Let LLMs control your UI (tambo.co)

The piece argues that the next wave of AI apps won’t replace UIs with pure natural language, but will let LLMs control pre-built UI components to combine the strengths of conversation and visual/contextual interaction. Natural language is great for vague goals and exploration, but UIs provide clarity, fast edits and confirmation (e.g., seeing a seat map versus “Seat 23E is available”). Letting an LLM orchestrate text plus UI yields more efficient, predictable experiences and unlocks new patterns like context selection, focus control, and intent signals derived from past actions and component interactions. Practically, this avoids risky “generative UI” that fabricates code or arbitrary controls. Instead the model is given a catalog of allowed components and tools with explicit prop schemas and function signatures: wrap your app with a provider, register TamboComponent entries (name, component, propsSchema) and TamboTool functions (with zod-style schemas), add a MessageInput, and the LLM can invoke or populate those components on behalf of users. That architecture confines model actions to developer-sanctioned functionality, simplifying integration into React apps while improving safety, debuggability, and UX for agent-driven workflows.