🦄 ai that works: Generative UIs and Structured Streaming
🦄 ai that works
A weekly conversation about how we can all get the most juice out of todays models with @hellovai & @dexhorthy
On this week's AI That Works, we'll explore hard problems in building rich UIs that rely on streaming data from LLMs.
Specifically, we'll talk through techniques for rendering **STRUCTURED** outputs from LLMs, with real-world examples of how to handle partially-streamed outputs over incomplete JSON data. We'll explore advanced needs like
Fields that should be required for stream to start
Rendering React Components with partial data
Handling nullable fields vs. yet-to-be-streamed fields
Building high-quality User feedback
Handling errors mid-stream
Pre-reading
To prevent repeating the basics, we recommend you come in having already understanding some of the tooling we will be using:
Discord
Cursor or VS Code
Programming languages
Application Logic: Python or Typescript or Go
Prompting: BAML (recommend video)
Meet the Speaker 🧑💻
Meet Vaibhav Gupta, one of the creators of BAML and YC alum. He spent 10 years in AI performance optimization at places like Google, Microsoft, and D. E. Shaw. He loves diving deep and chatting about anything related to Gen AI and Computer Vision!
Meet Dex Horthy, founder at HumanLayer and coiner of the term Context Engineering. He spent 10+ years building devops tools at Replicated, Sprout Social and JPL. DevOps junkie turned AI Engineer.