# Case study: Dramatyze (/docs/case-study)

Dramatyze is a product the AISquare team built fast, in the open, while running
on AISquare itself. This is a build-velocity and dogfooding story. It is not a
customer governance metric. What it shows is what a small team can ship when the
agent it is building leans on the same governed spine these docs describe.

<OutcomeCounters
  counters="[
  { value: 30, label: 'session hours' },
  { value: 569, label: 'commits' },
  { value: 3, label: 'contributors' },
]"
/>

The numbers come straight from the commit and work-session record below: 30.6
hours of tracked sessions (shown rounded), 569 commits (93 on the backend and
476 across the two frontend builds), and 3 contributors. They measure how the
work got done, not how a customer's agents are governed in production.

## What the timeline shows [#what-the-timeline-shows]

The build ran in distinct phases rather than one continuous grind, which is why
30.6 tracked hours covers more than a month of calendar time.

* **Backend first (Feb 11 to Feb 22).** The backend started on FastAPI and moved
  to Django early, then settled into a steady run of commits up to the v1
  release. This is the 93 backend commits.
* **A real gap (a Vegas and SF trip).** The record has an honest empty stretch
  where no commits land. The work paused and then picked back up. Velocity here
  is bursty, not uniform.
* **Frontend v1, then a v2 rebuild (Mar 1 onward).** The frontend was built,
  then rebuilt as v2. The v2 execution push is where the work concentrates: 229
  commits in a single day, the tallest spike on the chart.
* **Handoff to production (through Mar 17).** v2 reached a ready handoff and then
  production, closing out the 476 frontend commits.

Three people did this: one on the backend, one on the first frontend, and one
driving the v2 frontend rebuild. The shape of the work, long quiet stretches
broken by short high-output pushes, is what you would expect from a small team
shipping a real product around the rest of their lives.

## Why this belongs in these docs [#why-this-belongs-in-these-docs]

The point of dogfooding is that the team building AISquare ships on AISquare. The
same [Govern](/docs/govern/connect-your-agents) step that wraps any agent wrapped
the Dramatyze agent, so its decisions landed on the
[reasoning and memory graph](/docs/collective-intelligence) like any other run.
The velocity above is the proof we care about for this page: governing an agent
did not slow the team down. The agent kept running as-is while every decision
started shipping traces.

What this page does not claim is a production governance metric, a blocked-attack
count, or a compliance outcome for a customer. Those are real, and they live with
the [Trust Loop](/docs) and [Collective Intelligence](/docs/collective-intelligence)
pages where they belong. Here the honest claim is narrower and still worth
making: a small team built and shipped a customer-facing product fast, on the
same spine we ask you to put your agents on.

## Next steps [#next-steps]

<Cards>
  <Card title="Connect your agents" href="/docs/govern/connect-your-agents" description="Wrap the agent you already have. It keeps running as-is while decisions start shipping traces." />

  <Card title="Collective Intelligence" href="/docs/collective-intelligence" description="How governed decisions compound on the reasoning and memory graph." />

  <Card title="Quickstart" href="/docs/getting-started/quickstart" description="One complete first call, governed end to end, in about five minutes." />

  <Card title="Use these docs in your agent" href="/docs/use-in-your-agent" description="Query this whole corpus as context over MCP or as plain Markdown." />
</Cards>