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 you build a world for them to live in.
Table Stakes for Pragmatic Development Using LLMs
Updated for 2026: lessons from two years of using Claude Code in production. Context engineering, real eval frameworks, model economics, and agent workflows — what actually works.
Context Engineering: The Skill That Replaced Prompt Engineering
After 12 years in ML and two years building production AI systems, I stopped obsessing over prompts. The engineers who ship better agents are not writing better instructions — they are designing better information spaces.
Every Service Is Going to Need an MCP Layer
REST APIs were designed for humans calling services through UIs. AI agents are not humans. Here is what breaks when you expose your existing APIs to agents, and what the right architecture actually looks like.
What AI Agents Actually Are (And What They Can't Do Yet)
Everyone is building 'agents.' Most are just APIs with a system prompt. Here's the precise definition, what the components that actually matter are, the failure modes I've hit, and how to pick the right pattern for your problem.