Google DeepMind's Logan Kilpatrick: Why the Model Eats the Harness
In a Nutshell
Logan Kilpatrick describes Google's shift from using the Gemini model as the connective tissue across products to deploying an "anti-gravity" agent harness that powers autonomous, long-horizon agents in coding, Search, and consumer apps. He argues the harness itself is the current source of competitive advantage because models will soon absorb most scaffolding, and that coding has emerged as the general-purpose proving ground for agentic systems. Key bets include measuring agent run duration as a core KPI, betting that narrow superintelligence in verifiable domains will compound into broader capability, and positioning DeepMind's scientific culture as the engine for Google's frontier products.
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Logan Kilpatrick shared an example of using Gemini to edit a video in real time during a talk with Tulsi, who leads the model team. Someone in the crowd took a picture and edited it with Gemini, adding a dog that appeared on stage. In the edited version, other guests looked down, saw the dog, and chuckled while Kilpatrick continued speaking and petted the dog. The model handled subtle nuances like the guests' reactions and the interaction correctly.
Logan runs Google AI Studio and the Gemini API, spending significant time thinking about and building for the next generation of builders.
Sundar opened Google I/O by calling this the "Agentic Gemini era." Kilpatrick explained that while Gemini 2.0 mentioned some agentic concepts earlier, the Gemini 3.5 era is when agentic products are actually becoming reality. For Google, this includes agentic coding and agentic products across the board.
The agentic layer is powered by the anti-gravity agent harness, announced at I/O. This serves as an additional through line connecting all Google products. Historically, prior to Gemini, there was no single through line across Google's 50+ products. Gemini became that through line, and now anti-gravity is emerging as the new through line as products rebase to become agentic native and take action on behalf of users.
Anti-gravity encompasses multiple components: a core IDE, an agent-first web experience, a CLI, and an SDK. It functions as an ecosystem designed to meet developers wherever they are. Developers can use it through the Gemini API for a managed agent without infrastructure work.
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