Serverless AI primitives, and the control they cost

Technology

Langbase packages the parts of an AI feature as hosted primitives. A pipe is a prompt, a model, and tools deployed as an HTTP endpoint. Memory is retrieval you do not have to run. The pitch is an agent in production without standing up infrastructure.

That is a real accelerant early on, and it is the same trade every framework decision makes: how much of the system are you willing to have live in someone else's control plane. Our answer changes by layer, and this page is about where it changes.

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The trade

What hosted primitives buy, and what they cost

  1. A pipe is a prompt with a deploy target

    Model choice, system prompt, tools, and variables packaged as a versioned HTTP endpoint. It collapses the gap between a prompt someone tuned in a playground and something production can call, which is exactly where a surprising number of promising AI features quietly stall out.

  2. Your request path gains a hop and an owner

    A pipe is Langbase's endpoint calling the model provider on your behalf, so every generation crosses two services instead of one. That is a second uptime dependency and a second place a timeout can start, on a call path that was already the slowest thing in the product.

  3. A prompt in a dashboard is outside your diff

    When the prompt, the model choice, and the tool definitions are edited in a vendor console rather than committed, they sit outside code review and outside your rollback. Fine for a prototype. A governance problem the first time a regulated client asks what changed and when.

The question with any hosted primitive is which layer you are outsourcing. Deployment and scaling, take those. Retrieval quality is different, because it determines whether the answer is right, and it is not something you can escalate to a vendor when the number stops moving.

Langbase has not appeared in a client build we have shipped. We name it here because the trade it offers, speed now against control later, is the argument we have on every AI build regardless of which tool is on the table. Start a conversation.