Logan Kilpatrick
Product Lead, Google DeepMind. On 4 shows, 7 appearances. The Shows tab opens the full record on each.
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Logan Kilpatrick is the Product Lead for Google AI Studio and the Gemini API at Google DeepMind. Previously, he served as the first Head of Developer Relations at OpenAI.
4shows
7appearances
82statements
21resolved
18supported
1contradicted
86%fully supported
26said about them ↓ Everything Logan Kilpatrick said on any show that made the record, most notable first. Each card names its show and opens the statement there.
Kilpatrick: Pre-Training Isn't Dead; Gains Multiply Through Post-Training and RL
“And this is why, like, I don't subscribe to the, like pre-training is, you know, dead and all that stuff, because the more work that you can do at the pre-training level, those capabilities, as you do post-training and as you give the models RL capability, it'…”
Kilpatrick: Generative UI will be the killer use case for diffusion LLMs
“But I do think that's going to be the killer use case will be like this generative UI experience that doesn't exist today because the models just take too long to generate tokens.”
Kilpatrick: Google's strategy is building Gemini as one single unified model
“Like we're here to make one model and like that model is Gemini.
And like, I think you do need to just trust this point, like to make the capabilities work in some cases, like you do need to have these forks that like go off and make that capability and harde…”
Kilpatrick: Gemini's SOTA video performance resulted from reasoning, not video engineering
“With reasoning is a great example of this where like multimodal with video understanding ended up like having this huge, like it's having this beautiful moment.
The model is like soda out of the box because of all the reasoning capabilities that were baked in…”
Kilpatrick: AI models now outperform humans on most vision tasks
“If you look at like multimodal, like the fact that the models can like with better, better than just from a multimodal input perspective, better than humans are at like most vision tasks, like The number of products and like things that that unlocks is like tr…”
Kilpatrick: Pushing the AI Pareto Frontier Uniquely Increases Builder Margins
“And like the margin for people building AI products actually goes up every, like the farther you push the Pareto frontier, the more money builders get to make, which is like such a interesting and like unique thing about this AI moment that I actually don't th…”
Kilpatrick: ChatGPT's consumer success was driven by its API business
“I think part of my core worldview is a lot of the reason that ChatGPT has been as successful as it has
Is because there was an API business built around it.”
Kilpatrick: Gemini 2.5 Pro Relied on Pre-Training Innovations, Not Just RL
“But I think if you look at like a, an example of this in practice, like 2.5 pro is actually an example where it wasn't just like RL scaling that made that model better. Yes, RL was part of the story, but like there was also a bunch of pre-training innovation a…”
Next billions of AI users will onboard via SMS and phone
“I don't think those people are going to come in through, you know, some front end website somewhere. Like those people are going to come in through audio from a telephone to texting to email. Like that's just the most obvious outcome.”
Embeddings will not scale for cross-session memory in real-time AI systems
“I don't think that like embeddings are going to be able to scale to, I think they work well for some of this as like kind of the MVP version of the experience, but I think you're going to need a different experience and it's Probably something like really smar…”
OpenAI models will likely never match vertical tools like Harvey
“Our models are probably never going to be as capable as some of the things that Harvey's doing because like our goal and our mission is really to solve this like very general use case.”
Startups building general-purpose AI agents will directly compete with OpenAI
“I talked to a lot of developers who are building like, you know, just general purpose assistance and like general purpose agents and stuff like that. And I think it's cool and it's a good idea. I think like the challenge for them is like, they are going to end…”
Adding AI researchers decreases group productivity when GPU capacity is constrained
“In a world where you're constrained by the amount of GPU capacity that you have as a researcher, which is the case for OpenAI researchers, but also researchers everywhere else, like Each new researcher that you add is actually, like, a net productivity loss fo…”
GPT-5 will normalize as a useful tool rather than changing everything
“GPT-V is like surely going to be extremely useful and like solve some whole new echelon of Problems. Hopefully they'll be faster. Hopefully it'll be better on all these ways, but like fundamentally the same problems that exist in the world are still going to b…”
Kilpatrick: Gemini 3.0 Pro API undercuts GPT-5.1 Pro and Claude 4.5
“The actual model is two dollars per million input tokens and 12 dollars per million output tokens. So it's priced below some of those sort of comparable competitive models like GBT, 5.1 pro as an example, and Claude 4.5.”
Direct AI creation preserves story fidelity better than human intermediary layers
“What happens when you, as the person who like has a story to tell or like some idea, you have to like put it through this translate, this translation layer, especially when the translation layer is sometimes like a, you know, a bunch of people or something lik…”
Image quality does not degrade across multi-turn AI conversational edits
“The model doesn't like the image quality doesn't get worse as you like do a multi-turn edit. So like you don't need to get everything right on the first edit.”
