces. Context engineering is the meta-skill no one teaches.
Every Service Is Going to Need an MCP Layer
REST APIs were designed for humans calling services through UIs. AI agents are not humans. What breaks when you expose your existing APIs to agents, and what the right architecture looks like.
What AI Agents Actually Are (And What They Can't Do Yet)
Everyone's building 'agents.' Most are just APIs with a system prompt. The precise definition, the components that matter, the failure modes I've hit, and how to pick the right pattern for your problem.