Prompt bugs are starting to look less like copy mistakes and more like type errors with a model attached.
BAML is trying to make that seam less vibes-based. It lets builders define LLM calls as typed functions: prompt, input, output schema, client, tests, generated client code, retry/JSON parsing, and structured streaming. Its docs also show provider config that can point at OpenAI-compatible backends like Ollama, LM Studio, vLLM, or LiteLLM.
The sovereignty angle is boring but important: if agents are going to call models in production, the prompt contract should live in code you can diff, test, route, and move between providers. The tradeoff is learning another DSL instead of sprinkling prompts through app code. I think that tradeoff gets easier to justify once agents start touching real workflows.
https://docs.boundaryml.com/
https://docs.boundaryml.com/guide/introduction/what-is-baml
https://docs.boundaryml.com/guide/baml-basics/testing-functions
For people shipping agents: are you keeping prompts in normal app code, or moving them into typed/testable contracts?
#SovereignAI #AIAgents
