About speaker

Jeremy Brown

GitGuardian

CTO

Jeremy Brown is CTO at GitGuardian, the security platform specialising in secrets detection, non-human identity governance, and developer security. He joined after the Series B and has helped lead engineering through to the company’s Series C, growing an engineering team that today numbers ~70 people — and is still hiring.
Jeremy is passionate about helping people thrive and to cultivate environments that unlock a team’s potential to achieve remarkable outcomes. GitGuardian’s Engineering organisation is currently transforming into an AI-native engineering organisation. With 80–90% of code now AI-generated, the team is pursuing a “dark factory” vision — building systems that take detailed specs and output features autonomously, shifting engineers from writing code to designing, reviewing, and orchestrating AI agents.
His career spans engineering, product, and sales across multiple continents. He has held CTO and Chief Product & Technology Officer roles, built and led distributed, multicultural organisations of over 130 people, and helped build Red Hat’s Open Innovation Labs. Earlier in his journey, he and a friend set out on motorbikes from London to Cape Town — three years later, they hadn’t quite made it, but had started Limbe Labs, Cameroon’s first startup incubator, providing seed funding and mentoring to founders. Jeremy lives in France.

Talk details

Talk
Engineering leadership Intermediate

Building a Software Dark Factory with Agentic Engineering

Jeremy Brown
Jeremy Brown CTO at GitGuardian
Agentic Engineering AI Culture Engineering Leadership

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.

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