The elephant in the room?

​@itsmatt You’re not wrong about the shift—but you’re probably overcorrecting on what it means.

What you’re feeling is real: tools like Claude Code and Microsoft Copilot collapse a lot of “glue work” into fast, disposable code. That absolutely eats into the kind of ad-hoc, one-off workflows where FME used to shine. If your mental model of FME is “a faster way to script transformations,” then yes—AI agents are now competing directly with it.

But here’s the part that doesn’t hold up: the idea that this makes FME obsolete or that you’re heading toward irrelevance.

Where your argument is right

• Speed of prototyping has flipped
  AI agents are brutally efficient at “just do it” tasks. Writing Python + pandas + some spatial libs is often faster than assembling a workspace from scratch.
• Barrier to entry is collapsing
  Junior or non-technical users can now automate things that used to require an FME specialist. That will reduce demand for certain kinds of FME work.
• Cognitive shift
  You’re no longer rewarded for solving every small problem manually. That’s a real psychological loss if you used to enjoy that craftsmanship.

Where it breaks down

FME was never only just about speed—it was about reliability, transparency, and operationalization.

AI-generated scripts:

• drift over time
• lack clear lineage
• are hard to audit for now
• break silently in production for now

FME (especially with Flow) gives you:

• visual lineage (huge in enterprise + GIS contexts)
• repeatability and scheduling
• data governance compatibility
• team readability (not everyone reads Python well, even now)

AI is amazing at creating solutions. FME is still very strong at running them safely at scale.

The real shift (this is the important part)

You’re not being replaced—you’re being pushed up the stack.

The old role:

“Build the workflow”

The new role:

“Decide what should exist, validate it, and make it production-safe”

AI can generate 80% of a pipeline. But:

• Who ensures it handles edge cases?
• Who integrates it into existing systems?
• Who owns failures at 3 AM?

That’s still a human with experience—someone like you.

Why FME feels slow now

Because you’re comparing:

• AI → instant, disposable output
  vs
• FME → structured, production-ready workflows

That’s not a fair comparison. It’s like comparing a sketch to a building.

The real risk (and it’s not what you think)

The danger isn’t “FME dies.”

It’s:

You stay in “tool operator mode” while the world moves to “system designer with AI leverage.”

If you only define yourself as “the FME person,” then yes—that niche shrinks.

If you redefine yourself as:

• data workflow architect
• automation strategist
• AI-augmented problem solver

then you’re in a stronger position than most devs, because you already understand data pipelines deeply.

What would actually make us safer (practically)

• Lean into Python—not instead of FME, but alongside it
• Treat AI as your default builder, FME as your production layer
• Get comfortable reviewing and validating AI-generated code (this becomes a core skill)
• Think in systems, not tools

About your “FME agent” idea

You’re absolutely right:

An AI that can operate FME directly would be powerful.

That’s likely where things go:

• AI generating workspaces
• AI debugging them
• AI iterating inside tools like FME Flow

If that happens, FME doesn’t disappear—it becomes a backend execution engine.

Bottom line

You’re not imagining the disruption—but you’re aiming your fear at the wrong target.

AI didn’t just make coding easier.
It made building anything easier.

That doesn’t eliminate experienced people—it raises the bar for what “valuable” work looks like.

If you adapt, your 15 years of experience becomes more valuable, not less.

If you don’t, then yeah—it starts to feel like the walls are closing in.

P.S: I would not claim that these are my two cents! 

Happy FME:-) ing

SRG

​@itsmatt Thanks for putting into writing what I think is on a lot of peoples mind these days. 

I don’t think “FME is the new Cobol” just yet ;-) But I hear your arguments and we’ve had internal discussions in the same vein. It’s an interesting challenge, in particular when presenting FME to potential clients with more technical expertise than budget.

While you can definitely replace some workspaces with vibe-coded software, you’ll still face some very real challenges down the road. And for now I believe the longer the road, the bigger the challenges. Some of my own lessons learned include:

• There’s a real lack of predicitability in how AI handles edge cases (unless you’ve specifically planned for them) and no knowledge about the business aspects which a human developer would often take for granted
• As there is no collective memory of existing processes, AI tends to re-invent the wheel each time, sometimes with subtle and non-trivial changes in behavior. Just something as simple as establishing a parametrized database connection can be deceptively tricky and might be implemented in hundreds of ways. Which one will your AI coding agent use today?
• To avoid creating too much of a mess and getting predictable results, you still need the mindset and some experience as a software developer, unless the task is trivial. Blindly trusting the results of AI is a recipe for problems than can be very difficult to resolve. A software developer might know a lot about coding, but does he also have deep domain knowledge about your GIS business workflows? FME empowers those with domain knowledge.
• FME is more than Form, and re-implementing the functionality of Flow using vibe-coded software, for it to run other vibe-coded software components, would still be a massive undertaking with a lot of risk. Yes, there are solutions like Airflow out there, but the barrier of entry is substantial, even with AI as support. Speaking of support, Safe is really in a league of its own.
• Quality testing is critical and time-consuming, and cannot be fully solved using AI-generated unit tests alone.

This is not to say that AI-generated coding does not solve real problems, but for the time being we are a long way away from saying it can fully replace established platforms like FME other than for relatively simple and isolated tasks. And, honestly, acquiring FME for only such use-cases is probably overkill anyway.

Regarding having proper AI skills to author and reason about workspaces, I believe that is something Safe is actively working on, and that would absolutely be a killer feature. I sincerely hope Safe can close this gap as soon as possible.

What I see in the meantime, is that the co-existence of established software like FME and custom scripts is increasingly important. To stave off the vibe coders, I believe FME could quickly gain a lot by improved integration with external workflows, in particular in the Flow ecosystem, already ideal for orchestration. There’s some really simple stuff that could be done to meaningfully improve how the FME platform co-exists with custom scripts, e.g. everything related to the SystemCaller:

In my opinion this is low-hanging fruit that would help proponents of vibe-coding to not see FME as competition, but as complementary.

My colleagues are slowly discovering these tools as well and can do a lot more themselves with AI, soon they wont need an FME guy to automate stuff

I think this is the scary bit tbh.  As they say, you don’t know what you don’t know. I look forward to finding more excel spreadsheets with latitude and longitudes that have been converted from British National Grid via an unknown transformation online. And that’s assuming they’ve got the x & y the right way round in the first place!

I don’t actually have any experience of using AI in FME as the environment i’m currently working in doesn’t have access to AI assist but I’ve been very disappointed with all the questions FME related I’ve asked other AI systems so far.  

How much of the work that you are talking about is spatial?