Agent Optimization

An open book on building AI agents, from fundamentals to engineering practice, with runnable code for each chapter.

Persistent memory for coding agents. It records what the agent did in each session and feeds the useful parts into the next one.

An open-source memory platform that gives agents long-term memory across sessions through a self-hosted knowledge graph.

A large, battle-tested kit of agents, skills, hooks and commands that tunes Claude Code for quality, security and cost.

Nous Research's self-improving agent, which creates skills from experience, improves them in use and remembers you across sessions.

A Python framework for building realtime voice and video AI agents, with telephony, job scheduling and MCP support built in.

A 45M-parameter tool-calling model in a single 14 MB binary that runs a session in about 28 MB of RAM.

An open-source context database for agents that stores memories, resources and skills under a viking:// filesystem you can browse.

A desktop workspace for running a fleet of coding agents in parallel, each in its own git worktree, tracked in one place.

An agent meta-harness for Claude Code and Codex that runs coordinated swarms of agents with shared memory.

GitHub's toolkit for spec-driven development. Write the spec first, then let the agent plan, split the work into tasks and build.

A complete software-development method for coding agents, built from composable skills like planning, TDD and debugging.

A team-level memory hub that turns conversations, docs and code into reusable agent memory: chat memory, skills, a wiki and a code graph.