The original title is "Lessons from Embedding an LLM Inside a Drag-and-Drop Editor"

Short summary

A detailed writeup of embedding an LLM inside a drag-and-drop editor built on Puck, where the core challenge is ensuring AI output is structurally valid, not just semantically good. The author found that prose descriptions of component schemas fail at scale, and that placing schemas in the system prompt rather than user messages prevents drift in multi-turn generation-critic-refinement loops. Pipe-separated enums and inline constraints in formal notation proved most effective.

• •LLM output in structured editors must be schema-valid, not just semantically correct
• •Prose schema descriptions fail at scale; formal notation with enums and constraints works better
• •Schema placement in system prompt prevents critic-pass drift in multi-turn flows

Generated with AI, which can make mistakes.