Career Development

Originally published on Latent Space FDEs have the hottest job in AI. Labs, startups and PE firms are all hiring engineers to sit inside their customers’ operations and solve their problems. Almost none of them agree on what those engineers are supposed to accomplish, or what the strategy underneath the hiring actually is. I’m Vinoo, CEO of Kepler, the deterministic infrastructure for AI. I’ve built pieces of the forward deployed function three times, at three different institutions, over the course of over a decade. Here’s what I’ve seen work, what I’ve seen fail, and where I think this goes. ...

I spoke with Henry Chandonnet at Business Insider about Project Frontline and what companies are getting wrong about forward deployed engineering. The full as-told-to is there. A short version of what I told them. What Project Frontline Actually Was It was a rotation, not a hiring funnel. We took software engineers and put them in front of customers with real support underneath them — dual mentorship, a way back out, and people whose job was to make sure the rotation worked. Around 250 engineers went through it. A lot of them run forward deployed teams now at OpenAI, Anthropic, xAI, and Anduril. ...

Presented at AI Engineer. Most companies hire forward deployed engineers as an extension of go-to-market: a technical body to keep a large account happy. That’s the wrong frame. FDE is a product strategy. The job is to find the real problem, ship the smallest thing that solves it, and turn what you learned into leverage for the product. ...

Most AI projects don’t fail at the model. They fail somewhere between the demo that impressed everyone and the system that has to survive contact with a real customer’s data, workflows, and definitions. I published a new LinkedIn Learning course on the role that closes that gap: Forward Deployed Engineering in the Age of AI. Why This Course Exists AI deployment differs fundamentally from a traditional SaaS rollout. A SaaS product is largely the same on day one for every customer. An AI system is not — its behavior depends on the customer’s data quality, their vocabulary, their edge cases, and their tolerance for being wrong. That means the work of making it succeed happens in the field, not at headquarters. ...

Part of Lenny Rachitsky’s “The AI-Native Product Manager” free workshop series on Maven. Most products fail not because of bad engineering, but because teams build the wrong thing. They either overbuild features nobody asked for or underbuild solutions that miss the real problem. Forward Deployed Engineering (FDE) is the antidote. What is FDE? Forward Deployed Engineering is a methodology where technical teams embed directly with customers to witness how software meets reality. Instead of building from assumptions, FDEs develop customer instinct by being in the field — watching real users interact with real products under real conditions. ...