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The Cognitive Revolution / episode intelligence

The Model Eats the Scaffolding: DeepMind's Logan Kilpatrick & Tulsee Doshi on 3.5 Flash, Omni & More

20 May 2026 23 published claims 3 attributable people
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Speakers in the public record

Logan KilpatrickTulsee DoshiNathan Labenz

Claim mix

belief 10evaluation 6prediction 3commitment 2uncertainty 2

Evidence policy

Every row below preserves an exact excerpt. Identified speakers are linked; unresolved voices are labeled and excluded from people counts.

Claim ledger

The useful parts, with receipts.

23 published records

01 / belief

I think obviously the model that the actual audio model was really good as well, but like the prompt dialogue was really difficult for them to pull off and they pulled it off in an incredible way and I think helped people fall in love with that product.

“I think obviously the model that the actual audio model was really good as well, but like the prompt dialogue was really difficult for them to pull off and they pulled it off in an incredible way and I think helped people fall in love with that product.”
Publisher
The Cognitive Revolution

03 / uncertainty

One thing that I recall, I don't know if it was 2 IOs ago or whatever, right, but there was going to be 3 sizes of Gemini model at one point in time.

“One thing that I recall, I don't know if it was 2 IOs ago or whatever, right, but there was going to be 3 sizes of Gemini model at one point in time.”
Speaker
Nathan Labenz
Publisher
The Cognitive Revolution

04 / belief

Like it's not like in the context window of any large major LLMs is like, here's the details of how you're being trained and here's sort of your serving set up and here are the people who are working on it though maybe like these are interesting things to experiment with in the future. So I think a lot of it is just like pulling out of random distribution of like the large scale, training that happens on the models.

“Like it's not like in the context window of any large major LLMs is like, here's the details of how you're being trained and here's sort of your serving set up and here are the people who are working on it though maybe like these are interesting things to experiment with in the future. So I think a lot of it is just like pulling out of random distribution of like the large scale, training that happens on the models.”
Publisher
The Cognitive Revolution

05 / belief

I think the two things that I'll add is, and there's like probably a more nuanced technical story on sort of like the ultra thread, but it's not like, it's also not like the pro models haven't scaled up over time.

“I think the two things that I'll add is, and there's like probably a more nuanced technical story on sort of like the ultra thread, but it's not like, it's also not like the pro models haven't scaled up over time.”
Publisher
The Cognitive Revolution

06 / uncertainty

Is it going to be available via the API and is it going to be I've noticed with, I mean, Gemini's been the only API that's accepted video for a while now, but I don't know exactly how it works under the hood, obviously, but I do feel that it's sort of kind of down-sampled, or maybe there's like frames taken out of it historically.

“Is it going to be available via the API and is it going to be I've noticed with, I mean, Gemini's been the only API that's accepted video for a while now, but I don't know exactly how it works under the hood, obviously, but I do feel that it's sort of kind of down-sampled, or maybe there's like frames taken out of it historically.”
Speaker
Nathan Labenz
Publisher
The Cognitive Revolution

07 / belief

I think then it was Gemini and then sort of all of a sudden every Google product has Gemini and sort of getting them all stitched together and making all those products experiences great. And I think now you're seeing that again with the anti-gravity agent harness and sort of as products become agentic by default, you now have the anti-gravity agent harness being another through line through all of our products.

“I think then it was Gemini and then sort of all of a sudden every Google product has Gemini and sort of getting them all stitched together and making all those products experiences great. And I think now you're seeing that again with the anti-gravity agent harness and sort of as products become agentic by default, you now have the anti-gravity agent harness being another through line through all of our products.”
Publisher
The Cognitive Revolution

08 / belief

Yeah, and I think actually also to re-articulate a point that Tulsi made, like Google and specifically Google DeepMind's mission is to like build AI responsibly and make sure it benefits like all of humanity.

“Yeah, and I think actually also to re-articulate a point that Tulsi made, like Google and specifically Google DeepMind's mission is to like build AI responsibly and make sure it benefits like all of humanity.”
Publisher
The Cognitive Revolution

09 / belief

I would say, as I'm sure you're well aware, like commentary on Google's AI integrations across its vast product suite has been that it is characterized by like some bangers and then there have been some which have been characterized as misses.

“I would say, as I'm sure you're well aware, like commentary on Google's AI integrations across its vast product suite has been that it is characterized by like some bangers and then there have been some which have been characterized as misses.”
Speaker
Nathan Labenz
Publisher
The Cognitive Revolution

11 / belief

In fact, it's actually so fast that like sometimes in anti-gravity, like by the time I want to cancel, like it's too late. And so I think like we already are like, I think trying to figure out where do you start getting to Logan's point a different answer, like the diminishing returns and where do you see that value proposition is I think part of the question too.

“In fact, it's actually so fast that like sometimes in anti-gravity, like by the time I want to cancel, like it's too late. And so I think like we already are like, I think trying to figure out where do you start getting to Logan's point a different answer, like the diminishing returns and where do you see that value proposition is I think part of the question too.”
Speaker
Tulsee Doshi
Publisher
The Cognitive Revolution

12 / belief

I feel like that was also, obviously there was the application where you could sort of test it last year at IO, but I think the framing was like, we're doing interesting research.

