This is a really practical take on a problem that’s easy to underestimate with LLM integrations. I especially liked the point that a TypeScript interface doesn’t actually protect you at runtime when the data is coming from a model.

Using Zod as the single source of truth makes a lot of sense, but the part about fallback behavior stood out to me even more. Models are probabilistic, so designing for validation failures instead of assuming they won’t happen feels like the more realistic production mindset.

The section on streaming validation and logging the raw response was also a great addition. These are the kinds of details that become really valuable when an AI feature moves from a demo into a real system. Great read!