If I told you that you could get AI infrastructure out of the box, what would you need?
by•
Not another chatbot builder. Not another “connect your API to an LLM” tool.
I mean the boring, painful infrastructure that you don't want to build every time you ship an AI agent.
Things like:
Agent orchestration
RAG
900+ integrations
Evaluations
Observability & analytics
LLMOps
Payments & usage tracking
Basically:
You build the agent. We take care of everything around it.
What would you need?
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The item I'd add: versioned output contracts.
The moment an agent's output gets persisted, or cached, or read by an eval, its schema is a wire format. Rename a field and you haven't refactored, you've done a data migration, and the release that's still running has to be able to read what the new one writes. It's invisible on day one because you're the only consumer of your own JSON. We only call models with a strict JSON schema and never by parsing prose out of a response, and strict mode has edges you inherit as product constraints. It rejects minItems, so "at least ten of these" is something you handle in code, not something the schema can promise.
The other thing I'd want to know before adopting any of it: what happens to the run that succeeds and returns something wrong? Everything on the list treats a bad result as an error, and the expensive case is a clean 200 with a useless payload.