Agentspan

Agentspan is a tool for developers who build AI agents. It solves a common headache: what happens when your agent's process crashes, or when it needs a human to approve an action? Agentspan makes your agents durable. You write your agent definitions in Python, and Agentspan compiles them into workflows that run on its server. The execution state lives outside your main application process. This means if your app dies, the agent's work isn't lost; you can reconnect from anywhere and it picks up right where it left off.

It works by providing a clean Python SDK that sits on top of the Conductor orchestration engine, which is used by companies like Netflix and Tesla. Key features include automatic retries for tool calls, the ability to pause an agent for human approval (and resume it from Slack, a web portal, or code), and easy ways to chain multiple agents together into pipelines. Everything is logged and observable, so you can see every tool call and LLM request. It also includes a testing framework that lets you mock runs and assert on logic without needing an LLM, which is great for CI/CD pipelines.

This tool is built for developers and engineering teams who are moving AI agents from prototypes into production. It's particularly useful for building reliable, long-running automation tasks—like processing thousands of records, handling customer support workflows that need manager sign-off, or creating multi-agent research and writing pipelines. If you're tired of agents failing because of a network blip or a process restart, Agentspan provides the infrastructure to make them resilient.