The Question I wanted to know if I could delegate work to an LLM the way I’d delegate to a person. Not “ask it a question and get a response” delegation—actual structural delegation. Write a ticket, assign it, walk away, get a pull request back. The kind of handoff where you define the work, set the constraints, and trust the process to produce a result. Most LLM tooling right now is interactive.

Memory What is Claude Code memory? It’s the system by which you provide persistent instructions to the model across sessions. You write rules in files called CLAUDE.md at various levels of your project, and Claude Code assembles them into a block of text that gets included in every interaction. If you’ve spent any time configuring this system, you’ve probably noticed something odd. Claude follows your rules for a while, then quietly stops.

The most talked-about development methodology in AI coding right now is named after Springfield Elementary’s lovably dim student. Anthropic’s official Ralph Wiggum plugin for Claude Code implements an autonomous development loop that keeps working on your code until completion—embodying the philosophy that persistent iteration, not perfection, drives results. Developer Geoffrey Huntley’s technique has enabled developers to ship six repositories overnight and complete $50,000 contracts for $297 in API costs. The technique’s elegance lies in its simplicity: a feedback loop that intercepts Claude’s exit attempts and re-feeds the same prompt, letting the AI iteratively refine its work until success criteria are met.