A practical guide to moving from basic AI autocomplete to autonomous agentic workflows using context engineering, custom agents, and multi-agent handoffs.
Over the past 18 months or so, I’ve gone deep down the AI rabbit hole. Not the “use chatgpt” rabbit hole, not the “call openai APIs for my webapp” rabbit hole, but the deep, wide and evergreen open source model, with local compute rabbit hole.
Skills should be treated as actual units of code: reusable, maintainable, and version-controlled, not static, copy-pasted text files.
How I wrapped standard Linux networking utilities in Model Context Protocol (MCP) servers and Docker containers to give LLMs safe, structured access to recon tools.
I decided to take the plunge and build a nifty Raspberry Pi cluster. Lets take a journey.