“I feel like that was also, obviously there was the application where you could sort of test it last year at IO, but I think the framing was like, we're doing interesting research.”
Publisher
The Cognitive Revolution

13 / belief

The models are built with sort of that use case in mind. And I think for some portion of enterprise customers, they want flexibility in sort of like their external search tooling providers and sort of Google Cloud's doing their job as a great enterprise business of sort of partnering and finding the right folks to work with.

“The models are built with sort of that use case in mind. And I think for some portion of enterprise customers, they want flexibility in sort of like their external search tooling providers and sort of Google Cloud's doing their job as a great enterprise business of sort of partnering and finding the right folks to work with.”
Publisher
The Cognitive Revolution

14 / prediction

Like you definitely, I think the near-term horizon is going to continue to be the human in the driver's seat because the cost of these runs and the opportunity cost of going in the wrong direction and putting a bunch of resources is super, super high.

“Like you definitely, I think the near-term horizon is going to continue to be the human in the driver's seat because the cost of these runs and the opportunity cost of going in the wrong direction and putting a bunch of resources is super, super high.”
Publisher
The Cognitive Revolution

15 / commitment

So we want any of our enterprise customers or a developer who's building their own use case to be able to leverage Gemini effectively. And so it is important then from a model standpoint that we're training in such a way that we actually, we sort of call it like harness diversity.

“So we want any of our enterprise customers or a developer who's building their own use case to be able to leverage Gemini effectively. And so it is important then from a model standpoint that we're training in such a way that we actually, we sort of call it like harness diversity.”
Speaker
Tulsee Doshi
Publisher
The Cognitive Revolution

16 / evaluation

5 Flash because I think Flash does this really awesome job of being at the sweet spot of being really smart while also being really fast and really cost effective.

“5 Flash because I think Flash does this really awesome job of being at the sweet spot of being really smart while also being really fast and really cost effective.”
Speaker
Tulsee Doshi
Publisher
The Cognitive Revolution

17 / evaluation

Like I don't know if like a lot of the agentic stuff we were landing at IO like would have been possible if we if we hadn't have had sort of some of that infrastructure standardization across the harness and the model delivery.

“Like I don't know if like a lot of the agentic stuff we were landing at IO like would have been possible if we if we hadn't have had sort of some of that infrastructure standardization across the harness and the model delivery.”
Publisher
The Cognitive Revolution

18 / evaluation

I think the other part though is like, how does deep research do so well or how can we use the model in search is because we also have the model search, right?

“I think the other part though is like, how does deep research do so well or how can we use the model in search is because we also have the model search, right?”
Speaker
Tulsee Doshi
Publisher
The Cognitive Revolution

19 / prediction

I think we're gonna keep getting things that we're using internally that we even start to push out externally through previews and this.

“I think we're gonna keep getting things that we're using internally that we even start to push out externally through previews and this.”
Speaker
Tulsee Doshi
Publisher
The Cognitive Revolution

20 / evaluation

for totally different users and sort of I think actually that credit to the model team sort of like trying to find the fine line for all these different places because we're not just building for search, we're not just building for developers, we're not just building for cloud customers, it's not just for the Gemini app, it's like all of them at the same time, which is just exceptionally a lot of work to pull off that story on a consistent basis, which like from Gemini 3 forward has been the story, which is which is exciting.

“for totally different users and sort of I think actually that credit to the model team sort of like trying to find the fine line for all these different places because we're not just building for search, we're not just building for developers, we're not just building for cloud customers, it's not just for the Gemini app, it's like all of them at the same time, which is just exceptionally a lot of work to pull off that story on a consistent basis, which like from Gemini 3 forward has been the story, which is which is exciting.”
Publisher
The Cognitive Revolution

22 / prediction

Like the best case is like it works really well for Gemini and sort of we can sort of do the things we want to do to scale up because we do have sort of control over the sort of full stack AI story as Sundar likes to say.

“Like the best case is like it works really well for Gemini and sort of we can sort of do the things we want to do to scale up because we do have sort of control over the sort of full stack AI story as Sundar likes to say.”
Publisher
The Cognitive Revolution

23 / evaluation

Actually, like, it was awesome, one of my coworkers Anka, she's our lead for safety and alignment. And the other day, she, I think maybe a couple days ago, she pinged me from her hot tub and she was like, I could run all of these ablations from my phone because I could kick off a bunch of things to actually ablate Gemini to test for a bunch of these issues to see how some of our SIs differ or some data ablations differ.

“Actually, like, it was awesome, one of my coworkers Anka, she's our lead for safety and alignment. And the other day, she, I think maybe a couple days ago, she pinged me from her hot tub and she was like, I could run all of these ablations from my phone because I could kick off a bunch of things to actually ablate Gemini to test for a bunch of these issues to see how some of our SIs differ or some data ablations differ.”
Speaker
Tulsee Doshi
Publisher
The Cognitive Revolution
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