Workflows
How I think about a personal AI operating system
Why I'm building my personal AI operating system from first principles instead of cloning agent harnesses like OpenClaw, with three layers, a boring backend, and a context hub.
Blog
Workflows
Agent design, tool use, orchestration, and the workflows behind reliable AI systems.
Workflows
The 5 levels of AI agents: from simple LLM calls to multi-agent systems
A working framework for the five levels of AI agent complexity, from augmented LLM calls and DAG workflows to agent harnesses and multi-agent orchestration, and how to pick the simplest level that solves the problem.
Workflows
How to build human-in-the-loop for AI agents
Practical human-in-the-loop for AI agents, covering two ways to halt a process in your Python backend, plus the SSE streaming and async production patterns that save state and resume after approval.
Workflows
Context engineering for AI agents: why they still fail in production
Context engineering for AI agents in practice, covering why bad context, not the model, causes most production failures, and how to fix system prompts, tools, and message history.
Workflows
How AI agents actually work
An AI agent is an LLM call, a list of tools, and a loop. A walkthrough of a working coding agent in a little over 200 lines of Python, no framework required.
Workflows
How to build reliable AI agents
A field guide to reliable AI agents. Map the workflow first, use structured outputs for decisions, keep tool calling at the edges, and add recovery and human approval paths.