Explore common agent recipes with ready to copy code to improve your LLM applications.
truefoundry/trueforge
The open-source agent harness - the runtime layer that turns an LLM into a working agent.
If an AI agent can’t figure out how your API works, neither can your users
Discover how LLM‑powered agents act as tireless API testers—exposing friction in docs, errors, and design—and learn six essential strategies (consistency, comprehensive docs, rich errors, example‑driven tutorials, simplicity, and feedback loops) to elevate your API’s developer experience for both humans and machines alike.
Agent experience: How to design products that agents can actually use — WorkOS
What engineers and founders need to know about designing APIs, tools, and interfaces for agent-driven workflows
AI Agents: Key Concepts and How They Overcome LLM Limitations
An AI agent is an autonomous software entity that is often used to augment a large language model. Here's what developers need to know.
Paul Iusztin on Twitter / X
Using LLM wikis for agentic coding is pure gold. It's so powerful it feels like cheating. Here is how I used it to develop a coding harness from scratch:1. I ingested multiple coding harnesses repositories into the LLM wiki (e.g., opencode, pi, hermes, etc.) pic.twitter.com/7WE7NI9tnN— Paul Iusztin (@pauliusztin_) June 29, 2026
LLM Agents are simply Graph — Tutorial For Dummies
Ever wondered how AI agents actually work behind the scenes?
LLM Agents are simply Graph — Tutorial For Dummies
Ever wondered how AI agents actually work behind the scenes?
GitHub - humanlayer/12-factor-agents at sidebar
What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers? - GitHub - humanlayer/12-factor-agents at sidebar
Karpathy's LLM Wiki as Agent Memory - Agentic AI Foundation (AAIF)
At work, I’m building agents to handle various operational tasks and have found Karpathy’s LLM Wiki design to be an excellent solution for implementing most ty…
The golden rules of agent-first product engineering
Five principles for building products that work well for AI agents and MCP servers.
Harness engineering: leveraging Codex in an agent-first world
By Ryan Lopopolo, Member of the Technical Staff
Harness engineering: leveraging Codex in an agent-first world
By Ryan Lopopolo, Member of the Technical Staff
Our newest project is taking flight: meet codename goose! 🪶 Today, we launched an open source on-machine AI Agent. It’s modular, works with your preferred LLM, and integrates seamlessly with developer tools and other software via MCP. Developers, check it out! block.github.io/goose/blog/2025/01/28/introdu…
Introducing codename goose
block.github.io