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Younggi Choi

The safety and verification layer for agentic coding —
hooks, skills, and MCP servers that make an AI harness trustworthy enough to run unattended.

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Most AI coding effort goes into the prompt. I think the leverage is one layer below that — in the **harness**: the hooks that stop an agent before it force-pushes, the skills that encode a procedure so it isn't re-derived every session, the MCP servers that hand an agent real context instead of guesses, and the memory that survives a `/clear`. An agent is only as good as the environment you put it in. **That environment is what I build.** Three projects carry most of that work.

Existing languages were designed to be easy for *humans to write*. From here on, most code is generated — so what does a language look like when it's designed to be easy for an **LLM to reason about and optimize**?

Developer → Intent (what) → LLM → Semantic IR → Native Optimizer → Machine Code

You declare goals and business rules;