Building a Software Dark Factory with Agentic Engineering

At GitGuardian, 80 to 90% of our code is now written by AI. We’re building towards what we call a “dark factory”: systems that take a well-written spec and ship a working feature with very little human typing.

GitGuardian is a 7-year-old, post-Series C cybersecurity startup with a 70-person engineering org that’s scaling fast, and we’re SOC 2 Type II certified. Customers trust us to protect their secrets, so there’s very little room for mistakes. We have to reach our goal of getting to a software dark factory while holding the same quality bar as before, not quietly lowering it to make the numbers look good. Our journey has been like changing the engine of a car while it’s still driving!

This is the practical version of that story. Getting here took far more than handing everyone Cursor and Claude Code. I’ll walk through the building blocks we’ve had to put in place to make agentic engineering safe at our scale, from the infrastructure to run fleets of background agents to keeping a lid on spiralling token costs, and I’ll be honest about what worked, what broke, and what it cost us.

I’ll also talk about the human side, because that’s been the hardest part. What it does to how people learn, the stress it creates, the questions about what engineering careers look like from here, and the real work of driving adoption and meeting resistance head-on.

If your team is going down this path, you’ll leave with the how of what we did and not just the why — the technical scaffolding, the changes to how we work, and the lessons we’re still learning about the people side.

One happy surprise worth a mention: going faster hasn’t meant fewer engineers. We’re hiring heavily.