Real Alpha
Watch modeSubscribed

Latent Space · 2 min · Oct 22, 2026

Modal’s FDEs turn customer work into product features

Erik Bernhardsson

CEO, Modal

  • Shawn Wang (swyx)Host · Co-founder, AI Engineer

    Wrote “The Rise of the AI Engineer” and founded Smol AI, maker of AI News.

  • Alessio FanelliHost · Founder, Kernel Labs

    Partner at Decibel, backing technical founders who build developer tools.

About this segment

Modal grew its forward-deployed engineering team from four to about 24 in a year. Erik says their key role is turning customer-specific work into product features.

From “Why AI Compute Comes in Rectangles — Erik Bernhardsson, Modal”, Oct 22, 2026. Watch the full episode

“we started this year having like four fdes now i think we have like 24 or something like that”
Erik Bernhardssonat 58:08 · Latent Space58:08

Takeaways

  1. The FDE team grew from four to about 24 in a year.
  2. FDEs tune inference, help lower customer bills, and support migrations.
  3. Customer-specific fixes should eventually become self-serve features.
Watch 2:09 from 57:44

In this episode

Full episode
  1. 15:24Renting GPUs avoids some risks but creates long-term exposure5:57
  2. 28:18Neoclouds scale by pre-selling GPU capacity3:40
  3. 43:26Snapshotting can make massive test parallelism practical3:26
  4. 31:56Modal’s sandbox product grew from a small experiment to a third of revenue4:10
  5. 7:38A Stable Diffusion customer brought Modal its first meaningful revenue2:55
  6. 21:49Modal qualifies GPU vendors with specs, tests, and support history2:32
  7. 52:48Agent training data makes old APIs harder to retire4:25

  8. 57:44Modal’s FDEs turn customer work into product features2:09

Up next · The Knowledge ProjectA venture reset is coming, so founders should hoard runway3:51

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

  1. 57:51

    you guys hire like forward deployed engineers like what do you do we're in a new era of like building applications and and and you know things that we couldn't build you know just a few years ago and we see a lot of companies that you know they need a little bit of help right like you know and so we started investing in fdes a couple years ago but it but it's really been this year we've kind of scaled it up a lot i think we started this year having like four fdes now i think we have like 24 or something like that so we've grown it a lot and they do it you know it's more it's not exactly the pound term model but they do a lot of like heavy you know sort of customer engagement like they work with a lot of customers on performance tuning especially with lms we see that there's so much benefit from like you know sitting down with customers and training draft

  2. 58:36

    models and tweaking uh you know the parameters and dlm and sglang um they often you know fix bugs or not fixed bugs, but when customers run into issues, they often work with customers trying to figure out how do we work around that. Another thing we've used FDs a lot for is kind of proactively, if we see certain customers over-provisioning with modal, like customers requesting too much CPU or too much memory, for instance, that's kind of expensive.

  3. 59:05

    And we try to catch those things and we try to sit down with those customers like, yo, you're spending a lot of money on modal right now, we can actually help you save money. And then, of course, with active deals, we help them migrate code from other platforms, things like that. I think we never have the intention of becoming a service-heavy business. I think the goal for FDs is A, is to be part of the sales process and closing deals.

  4. 59:34

    B, is to serve customers and do some customer support. but like i actually think like the most important thing is like c it's like bridging gaps in the product that we later want to turn into like real features so i think to a large extent you know