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Published: 2026-09-03 20:43:48 Views: 1835

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Do companies really need a separate FDE role? The author argues that the essence of the FDE is eliminating requirement translation, and that in the AI era the division of labor between business and IT will be restructured, overturning conventional wisdom. Key points: 1. The FDE's essence is eliminating requirement translation; with AI, business people can write programs directly. 2. IT's new role: shifting from development to decisions on toolchains, permissions, etc., preventing siloed systems. 3. No separate role needed: FDE capabilities already exist among current business/IT staff.

Yang Fangxian

Founder of 53AI / Most Valuable Expert of Tencent Cloud (TVP)

Some companies have already started hiring, and the job requirements all look about the same—understand the business, master VibeCoding, deliver independently. By these criteria, many have been hiring for months without success.

My previous article, "FDE Is the Collective Deathbed Fantasy of Chinese Software Companies," drew a huge response. Some said the title was sensationalist, but the content was a very rational discussion of the value of the FDE on the vendor side. In this piece, we'll continue the discussion with the FDE on the client side.

(FDE stands for Forward Deployed Engineer, a practice pioneered by Palantir: sending people who understand the business and can write code themselves to work on-site at the customer, completing system implementation directly without passing through layers of product managers and developers.)

These are my personal views; discussion is welcome—debate brings clarity:

On the surface we're discussing a headcount question, but the essence is: once AI levels the barriers for many things, how should a company redivide its work? In my view, the FDE role doesn't need to be created. Not because it's unimportant, but because the person you're looking for is already in your company.

Here are three points—some are predictions, some are already happening:

There are many definitions of the FDE in the industry—understands the business, can code, can handle the front lines, can make decisions on the spot. Traditional implementation consultants need all of these too; nothing new there. The only thing that truly distinguishes the FDE from traditional implementation is: eliminating translation.

How is a classic enterprise system built? The full process is: the boss proposes an idea → business raises requirements → product manager/consultant designs → UX/algorithms/engineering development/data development takes over → testing, with a project manager coordinating throughout, in continuous cycles.

Every layer is a translation. And with each translation, some of the most critical information may get lost.

The ideal FDE, in essence, compresses this chain into a single such "superhuman."

So within an enterprise, who is the person with the shortest requirements chain?

It's the business person themselves. They don't need to explain the requirements to anyone else—they are the requirements.

In the past they couldn't do it because software itself is an extremely complex engineering effort; it was impossible for business people to build it themselves. In the future, they only need to explain one thing clearly—to the AI.

The judgment behind this is: teaching business people to use AI to write programs is far easier than teaching IT people to understand the business and become business experts.

When I state this point, many IT folks are already drawing their knives.

This is the most frequently asked question, and the one most easily misunderstood as "IT being sidelined." It's actually the opposite.

In the past, IT's power came from "only I can do it." Now the source of power has become "only I can decide how this is done"—which toolchain to use, how data connects, where permissions are granted, what kind of output can go to production.

That's far more power than "I'll develop it for you." Because what it governs isn't the scheduling of a few requirements, but everyone's boundaries.

And it guards against exactly what CIOs fear most: business departments bypassing IT to do their own thing, each building their own, ending up with a pile of disconnected silos—and IT still having to clean up the mess.

I know quite a few companies that provide workbuddy and claudecode to all employees. It often happens that after a business person builds a small tool themselves, they come to IT asking IT to help deploy it.

Once, during a visit to a star hardware company for an exchange, when I was presenting our promotional simulation tool, the other side's business lead turned to a colleague and whispered—"Have Claude make me one tonight" (I wasn't surprised, and I think it's quite reasonable; it's a trend we must embrace).

This will only happen more and more, and IT can't stop it.

The business side will say: "I've already built this feature myself. You didn't have time to develop it for me, and now you won't even help me deploy it?"

So the question was never "whether to allow it," but how to regulate it: what the process should be, which tech stack to use, where the boundaries of security and permissions lie, what can go to production.

The real choice isn't "whether to let the business do it themselves"—they're already doing it. It's whether to give them a path within the governance framework.

IT must transform from the "translator" between requirements and programs into the provider of AI tools, the rule-maker, and the governor. This transformation is essentially what many people call the enterprise's internal AI organizational upgrade. In this process, IT certainly needs people who are both proficient in AI and understand some business—this role could be the CIO themselves, or an architect: they don't produce business systems; they produce rules and tools. Or, for a transitional period, bringing in outside help is fine too.

IT needs to build this mechanism, but where do the standards come from? What counts as compliant, what can go to production, which data can be given to whom—these judgments themselves require business knowledge.

If decided purely by gut feeling, the rules will most likely be too strict. Then the business side finds they can't do anything, turns around and bypasses it all to do their own thing, and the mechanism is built in vain.

So a more accurate statement is: get the mechanism running first, then revise it version by version.

The first version will definitely be rough, even wrong.

I think this point is more important than the mechanism itself, because what it tests isn't technology but the organization's tolerance. Many companies get stuck right here: the first version looks ugly, someone immediately jumps out and says "See, I told you it wouldn't work," and then nothing more happens. This kind of thing isn't designed in a meeting room and then pushed down. You have to allow it to grow a bit slower and a bit uglier.

Additionally, I believe that in the future, within this mechanism, every company will develop a set of tools:

I call this kind of thing an in-house harness—the generic harness is the skeleton, and the rules each company installs into it are their own. This ensures that within a client enterprise, business knowledge is continuously accumulated over time, iterated in a loop, and efficiently invoked, so the business can be supported through AI faster.

1. Business people are already the FDE; no separate role is needed.

2. IT doesn't translate; it governs and builds tools.

3. Get the mechanism running first, then revise it—it's fine if the first version is a bit ugly.

In actual practice, there are far more details than the above—what the framework should and shouldn't constrain, how to guide business people, how to keep knowledge and tools continuously iterating. We ourselves are exploring these together with several deeply partnered enterprises.

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