Kilpatrick: Live AI APIs create severe vendor lock-in due to bespoke infra
“I think if you look at a lot of the live API infrastructure right now, like you really do need to commit that you're like gonna, you know, there's, it's not easily interoperable between different model providers. Like everyone's infrastructure is all bespoke a…”
Kilpatrick: Google's Full-Stack Control Extends From Silicon to Model Delivery
“Google controls. From a product perspective, like all the way to how the models are delivered to how the models are trained down to the silicon. So like you can make decisions assuming a bunch of those things are going to be true, which is like a lot of folks …”
Kilpatrick: Real-Time Audio and Video Is Next Major AI UX Iteration
“I don't think we've seen like across other product services, people actually invest in like real-time audio and real-time video and image stuff. And I think that's like the next iteration of the UX of how people are going to interact with AI models.”
Kilpatrick: Burdening AI users with prompt crafting is a product bug
“Yeah, I actually, my personal take on this is I think this is a bug of this current AI moment where like the, if you look at like what is the ideal case is the models and the products like pull out what they need to from the user in order to create value for t…”
Kilpatrick refuses to build AI products that require changing user behavior
“And this is maybe too like absolutist of like a product perspective, but like, I will not build a product that like we have to try to convince a consumer to change their behavior.”
Kilpatrick: In 10 years, AI interfaces will look eerily similar to texting
“And I actually think if we've, if we fast forward like. 10 years, I do think there's going to be a lot of those experiences which like look eerily similar to the way that they do today, because it's just like so ingrained in like human culture, like how, like …”
Kilpatrick: Real-time multimodal models will become co-present pair programmers
“I think the future that we're going to see with the multimodal live API is really the ability for the model to or just like generally for models to be co-present in the experiences that you are. And like, you could imagine your IDE is the best experience of th…”
The other half of the tape: Logan Kilpatrick's own voice is left out of every number here. Other people bring the name up 26 times in 17 episodes across the shows. every mention, with the transcript →
Who brings them up most Greg Isenberg 5Shawn Wang 3Tae Kim 2John Coogan 2Alessio Fanelli 2Yi Tay 1Lee Robinson 1Jordi Hays 1
Every mention by year
tap a year for its mentions
TBPN 13
Latent Space 7
the Startup Ideas Podcast 6
2026 11 mentions in 8 episodes 1 per episode
- AI Safety Timeline Takeover, Bending Spoons Acquires Miro, iPhone Duo Reactions | Diet TBPN
- ⚡️ Google's Open AI Strategy — Omar Sanseviero, Google DeepMind
- FULL INTERVIEW: Why I Think Nvidia Is Perfectly Positioned In The AI Race
- Podcast Crossover: AIE, AGI, frontier lab strategy with @matthew_berman and @swyxtv
- Google I/O, Fertility Decline, Spotify Logo Drama | Diet TBPN
- Netflix’s Next Move, Zuck’s $170M Florida Mansion, the Billionaire Tax Push | Diet TBPN
- Big Tech Earnings, Elon’s SpaceX–xAI Merge, Genie 3 | Diet TBPN
- Captaining IMO Gold, Deep Think, On-Policy RL, Feeling the AGI in Singapore — Yi Tay
- every mention in 2026, scene by scene →
2025 13 mentions in 8 episodes 2 per episode
- I Tested Gemini 3 as a Designer. It’s Terrifyingly Good.
- ELON MUSK's New Grok 4 Is Here! - We Break it Down
- Google Gemini 3 Reactions, Google Antigravity, Anthropic-Nvidia-Microsoft Deal | Diet TBPN
- I gave away $1M to prove anyone can build with AI
- Cursor AI Agents Work Like 10 Developers (Cursor VP Live Demo)
- Google’s Genie 3 Builds Game Maps From a Single Prompt
- Weekly Recap: Grok 4 Launch, Texas Floods, Web Browser War, Top Signals, Meta Smart Glasses
- ⚡️Launching AI Diplomacy: the hardest LLM Game Benchmark yet - Alex Duffy
- every mention in 2025, scene by scene →
2024 2 mentions in 1 episode
One line per show, most statements first. The link opens Logan's full record on that show: the calibration, argument clarity, speaking style and every statement made there.
| Show | Role there | Eps | Statements | Record | |
|---|---|---|---|---|---|
| STARTUP IDEASLEDGER | Product Lead, Google DeepMind | 3 | 30 | 82% 9/11 | full record on the Startup Ideas Podcast → |
| TBPNLEDGER | Product Lead, Google DeepMind | 1 | 19 | 80% 4/5 | full record on TBPN → |
| LATENT SPACELEDGER | Product Lead, Google DeepMind | 2 | 17 | 100% 3/3 | full record on Latent Space → |
 LENNY'S PODCASTLEDGER | Product Lead, Google DeepMind | 1 | 16 | 100% 2/2 | full record on Lenny's Podcast → |