alt Hacker NewsI don't really understand the criteria for when something is 'proven' to the Pi team. Jev and the like took off less than a month ago, but MCP has been growing for nearly 2 years, and it only gets support now?
Pi felt nice when I used it, and I do value keeping things minimal, but I just find the criteria very uneven.
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> but MCP has been growing for nearly 2 years, and it only gets support now?
I don't know if you were aware, but not shipping with MCP was one of its "features":
https://mariozechner.at/posts/2025-11-02-what-if-you-dont-ne...
They let you have it via a plugin/extension.
It was already very good and has been used/battle tested by many us for a long time.
Some tools used to be 0.x for ages and, in this case, the 1.0 signals they're happy enough and allows them to promote things in a better way.
This (edit the durable part) is I guess the natural evolution of playing around building temporal like things for a need that many have.
the latest 07-28 MCP spec is quite different than the previous iterations of MCP, so I understand the delay there tbh.
I agree. I don't necessarily "trust" Anthropic and OpenAI when it comes to CC/Codex respectively, but I respect that they have immense internal resources and telemetry to be able to understand what features move the needle and nudge traces in the right direction. I don't understand how non-labs judge feature inclusion? Just vibes?
Armin from Earendil here. I think the question is fair, and quite frankly the answer is pretty disappointing: we look at what the models are doing. They are trained on their respective harnesses and we're not here to fight their behavior.
Codex in particular is using responses lite internally and relies on codemode for parallel tool calling. So codemode was a given.
Jev on the other hand is new but it's not the first type of model we had troubles with supporting in Pi and we looked at how to make that make sense. The internal pi-ai SDK supports image generation and classifier models, but without building an extension it was never possible for you to utilize it.
So there was a while functionality of Pi that few people used, because there were no obvious ways to hook it up with the coding agent. Codemode also allows us to close that gap.
And once you have codemode, modern MCP can work quite well if the servers cooperate.
Classification models have been around for literally almost a century at this point. I think it's safe to say they are a proven technology.
The only thing that makes Jev and the likes particularly interesting is that it is a general purpose classifier. In the past, classification tasks meant training a new model to solve your problem. Now you can just use an off the shelf general purpose model and hit the ground running.