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ES Evangelos Simoudis On The Data Exchange with Ben Lorica

“During experimentation there is a lot of switching between models and between tools. But once you start moving to deployment and making decisions, the switching, whether at the model level or the application level, goes away, because the enterprise cannot afford it. Be very difficult then to dislodge them, and we've seen it over the years in information technology. And that then becomes their moat.”

The Data Exchange with Ben Lorica · AI Research & Frontier Labs · October 2026

“During experimentation there is a lot of switching between models and between tools. But once you start moving to deployment and making decisions, the switching, whether at the model level or the application level, goes away, because the enterprise cannot afford it. Be very difficult then to dislodge them, and we've seen it over the years in information technology. And that then becomes their moat.” — Evangelos Simoudis, The Data Exchange with Ben Lorica

Context

The host said people seem to settle on one coding tool and rarely leave it. The guest distinguishes experimenting from deploying, as his answer to what a model lab's moat actually is.

Transcript

The Data Exchange with Ben Lorica Around 19:28 into the episode
Evangelos Simoudis

…accident or if it was deliberate, but it was a brilliant product market fit. And that has allowed not only Anthropic, but also other companies to be successful. Identifying additional such use cases will be very important for the future. Otherwise, I think we will see some very unexpected outcomes.

Ben Lorica

…well, right? So I happen to use open code with open routers, so Impressive. Can switch models. But the general impression I get is that most people settle on cloud code and maybe, you know, they don't really move off of it quite as easily as I would think. But that's just anecdotal data on my part.

Evangelos Simoudis

Actually, I would say I would put it both during experimentation. I mean, if you look at enterprises that are experimenting with AI, and most of them do, including many of these 12,000 that they list as customers. And during that phase, there is a lot of switching between models, between tools. But once you start moving forward and you start going to deployment, you're making some decisions, then the switching, whether it is at the model level or the application level, goes away. Because the enterprise cannot afford it, right? So this is something that I think this old bianthropic and these consulting partnerships that they have could be extremely beneficial for them because if an organization adopts for real their tools, it will be a good idea. Be very difficult then, and we've seen it over the years in information technology. It will be very difficult to dislodge them. And that then becomes their note.

Ben Lorica

There is one upcoming trend which will happen in the next few months, early next year, probably. It's that a lot of people are working on shared memory, shared contexts, right? So, one of the things is that when you use a coding tool, then and then you try to switch to another, then you lose a lot…

Evangelos Simoudis

of the context, that's right.

Ben Lorica

A lot of context and memory. But a lot of people have noticed this and are upset about it. So, I know of at least one open source project that I've actually been quite impressed on who are going to release something early next year. And this will solve your switching costs, I think.

Speaker names come from our own diarization. The position is estimated from where the line sits in the episode.

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