Welcome to NEXUS PRIME, and why we're building it

I counted once. In a single afternoon of "using AI to get work done," I had seven tabs open: one chat model for a first draft, a second to sanity-check it, a third for an image, a research tool for sources, then a doc, a spreadsheet, and my inbox to stitch the pieces together. The models did maybe forty percent of the work. I did the other sixty, copying, reconciling, re-pasting, and remembering what the last tool had already told me.

That afternoon is the reason NEXUS PRIME exists. Somewhere in the last two years, the model stopped being the bottleneck. The bottleneck now is that you are the integration layer, the glue between a dozen tools that don't talk to each other.

Our bet is simple: the next real gain in AI work won't come from a smarter model. It will come from orchestration, software that holds the whole job in its head so you don't have to.

What NEXUS PRIME actually is

It's a single control surface for a fleet of more than 100 specialist AI agents, wired into six major model providers (OpenAI, Anthropic, Google, Mistral, Groq, and xAI), plus a set of open models we host ourselves.

You hand it a directive in plain language. The orchestrator reads it, decides which specialists the job needs (a researcher, a strategist, a writer, a reviewer, whatever the work actually calls for), routes each subtask to the model best suited to it, checks the work as it goes, and hands back a finished result.

You don't manage the team. You don't pick the models. You describe the outcome you want, and the system runs it.

Why "100 agents" is more than a number on a slide

The interesting part isn't the count. It's that these aren't 100 copies of the same assistant. They're 100 specialists, each shaped for one kind of work. The compliance reviewer reads a draft the way a cautious lawyer would. The copywriter actually writes like a copywriter. The security reviewer thinks like someone trying to break in. A project manager keeps the whole thing on schedule and on brief.

Each specialist carries three things:

When you need a real team, you don't want a hundred interchangeable generalists talking over each other. You want a hundred people who know their lane, and know when to hand off.

The shape of the product

Three tiers, one orchestrator underneath all of them:

What changes between tiers is concurrency, access to our own hardware, and how far the fleet can scale. The engine is the same one in all three.

What this blog is for

Three things, honestly.

The craft, first. Multi-agent systems are young, and most of the real lessons aren't written down anywhere yet. We'll publish what we learn: the orchestration patterns that hold up under load, the ones that look elegant and quietly fall apart, and the failure modes you only meet once twenty agents are running at once.

Then the build. What shipped, what broke, what's next. The actual log, not a stage-managed milestone reel.

And the bigger question underneath all of it: when one system can run specialist work end to end, what does "a job" mean? What does "a company" mean? We have early opinions, and we'll argue them in public.

The invitation

We're in waitlist mode. The first wave of pre-orders gets 50% off the first year of Power or God Mode. Signing up sends you exactly one confirmation email, no drip sequence, no manufactured urgency. When pre-orders open, we'll tell you once.

If you've ever finished an afternoon of "working with AI" and realized you were the one doing the work, that's the problem we're building against. Come watch us build it.


Next: "The 100-agent problem", why most multi-agent systems come apart somewhere past ten agents, and the design choices that keep ours from doing the same.

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