juggling three balls but i never learned how to juggle... so we made a formula instead

Hey all! :)

A short founder-friendship story before the point: I met my cofounders in high school. And it wasn't just any school, it was the top computer science + math school in Poland at the time. So basically a building full of nerds who loved explaining the entire world with math.

We pretty much didn't change since that time.

So the other day, when we were trying to figure out where AI value actually comes from, we did the most us thing possible. We turned it into a formula.

Let me break it down:

1. competence = domain expertise turned into mapped processes, skills, and best practices. The "knows what good looks like" part.

2. execution = the harness + the model together (think Claude Cowork, or OpenClaw + gpt). The "can actually do the thing" part.

3. context = situational, object-oriented data. It mixes stuff the LLM can't see (external sources) with memory from past interactions with a user. Optimized for retrieval, and cheap enough to actually digest.

Okay. So here's the thing. We've been floating around a bunch of builder communities lately. And we kept noticing that everyone's trying to solve all three at once. Like, watch:

For competence -> most teams start with some expertise, or just build it on the go. For execution -> they fork OpenClaw/Hermes, evaluate a bunch of models, tweak harnesses. For context -> they build integrations, parse data, process it, try to make a little "brain" for their exact use case, then optimize retrieval.

Sometimes it's not even teams. It's one person trying to do all three solo. And most of them fail.

Not because they're dumb or sth, just because of zero focus. So we made a call and picked one: context.

We're on a mission to build the default context infrastructure. The thing users, companies, and apps can all just plug into and stop worrying about, so they can go focus on their actual core business.

And, not to flex, but... we're doing damn good :)