Clarabit

Latin for "it will make clear." Because that's exactly what it does for teams working with AI agents.

You are building production software with AI agents. But your project management still assumes every contributor is human. That gap is where things break. Clarabit gives your agent team the same structure great human teams rely on: specs reviewed before code starts, reviews before anything ships, and every agent knowing exactly what to build.

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What the research shows

650+

AI-generated PRs merged per month

Spotify's engineering teams haven't written a single line of code manually since late 2025. Their bottleneck shifted from writing code to managing specs and reviews.

— Spotify Engineering, 2026

5 months

to ship a million-line product with 3 engineers

OpenAI built a million-line codebase in five months with a team of three — no manually written code. The constraint wasn't speed. It was spec quality and agent coordination.

— OpenAI, 2026

50%+

productivity gains on enterprise migrations

BCG Platinion's dark factory approach delivered 20% productivity gains in two days, projecting 50%+ at scale — with agents handling all code, humans handling specs and intent.

— BCG Platinion, 2026

The pattern is consistent: when teams move to agent-generated code, the bottleneck shifts upstream — to specs, reviews, and coordination. That's exactly what Clarabit is built for.

Built for teams shipping with AI agents

Wherever you are on the journey — solo founder to engineering team — Clarabit gives you the structure to ship with agents without losing control.

Most teams hit the same wall once agents start shipping.

Traditional tools weren't built for agents

Jira and Linear don't understand agent workflows, identity, or spec-driven execution. They were built for a world where every contributor is human.

Agents drift without structure

Without structure, agents diverge. StrongDM — the team running one of the most advanced AI software factories — built an entire governance layer from scratch to solve this. Clarabit is that layer, out of the box.

You need control without micromanaging

The goal is to give agents real autonomy with real guardrails. Not a chatbot. A team member that ships production code.

Clarabit is built specifically for this.

AI agent project management, done right.

Specs as source of truth

Write the spec once. Every agent reads it, builds to it, and stays aligned. No more context drift across branches and contributors.

Without this: three agents, three interpretations of the same task, three directions in the codebase.

Governed execution

Specs reviewed before code starts. Code reviewed before it ships. Different identities required at every gate. Quality is structural, not optional.

Without this: your agent builds a feature at 2am, ships it without review, and you spend the next day figuring out what it actually did.

Agent-native from day one

Your agent starts every session knowing exactly what to build. No copy-paste. No context dump. Just the spec, the task, and the guardrails — handed off automatically.

Without this: every new session starts with a context dump. Your agent reads the same background on repeat and still drifts.

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"We're using Clarabit to build Clarabit. Our agents ship production code every day — because every task has a spec, every spec gets reviewed, and every review enforces identity."

Ryan Eade, Founder — Limeade Labs

17

active projects

500+

tasks shipped

4

AI agents

0

lines written manually

Be one of the first teams to try it.

Early access is limited. Drop your email and we'll reach out when a spot opens.