Stop guessing. Forecast.

Every sprint ends with a Slack thread that says some variation of "users are going to love this." The confident ones start with "obvious win." The cautious ones add a "I think" at the front. Three weeks later, the data is in: adoption at 8%, churn up half a point, a rollback scheduled for Tuesday. The post-mortem says "didn't resonate." Everyone nods. Nobody had a better plan.

This is the default state of product development. It isn't laziness and it isn't incompetence — it's a fundamental information problem. You cannot know how a population of real users will react to a change until you expose them to it. And once you've exposed them, you've already paid: engineering time, customer trust, sprint velocity. The feedback loop that's supposed to make teams smarter takes six weeks minimum, and by the time you close it, the context has changed anyway.

For decades, the workaround was qualitative research: user interviews, focus groups, surveys. None of it scales. A survey with 200 respondents might take two weeks to design, run, and analyze — and still misses the tails. The edge cases, the churners, the power users who hate the new UI but won't say so until they cancel. The users whose behavior you care most about are the hardest to represent in a sample.

What changed is not the need. Teams have always needed this. What changed is the feasibility.

In 2026, LLMs carry enough persona context — behavioral patterns, price sensitivity, category preferences, frustration triggers — to model a specific user type with fidelity that would have seemed impractical two years ago. And agent orchestration frameworks now let you run hundreds of independent reasoners in parallel, without a human in the loop, in minutes instead of weeks.

Which means you can, for the first time, simulate.

Not "ask ChatGPT what users will think." That's not simulation — that's vibes with extra steps. A single model giving you a single opinion is as useless as a single interview. What matters is distribution. You need 500 independent agents, each holding a different persona context — different role, different pain level, different price anchor, different willingness to switch — and you need them to react to your change without coordinating with each other. Some will love it. Some will shrug. Some will argue. You're not looking for consensus. You're looking for signal.

That's what Presume is. A simulation engine, not a chat interface. The agents don't just rate your pricing page — they argue about whether it's fair relative to what they're used to paying. They notice when the new onboarding flow is faster but asks for more data upfront. They upgrade when the value is obvious and churn when it isn't. Position × volume × parallelism gives you a probability distribution, and a distribution is what you ship from — not a feeling.

This is not for everyone, and being honest about that matters.

If you're a VC-backed consumer app shipping twice a year with the luxury of a year-long product cycle, Presume will probably feel like overkill. If you're a marketing team looking for a vibe check on copy before you post it, there are faster, cheaper tools. This is built for PM-led B2B teams who ship weekly — teams where each sprint touches customers, where a mispriced feature costs real revenue, where the cost of being wrong is measured in churn and support load, not just embarrassment.

For those teams: you don't need to wait six weeks for the feature-rollout post-mortem. You can run a simulation in twelve minutes and go into the sprint planning meeting with a forecast you can defend instead of a gut feeling. You can test the pricing change, the new onboarding gate, the "freemium tier we might add." Not because you're guessing less — because you've replaced guessing with something better.

We owe you the disclaimer too. Presume is only as good as the product context you give it. Drop in two sentences about your ICP and you'll get back two-sentence-quality answers — coherent, even articulate, but shallow. Pipe in your real cohort distribution, your actual pricing tiers, the segments that churned last quarter, and the personas start arguing the way your customers actually argue. Garbage in, beautifully-formatted garbage out. We're not pretending otherwise.

Presume's job is to make "I think users will..." the most expensive sentence in your sprint planning.