Talon: a self-hosted harness for long-lived AI agents

A developer released Talon, an open-source self-hosted harness for long-lived AI agents that persist beyond single-task loops. Talon supports multiple frontends (CLI, web chat, Slack) and swappable model backends (OpenAI, Anthropic, local models), enabling agents to maintain memory, run background jobs, and operate continuously. The project aims to provide infrastructure for assistants that integrate into real workflows rather than one-shot demos.

Most agent demos are one-shot loops. You open a terminal, give the model a task, watch it call tools, and then the process dies. That is fine for coding sessions. It is a weak shape for an assistant that is meant to live in your actual workflow. Talon https://github.com/dylanneve1/talon is built around the other shape: a persistent agent process with frontends, memory, tools, background jobs, and swappable model backends. Talon can expose the same agent core through: That means the agent is not tied to one UI. The chat app is just a mouth. The core state, tools, memory, goals, and model backend live behind it. The same harness can run through: Each backend implements the same capability interface, so the rest of the system does not need to care which model runtime is active. The important parts are not flashy. They are the things that let an agent keep working after the first message: This is the difference between "chat with a model" and "run an assistant". npm install -g talon-agent talon setup talon start Repo: https://github.com/dylanneve1/talon https://github.com/dylanneve1/talon If this is the kind of agent infrastructure you want more of, a GitHub star helps the project get found.