Jim nailed the core problem. I've been building exactly this "missing layer" for past few months. The challenge isn't just connecting product decisions to code. It's that product context lives in a format that's optimized for human communication, not machine consumption. When engineers feed this to LLMs, they spend massive effort "re-contextualizing" what stakeholders already decided. I built TypMo (https://typmo.com) around two structured formats that serve as this context layer: PTL (Product Thinking Language)- Structures product decisions (personas, objectives, constraints, requirements) in a format both humans can read/edit and LLMs can parse precisely. Think YAML for product thinking. and Interface Structure Language (ISL) - Defines wireframes and component hierarchies in structured syntax that compiles into visual mockups and production-ready prompts. LLMs don't need more context, they need structured context. The workflow Jim describes (stakeholder meeting → manager aggregates → engineer re-contextualizes for LLM) becomes: stakeholder meeting → PTL compilation → IA generation → production prompts.

LEt's see where it goes!

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4b11b4 2 hours ago | parent [-]

Nice and I'm thinking along similar lines but not DSLs.

My intuition off reading what you wrote is... Nobody is gonna want to write PTLs and ISLs.

	▲	aditgupta an hour ago \| parent [-]
		Exactly right, and that's the core point. Users don't write PTL or ISLs. Let's say you have customer interactions (fetched from Zoom) or product/research notes. The AI structures that into PTL automatically. You see clean, editable notes and visual wireframes + high-fidelity prototypes and prompts. The structured formats exist in the background for token efficiency and interoperability.