A product that uses LLMs has to assume the LLM will be hilariously, disastrously, unpredictably wrong sometimes.
If it's not resilient to that, the product isn't viable.
From other episodes
- It used to be that to test demand you made a doorbell in the jungle.2026-04-20
- LLMs don't have an experience for others to resonate with.2026-04-20
- If you're below mean on a given dimension, LLMs pull you up.2026-04-20
- All of the labs would rather not have to give access to the top-of-the-line models via general API.2026-04-20
- LLMs are significantly cheaper if you only append the tokens.2026-04-20
- Before you only had to trust the entity that made the code.2026-04-20
- LLMs are easy to trick by putting words in their mouths.2026-04-20
- LLMs are really good at rebasing.2026-04-20