⚡️ Ship AI recap: Agents, Workflows, and Python — w/ Vercel CTO Malte Ubl
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What is Vercel’s overall AI‑engineering philosophy and why does it matter?
All right, we are here in the remote studio. Thanks again to F dot Inc for lending us the space with Malta Ubo, who's CTO of Verseel. Welcome. Hey, how's it going? Glad to be here. Did I get it right Ubo? I've actually never pronounced it out loud until like just now.
Yeah, I was completely perfect. It's Ryan's just Google.
Ah, okay. Uh so perfect that you uh worked on search at Google and AMP and Wiz, which like I I think still people don't know enough about Wiz.
It is like no longer a secret, but yeah, you can't use it, so like unless you work at Google, in which case you probably know what it is. Otherwise uh there's no reason to really know.
Anyway, suffice to say that you are responsible for a lot of the web as it is today. So thank you for spending some time with us. You're also obviously now uh building the next web, as as we say, with uh Vercel. And we we we can cover framework defined infrastructure. I I think y you probably saw I have a I have a lot of interest in self provisioning runtimes. Uh we can cover V Zero, but here really this part is is recorded right after you did Ship AI. Which uh we're trying to sort of recap, right, for uh the general uh Lane Space audience who may not be watching Vercel as closely as uh I do or or uh you do. So like so b basically just generally, what I guess is your message to the broader AI engineer audience on what Vercel is doing with AI?
Yeah, I think the the
the super high level view is that what we're really trying to do is like we we're like the biggest fan of the AI engineering movement and we are also fans of, you know, we're not not just like going super hard on on hype and the big ideas and and talking about things, but like v being very concrete about like, you know, agents are very exciting and you can actually build them. Right. And so like I think our entire conference was about both making that easier, right? And and discovering the right abstractions as we're kind of figuring out what the what people actually want to do, right? Which is emerging as we speak. Then the way Vercel always does these things is by building things ourselves, right?
And so that is both in terms of products. So agents that are products that you can purchase from Vercel and stuff that we do basically in our back office to make our own operations more efficient. And so this kind of building of apps lets us ground kind of what we do in in that reality and then and then extract the abstractions that we feel are really helpful to to then put that on the road. And I think the the probably most talked about thing that we shipped at the at the conference was our new workflow development kit. Which really really is just uh way to make writing uh like workflows like very idiomatic as something that just becomes kind of first class is something you do every day. You think about it, you know, write 15 design docs just because you want one of them.
It's just something you do literally every day. I think like since you are your audience also more generally like in the thing probably like listening to what people talk about, I think that's where I've talked about our virtual development kit, but also like more generally like what is what are we workflows, what are agents, how are they related? Do you use one or the other? I would actually love to talk about that as well. But like um obviously like in our in our uh conference we basically introduced just like what we hope is by far the easiest way to make your You know, make your agents something that is easily embeddable into complex workflows and to make those workflows durable, zoomable, streamable and so forth.
Yeah, I mean, as as listeners might know, I have a long history of uh workflows um at at temporal. Um and I think what's weird is a lot of people are discovering this for the first time. You don't really learn about this in CS classes, you don't really learn about this in like boot camps or anything like that, because it's not really a unit of compute and storage that is taught. It's kind of like emergent from you know, Uber and like Stripe and and everyone else.
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Chapters
8 chapters
1
What is Vercel’s overall AI‑engineering philosophy and why does it matter?
0:03–5:44
2
How do Vercel’s Workflows differ from Agents and why are durable serverless functions important?
5:44–10:55
3
What lessons did the AI SDK 6.0 launch teach about low‑level, humble abstractions?
10:55–15:37
4
How does the Vercel DevOps Agent automatically detect and investigate production anomalies?
15:37–21:07
5
Which internal agent use‑cases (lead qualification, abuse analysis, data analyst) have shown the biggest impact?
21:07–26:09
6
What is the “Agent on Every Desk” program and how can companies start building their first production agents?
26:09–31:28
7
Why is native Python support (Flask, FastAPI, zero‑config deployment) a game‑changer for Vercel?
31:28–36:54
8
How is Vercel addressing AI‑native security and the future of trustworthy AI‑coded applications?
36:54–41:48
Speakers
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