ep. 93. Companies are sending Forward Deployed Engineers into organizations to study users. Why not send UX Researchers?
Speccing out the Forward Deployed UX Researcher role.
On May 11, OpenAI launched the OpenAI Deployment Company, a subsidiary with more than $4 billion in committed capital from 19 investors, including leading consulting and systems integration firms such as Bain, Capgemini, and McKinsey.
The new venture exists because enterprise AI has stalled at the integration layer despite rising model capability. Closing that gap requires people who can do the implementation work alongside customers.
To that end, OpenAI is embedding Forward Deployed Engineers (FDEs) inside customer organizations to integrate frontier models into existing workflows. Roughly 150 of these FDEs come from Tomoro, a London-based applied AI consultancy OpenAI is acquiring alongside the launch.
This move is part of a larger trend: From January to October 2025, FDE job postings grew 1,165% over the same period in 2024.
By OpenAI’s own description, a typical engagement starts with a diagnostic of where AI can create the most value, followed by a small number of priority workflows selected with the customer’s leadership and operating teams.
Breaking down that list, you have:
Mapping current workflows and collaboration models.
Identifying needs and pain points.
Determining what to automate versus keep human-led.
I just described a UX research skillset.
Next, FDEs work inside the organization to build and test new systems for the team to use in everyday work. As I’ll go on to describe, this part of the role is also within reach (not to mention UX researchers already being experts in evaluation).
Researchers are actively examining how our role evolves as AI changes product development. Companies need people who deeply understand people and workflows to make AI work for their organizations. It’s time we consider the Forward Deployed UX Researcher (FD-UXR).
The FD-UXR Job Description
The core goal of both the FDE and FD-UXR job is: understand users, then change the way they work.
UX researchers already have the core competencies for “understand users” part, such as proficiency in qualitative methods, required to map workflows, identify opportunity areas, and test hypotheses.
The “change the way they work” will need researchers to hone a few new skills centered on implementation.
The Implementation Skillset
An FD-UXR needs to implement what they find.
After they understand how work is done today, they need to identify what needs to change and make that happen. This involves developing the hard skill of building with AI tools, and the soft skill of owning a POV.
Building with AI today means pipelines and agents. The tooling currently looks like agent SDKs (Open AI and Anthropic each have their own), AI coding environments (e.g., Cursor, Claude Code), and evaluation frameworks (e.g., Braintrust, LangSmith). This is what current FDEs know inside and out.
If learning these tools seems unrealistic, consider that many researchers are already building their own agents to automate parts of their own workflow.
AI tools have also significantly lowered the barrier to entry into software development. Yes, you’ll need to extend those skills; learning the basics of software architecture will help. PMs can learn how to build production-level software. Researchers can too.
Some projects will be complex enough the require deeper engineering talent. In that case, the FD-UXR would collaborate with an FDE. Researchers already have strong cross-functional collaboration skills. The collaboration will only strengthen after more hands-on experience building with AI tools.
Then there’s owning a POV about what to build and taking that to implementation. This is the harder shift than learning to build with AI tools. In most organizations, research has become divorced from implementation. The researcher has to influence the team to act on findings; the researcher isn’t acting on the findings themselves.
With FD-UXR, the job moves from observation, to modeling the change in software with the FDE, to iterating, to testing again. You need a point of view about what implementation could look like, not just what the research found. To start cultivating this skill, researchers should:
Stop ending research with recommendations. Start ending it with a working version. Even a rough one. If you observed a workflow, build a prototype of the workflow with AI doing some of it. The prototype doesn’t have to be good. It has to exist. The shift from “here’s what I learned” to “here’s what I built based on what I learned” changes how teams respond to your work and changes how you think while doing it.
Study how things get built, not just how they’re used. Read engineering blogs. Sit in technical design reviews. Ask the engineers you work with to walk you through their architecture decisions. The goal isn’t to become an engineer. It’s to develop intuition about what’s easy, what’s hard, and what’s possible, so your point of view is grounded in the medium you’re working in.
