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Show HN: Sectr – Serverless backend platform for easy deployment of AI agents

Hey HN, I've been building Sectr, a backend-as-a-service for making it easy(ier) to develop and deploy AI agents. Deploying agents requires non-trivial systems design work. Consider a support agent: how do you stream me…

Hacker News 最新donald_pinckney2026/10/27 · 昨天6 分钟阅读

以下正文同步自 Hacker News 最新,版权归原站所有,已转换为易读排版。

Hey HN, I've been building Sectr, a backend-as-a-service for making it easy(ier) to develop and deploy AI agents. Deploying agents requires non-trivial systems design work. Consider a support agent: how do you stream messages to your frontend, how/where do you persist messages for frontend fetching later (or for auditing), and when the agent wants to issue a refund, do you spin-down the compute infra while it's waiting on human approval? Sectr aims to be the serverless abstraction and platform to provide these systems for you.No sign-up needed to try using the dev server:

  curl -fsSL https://sectr.dev/install.sh | sh # Install CLI
  sectr init my-agent && cd my-agent # Starter code
  sectr dev # Dev server, with UI to test chatting

Sectr provides:- Streaming of every token, tool call and event, and persistence so they can be loaded fresh later.- Scaling up, and down to zero when the agent needs to wait, and resumption right to the suspended agent's state.- Human approved tools automatically use Sectr's suspension and resumption capabilities, no code needed from you.- AG-UI endpoint for any deployed agent so you can trivially hook up your frontend- Local dev server experience, so you can rapidly debug and iterate on your agent's behaviorAt the core, you can deploy any container image to Sectr as long as it implements a certain shaped HTTP endpoint. In practice, currently Sectr provides adapters to let you deploy your existing OpenAI Agents SDK, LangGraph, or Pydantic AI agents, with only 2 new lines of code:

  app = AgentApp(name="support")
  app.add_route("/chat", openai_agents(agent))

Certainly the hardest part of building Sectr was getting the resumption logic to be correct and invisible, across the Program State x Model Provider x Agent Framework matrix. For example, an earlier bug was when a model replied with text plus a tool call, Sectr would resume that as two separate messages, instead of one message with a text and tool part. This works, but breaks prompt caching (and might subtly change model behavior).Sectr is free during the beta (and can be tried locally without sign-up); I mainly want feedback, especially on dev & deployment experiences, any bugs, and what features would excite you.Introductory video: https://www.youtube.com/watch?v=H-y3wynkKc0Docs: https://docs.sectr.dev Comments URL: https://news.ycombinator.com/item?id=50260969 Points: 2

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