AI in production : reflecting on one year, five projects and dozens of factories deployed.
Twelve months later, we’ve launched four AI-native companies and helped implement AI in an existing portfolio company with a hands-on, months-long project. Across our broader portfolio of 20 companies, AI is now present in almost every product and operational workflow. We’ve shipped real systems into dozens of factories. And we’ve had our share of wins, dead ends, brutal rewrites, and joyful breakthroughs.
This article is not a victory lap. It’s not even advice. But it is a set of reflections — honest, messy, and grounded in real deployments. If you’re a builder or operator trying to make AI useful in production — this one’s for you.
We’ve seen a recurring anti-pattern: a SaaS product adds a chatbot on the side. Sometimes it’s called a “copilot.” Sometimes it’s “AI-powered search.”
Zero impact on activation, zero on retention, zero on revenue. Why? Because slapping AI on top of an existing flow without rethinking the core job-to-be-done is like painting a forklift neon yellow and expecting it to go faster.