Subject matter expertise. A point of view about what should be built is easier when you can already see the landscape. The FD-UXRs who'll do well have spent years inside their domain, know the stakeholders, and understand how the pieces fit together. For example, if you spent five years as a researcher in e-commerce, you probably have a solid picture of how e-commerce as a system works (the stakeholders, the information flows, the tools, the challenges), and therefore, what can be improved.
A Kind of Homecoming
The FD-UXR role is old wine in new bottles. Kinda.
Sure, we didn’t have AI-powered coding tools until recently. No, we traditionally didn’t build solutions. But we did have anthropologists conducting fieldwork in business contexts for a very long time.
Anthropologists first began working in business during the late 1920s, with landmark research of Lloyd Warner at Western Electric’s Hawthorne Works plant in 1931. Using qualitative methods to study employee interactions, Warner helped establish the field of industrial anthropology, demonstrating that human relations were vital to organizational performance.
This momentum continued. For instance, Social Research, Incorporated, the first management consulting firm to include anthropologists, was founded in 1946 (45 years before IDEO!).
Another important moment in this history was anthropologist Lucy Suchman’s work at Xerox PARC, starting in 1979. One of her best known projects was based on video-recorded office workers (including heavyweight AI researchers like Ron Kaplan and Allen Newell), trying and failing to use a new Xerox copier with an “expert system” interface designed to guide them through tasks. This work informed her 1987 book Plans and Situated Actions, which has become foundational for human-computer interaction.
By the 1990s and early 2000s, the discipline had expanded into three primary fields: organizational anthropology, design anthropology, and the anthropology of marketing and consumer behavior. This era saw anthropologists being hired by major corporations like Xerox, Intel, and Microsoft, and the establishment of dedicated professional venues such as the Ethnographic Praxis in Industry Conference aka EPIC (shameless plug, I’m co-chairing a day-long learning activity, Building with Context, at EPIC 2026 in Chicago).
This is also when you started started seeing the modern UX research role emerge.
Enter UXR
Contextual inquiry, developed at Digital Equipment Corporation in the late 1980s, packaged ethnographic field interviews into a method that didn’t require an anthropology PhD. Design consultancies like IDEO and E-Lab built ethnographic methods into their offerings. Tech companies started hiring “UX researchers” who borrowed from anthropology, cognitive psychology, human factors, and HCI.
The role typically looks like studying users, modeling the work conceptually, and influencing engineers and other product team members to build per our recommendations. Closing this loop would take weeks, at best.
Today, UX research is at an inflection point, after being in a state of ‘reckoning’ for several years. In the 2025 State of User Research survey, 49% of researchers reported that they felt “bad vibes about the future of UXR”, which was a 26-point increase from 2024. Tools like AI-moderated interviews and the allure of dropping customer call transcripts into Claude and calling the process “research” rightfully cause us to question the future of the role.
What if we turn our attention to the barriers AI has lowered for us, providing the conditions to breathe new life into the UX researcher role? You can now observe, model the work in software within hours or days, watch the system operate in situ, and iterate.
Let’s use AI’s accelerant properties to our advantage.
In Closing
If you’re a researcher: Is there a path to propose a FD-UXR role in your company? Do you have FDEs? If so, have a conversation with someone in this role to understand the scope and opportunities. If you’re not already building with AI, try making something (for a starting point, I like the Claude how-to guides on Sid Bharath’s blog; he was one of the guest lecturers for my UX for AI course at UC Berkeley). Next, build out one of your research recommendations.
If you’re an employer: UX researchers’ deep well of expertise is exactly what you need right now to understand organizations. Take a chance and lead. If you already have FDEs, pair a researcher with them on their next engagement. Nobody is hiring for this role yet. Somebody should.
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That’s a wrap 🌯 . More on UX, HCI, and strategy from Sendfull next week!
Honestly, FD-UXR sounds like a great title. The skill-problem alignment is great. I bet pairing engineers with UXR would create 1000% better results.
The case for bridging research and implementation through the FD-UXR role is compelling. I'm curious, how do you see the role potentially addressing pain points that are more organizational or systemic in nature vs tool-based?