JOIN HUMAN BEHAVIOR

Join Human Behavior

We're building the product that improves itself: one snippet to collect everything, AI to understand it, and agents that fix and ship. Backed by $5M from General Catalyst, Paul Graham, Vercel, and Y Combinator.

Our Plan

We believe the product that improves itself starts with one thing done well: a feedback loop built on real user behavior.

Human Behavior started as a simple AI that watched session replays, pulled out intent signals and bugs, and summarized them. That worked, and it turned into the rest of this.

Collect — You install one snippet and we instrument everything: session replays, errors, funnels, revenue. No dashboard, no UI. It runs headlessly, because if a company is going to run itself, no human should be clicking through screens to make that happen. One install beats wiring up a dozen MCPs — agents get the whole picture in one place instead of a thin, disconnected slice from each server you have to babysit.

Down the line, own more of what tells you where to go — voice of customer, Zendesk and support tickets, app store reviews. Everything that dictates what gets built next should come from installing Human Behavior and nothing else.

Understand — AI watches the replays and structures what's hard to structure. Our NeurIPS 2025 work ranks which bugs actually matter.

Down the line, much better intent filtering. Knowing what a user was trying to do, not just what they clicked.

Act — Agents run on automations and triggers today. Something breaks, they find it, fix it, and open the pull request. Nothing ships without a human merging it.

Down the line, agents that go looking on their own — reading the data, forming their own ideas about what to build, running the experiment, and validating it through A/B tests. No trigger, no prompt.

And that's just the obvious path. Full product understanding unlocks a lot more. AI QA that actually uses your product the way a person would. A live helper that sees where a user is stuck and drives a second cursor to guide them — or does it for them. Computer-use agents trained on the mountain of session replay data we already have — real humans, real flows, real edge cases. There's a bajillion things you can build once you genuinely understand a product, and almost nobody has the data to try.

Roles

Small team, hard problems, no meetings that should have been a commit. These are the shapes we're hiring for:

Distributed Systems Engineer

San Francisco · On-site · Full-time

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Own the ingestion pipeline end to end — billions of events a day, sub-second queries, zero drama. If Kafka partitions and ClickHouse merge trees are your idea of a good time, we should talk.

Agentic Systems Engineer

San Francisco · On-site · Full-time

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Build agents that read product data, decide what matters, and open real pull requests — then make them boringly reliable. You'll live in tool-calling, evals, and long-running autonomous loops.

Product Engineer

San Francisco · On-site · Full-time

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Design and ship the surfaces users touch, end to end. You write fast React with no wasted re-renders, sweat the last 5% of an interaction, and can tell good design from a mile away.

Don't see your role?

San Francisco · On-site · Full-time

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We're only hiring engineers right now — a good product does its own marketing. If you're exceptional and none of the boxes above fit, invent your own box and pitch us.