Why 95%+ of Startups Get the Forward Deployed Engineer Role Completely Wrong
Startups are rushing to hire Forward Deployed Engineers, driven by the generative AI wave. In most cases, it’s an expensive mistake. The FDE model only works under very specific conditions, and outside of those conditions it destroys value fast. After an internal session at Flybridge with Brian Keohane, a former Palantir FDE, one conclusion stood out:
For the vast majority of startups, hiring an FDE is the wrong strategy, and often a very expensive one.
What an FDE Actually Is
The Forward Deployed Engineer sits at the intersection of product management, software engineering, and strategic consulting. They work directly inside customer workflows, uncovering real operational constraints, organizational dynamics, and architecture-level bottlenecks. Crucially, and unlike a traditional consultant, or Sales Engineer, a great FDE ships production-grade code directly into the customer’s live environment.
A great FDE doesn’t just understand the customer deeply; they educate the customer, help them articulate latent problems, bridge the knowledge gap between “what they think they need” and what the technology their company offers can actually unlock, and often reveal entirely new ways of operating that the customer hadn't considered.
Think of an FDE as a product discovery loop embodied as a person:
They map the customers workflow, including the hidden logic behind why each step exists
They surface hidden constraints — technical, organizational, and process-level.
They educate and align stakeholders, turning ambiguous needs into crisp problem statements.
They build “gravel road” solutions that deliver immediate, measurable outcomes.
They expose customers to new possibilities by showing what the product could unlock.
They feed the patterns back to HQ, where product teams harden them into reusable features for other customers.
This blend of technical fluency, ownership, and first-principles thinking, explains why so many former FDEs become founders, including: Tarek Mansour (Kalshi), Alex Arjun (Outake), Glen Takahashi (Hex), Alex Atallah (Open Router), Dara Ladjevardian (Delphi), Quinn Slack (Sourcegraph), Deep Singhvi (Fern), and Matt Grimm (Anduril).
Where Most Startups Go Wrong
The FDE model only works when there is real leverage, and expansion potential both in contract value and in reusable IP. If you cannot see a path from a fifty thousand dollar pilot to a seven figure contract, and if the work done in the field does not compound into the core product, the economics argument collapses fast.
The biggest mistake founders make is deploying FDEs into low ACV accounts with limited expansion potential. In these situations, the customer problem is usually simple and the workflow is already well understood. The FDE ends up doing work a strong customer success or solutions engineer could handle at one-third the cost. Fully loaded, an FDE hire often runs $220k to $400k per year when you factor salary, equity, and benefits. If that person spends most of their time on sub-$100k accounts, the unit economics collapse almost immediately.
A second failure mode is using FDEs to compensate for a weak or immature platform. When the core product is not modular or robust, the FDE gets pulled into building one-off, brittle systems for each customer. None of that work generalizes, and feeds back into the general product. Over time, the team accumulates fragmented deployments and the company drifts into a high effort, non scalable, low margin business.
If you are considering hiring an FDE, your product and market space should meet the following criteria:
Problem is Complex / Workflows are Ambiguous: The customer problem is not easily defined, and the optimal solution is not obvious, requiring deep immersion into unique or complex operations to understand.
High visibility for expansion: You can articulate a credible path to a seven figure ACV and multiple workflows.
Work is Productizable: Part of the solutions built in the field must be generalized and fed back into the core platform.
A Strong, Modular Platform: Your product needs to be sturdy enough that FDEs do not spend their time patching foundational gaps.
The Traits of a World Class FDE
For the 5 percent of companies where the model makes sense, the profile of a great FDE looks remarkably consistent:
High ownership and grit: The number one correlation with success. They have a founder's commitment to the outcome, treating the customer workflow as their own product, and doing whatever it takes to make the production system run.
Technical Fluency plus executive communication: They can write production grade code while simultaneously leading a boardroom presentation and translating technical constraints for non-technical stakeholders.
Bias for action over analysis: They prioritize shipping working systems ("gravel road" solutions) that deliver value fast and reveal deeper product truths, rather than engaging in endless analysis.
Comfort with ambiguity: They thrive in messy, underspecified environments where the real problem is still hidden. They reason in second and third-order effects.
Curiosity & empathy: They listen, infer, and ask precise questions that surface buried constraints.
The Bottom Line
The FDE model is misunderstood and misapplied. In our view, 95 percent of startups hiring for this role are executing the wrong strategy, usually as a crutch for weak product market fit, fragile platforms, or low value deployments.
But for the startups where the conditions are right, where complex problems meet high ACVs and productizable insights, the FDE becomes one of the highest leverage hires you can make. They accelerate discovery, expand accounts, and feed patterns directly into a scalable platform.
If you are a forward deployed engineer considering starting a company, or a founder thinking about whether this model fits your GTM strategy, I would love to talk.
daniel@flybridge.com
