“I always laugh at the IT industry’s terms,” says Ryan Sheehan, a senior vice president at $16 billion global solutions integrator SHI. And right now the jargon that gets him giggling is “forward-deployed engineer” (FDE) because, as he told The Register at VMware's September Explore conference, “We have been doing FDE for a long time.” “Doing FDE” involves sending top consultants to a client, without tying them to a project. Instead they get a mission to build something valuable using new technology, and carte blanche to make that happen in a hurry. Sheehan has company in believing FDEs aren’t fundamentally new. Cloud monitoring vendor DoIT told The Register it has used FDEs since 2011, but only started using the term in the last quarter of 2025, when it changed the name of its “Customer Reliability Engineering” practice to FDE. That decision came as services companies adopted the term FDE to describe the work needed to build AI proofs of concept. The name has its origins at Palantir, whose chief technology officer Shyam Sankar claims he coined it in 2007 after a conversation in which his CEO Alex Karp asked him why French restaurants are so good. Karp apparently answered his own question by saying, “The wait staff is actually part of the kitchen staff. They intimately understand the food, the methodology, and the technique. They are not merely carrying the food from the kitchen to the table, but are instead part of a subtle and complex system that affects kitchen operations.” Sankar says Karp asked him “to build that, but for engineering” so he did and called it “forward deployed engineering.” “FDEs embed alongside our customers and work to ensure our software solves their problem and not some proxy for their problem,” Sankar wrote on his personal Substack. “They’re crazy enough to get on a last-minute plane to Iraq, they’re smart enough to ship quality, same-day code, and their EQ is still high enough to talk to users (and maybe even enjoy it).” Sankar says Palantir’s investors thought FDEs were a bad idea because the costs they incurred ate into margins, but says they’re worth it because they ensure customers understand the company’s products and how to get value from them. “We didn’t believe in throwing our software over the wall in the hopes the customer would divine the correct meaning from it,” Shankar wrote. “This approach built an engineering organization with unmatched creativity, responsiveness, and focus on the primacy of winning.” AWS likes winning, too, and in June announced a dedicated AWS FDE organization, and $1 billion to fund it. In July Microsoft trumped that with a $2.5 billion so-called “Frontier Company” it claims “goes beyond” FDEs. Both companies see FDEs as a way to get their consultants into customers to help them build AI apps. They argue FDEs’ time has come because, as Palantir found when users struggled to put its software to work, organizations often struggle to turn AI experiments into production applications. Stop us if you've heard this one before But vendors also admit that FDEs aren’t entirely new. Indeed, AWS told The Register it has offered customers something very similar to an FDE for years. “We started this journey all the way back in 2017 when the focus was machine learning (ML),” said Taimur Rashid, the cloud giant’s managing director for go to market, Frontier AI Engineering & Services. “We created a team called the ML Solutions Lab. The idea was that the tech is new, customers need to navigate it. So we said ‘Why don’t we loan them a data scientist?’ They can build a PoC, and the customer can build on our platform.” Rashid says AWS sometimes called this sort of arrangement a “secondment,” a “resident architect” or a “resident scientist.” Whatever you call it, Rashid said the approach worked well so AWS decided to evolve it when generative AI burst onto the scene – this time using an applied scientist and a strategist, and an evolved approach. “We forward-deploy them – they will help to identify the art of the possible and develop the solution for you or with you,” Rashid explained. “They will be part of your business and operational workflows, and effectively be yours for a defined time,” he said. That’s different to conventional services engagements, he argues, because there’s no scope of work, no hourly charge for consultants’ services. “What is different about FDE is you are saying the customer wants to build. The path is not determined.” Carlos Pereira, a Fellow and Chief Architect in Cisco’s Customer Experience team, also admited FDEs aren’t entirely new, but argued AI makes them more valuable than conventional consultants. "The idea of an expert being embedded on-site to help a customer adopt new technology and solutions isn't new,” he told The Register by email. “Our Customer Success organization has been doing this for years.” “The evolution is that AI is now a key part of that equation,” he added. “It introduces new variables like non-deterministic AI models, evaluations, faster-moving requirements, and specialized skills that not every customer team has in-house.” Analyst firms Gartner and Forrester agree that FDEs can be useful, and that this form of IT services differs due to greater intimacy between client and consultant. “They often have full-stack access to the customer’s environment and the vendor’s codebase, allowing them to build and iterate in real time,” Gartner’s Arun Chandrasekaran and Robert Thanaraj wrote in March guidance titled “An AI Leader’s Guide to Forward Deployed Engineering to Scale AI.” A June best practice report from five Forrester analysts, titled “Forward-Deployed Engineers: Use provider-embedded builders to improve outcomes,” praises the model for helping to “accelerate adoption and turn complex platforms into production-ready outcomes.” Yet both analyst firms also warn that using FDEs may see clients develop a dependency on the vendor that provides them. “The allure of delivering outcomes at speed can induce blind spots and is fraught with risks,” according to Forrester. “Without the appropriate guardrails on tech architecture and stack choices, teams can fall into a bespoke trap, where highly tailored solutions deepen vendor dependence and make future change costly.” Debt and dependency Gartner urges would-be hirers of FDEs to “beware of ill-conceived FDE engagements that can lead to a high degree of vendor dependency, security/data risk exposure, technical debt, and talent atrophy.” The latter happens when organizations hire FDEs but don’t train their own teams on new tech. “Your internal team may become operators of a black box rather than architects, making it difficult to innovate without the vendor,” Gartner warns. Gartner also worries FDEs can be a fast-track to technical debt. “A major concern with the FDE model is that it relies heavily on manually designed structures and hard-coded domain knowledge. Such human-engineered components tend to deliver short-term gains but are repeatedly superseded as more general, scalable learning systems improve.” “As large language models continue to advance, much of this manually encoded logic is likely to be rendered obsolete, requiring costly rework or full redesign, and creating a long-term technical and organizational burden.” FDEs themselves may soon be obsolete, because they’re not vendors’ only bet on improving AI consultancy skills, according to Omdia chief analyst Jay McBain. “At the same time as investing in FDEs, the big players have been investing big into partner enablement,” he told The Register. “They are playing both ends.” The tech services channel doesn’t mind that, because according to Omdia data 82 percent of partners report they “aren’t ready” to quickly grow their AI services. The vendors promoting FDEs, meanwhile, don’t want to use this form of consultancy for long. “None of these companies’ investors want to dilute a low-value services business into the overall revenue,” McBain wrote. “We are predicting all of this FDE investment will fall back into the channel by 2031 when this matures.” Which rather suggests that in a few years we’ll all be laughing at how Palantir re-heated an old form of tech services under a new name, and the rest of the industry decided to follow the same recipe. ®
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