Pi reaches 1.0: an open-source harness taking on Claude Code and Codex
Next has written about Pi, an open-source harness that has just reached version 1.0.0. For readers unfamiliar with the term, a harness is the software layer around an AI model that lets it read files, run commands, or search the internet.
Pi aims to be minimal but extensible. It is compatible with more than 1,500 models and variants, both commercial and open-weight models that can run locally, and it presents itself as an alternative to Claude Code and Codex that does not depend on Anthropic's or OpenAI's models. Developers see the move to 1.0 as a sign of maturity.
The article also covers recent additions: MCP connectors, a 'codemode' option, and support for ChatGPT. Pi Durable is described as able to withstand catastrophic internal and external failures.
To be clear, about 80% of the text is reserved for subscribers, so I am limiting myself to what can be read publicly. In the comments, several readers compare Pi with OpenCode: one finds it very lightweight but harder to configure, especially for MCP, and another points to the Oh-My-Pi variant. The author also announced an article about installation and usage.
What interests me is the idea of separating the harness from the model: you can change models without changing your tool. Whether Pi's simplicity holds up as usage gets more complex remains to be seen. And you, which harness do you use day to day for coding with AI?
Source: Next
Pi aims to be minimal but extensible. It is compatible with more than 1,500 models and variants, both commercial and open-weight models that can run locally, and it presents itself as an alternative to Claude Code and Codex that does not depend on Anthropic's or OpenAI's models. Developers see the move to 1.0 as a sign of maturity.
The article also covers recent additions: MCP connectors, a 'codemode' option, and support for ChatGPT. Pi Durable is described as able to withstand catastrophic internal and external failures.
To be clear, about 80% of the text is reserved for subscribers, so I am limiting myself to what can be read publicly. In the comments, several readers compare Pi with OpenCode: one finds it very lightweight but harder to configure, especially for MCP, and another points to the Oh-My-Pi variant. The author also announced an article about installation and usage.
What interests me is the idea of separating the harness from the model: you can change models without changing your tool. Whether Pi's simplicity holds up as usage gets more complex remains to be seen. And you, which harness do you use day to day for coding with AI?
Source: Next
Comments 0
Leave the first comment, in any language.
Log in to comment