Pi Durable

Today Earendil and the Pi community shipped Pi 1.0 . This reflects our belief that after countless hours of hardening, maintenance, and active development, Pi is now a solid foundation on which to build. Pi also continues to evolve. Together with Pi 1.0, we are shipping an experimental new package called Pi Durable. Pi Durable was built specifically for long-running, durable, and malleable agents that can run anywhere. We would like you to join in the fun and help us make it the best durable harness there is. Why Pi Durable? Pi the coding agent is built to run on your (remote) machine, inside a terminal, driven by one person. If the process dies, you look at what happened and tell it to continue. That is what Pi 1.0 focuses on and excels at, and that is not changing. At Earendil, we want to bring this technology to everyone, in whatever form fits their needs best. For that, we need a harness that runs anywhere, can be reached from different surfaces, supports infinitely long conversations, survives catastrophic internal and external failures, and lets multiple humans steer the same agents. Pi Durable is that harness. It does not replace the Pi coding agent. It is a framework for building any agentic application, coding agents included. It shares not only code with the Pi coding agent, like pi-ai, but also its principles: minimalism and malleability. It also lets us explore designs in this space without disrupting Pi the coding agent. Lessons we learn building agentic applications on Pi Durable will flow back into Pi the coding agent as they prove themselves valuable. What is a harness? Everybody has their own definition of a harness. We wrote about this previously , but let us reintroduce the concept of the harness for Pi Durable. A harness is storage plus the machinery needed to run one or more conversations with large language models in parallel. It provides the tools those models call, and the execution environments the tools run in. A conversation is an interaction between you and an agent, recorded as a transcript. The agent is the large language model together with its settings, like the thinking level, and the tools it can call. Tools do their work through an execution environment, which can be your laptop, a remote VM, or an in-memory sandbox. Which tools and which execution environment an agent gets is up to each conversation. Everything the harness runs, from calling the model to executing a tool, is a task. Like everything in Pi, Pi Durable is …