Google published an interview with Google DeepMind SVP and Chief AI Architect Koray Kavukcuoglu. Kavukcuoglu shared that Google is increasingly viewing Gemini as an AI agent, not a chatbot. This is important because CEO Sundar Pichai has expressed that agentic AI is the future of search.
Gemini Is Transitioning From A Model Toward Agentic AI #
Koray Kavukcuoglu shared that Google DeepMind increasingly sees Gemini as an agent, much more than just a chatbot or language model. What inspired this change is coding, that was the gateway to software engineering, tool use, and agentic workflows.
Kavukcuoglu said that the goal is not really about creating a model that answers questions better. The focus now is to create something that can take actions on behalf of and alongside a human.
The interviewer, Logan Kilpatrick asked Kavukcuoglu if he wanted to talk about Google DeepMind’s “architectural innovation” and Kavukcuoglu answered that that wasn’t something he was willing to talk about right now, indicating there’s something going on behind the scenes.
But what he did discuss was how Google’s focus has transitioned toward agentic AI.
He shared:
“Going from the initial 3.0 launch, my reflection is we learned a lot in terms of understanding what it means to do coding, and not just coding, right?
Like what it means to do software engineering, what it means to work with tools or work with the functions that people use every day.
Basically turn this whole thing into an agent, from a model to an agent.
And that transition, I think we were sort of walking around it, and that was the thing that we wanted to directly tackle. And of course, software engineering is the most critical domain and environment that you want your systems to be successful in because it’s at the root of many, many different things that you can do.
During that time, we learned a lot in terms of how to train a model, how to train an agent that can actually code with you. And after that, I think the steps have started becoming faster.
And like in any research project, there are many parallel tracks that is going on at the same time too. So what we are trying to do right now is combine all these learnings, of course, like add on top of them, understand what it means to do agentic actions and agentic workflows better, together with new architectural improvements, together with new ideas that we have been working on for a while.
Many of these things that we have done in 3.6, 3.7 go back like a year or more, and then those start paying off and you converge them into the model.
And it’s great to see the quality impact that we got from that. We were very excited in the run up to 3.7. When we were doing 3.6, of course, we could see what 3.7 could be or what the next step could be.
And then it came together and internally we started enjoying that model A lot. So that’s the parallel track effect that you are going, that you are seeing.”
AI Is Changing But The Steps Remain The Same #
Something else he talked about seemed contradictory in that he said revolutionary change is happening but what’s causing it is not revolutionary itself. He said that the basic steps for creating AI hasn’t changed nearly as much as the problems that AI is solving have. What it does is revolutionary but the way it gets there hasn’t undergone a revolutionary change.
Kavukcuoglu said that they are still using:
- Deep learning
- Pre-training
- Reinforcement learning
- Optimization techniques that rely on similar underlying principles as from the past
What changed, he said, is the environment in which AI is operating in which requires models to infer intent, deal with ambiguity and collaborate with humans.
Google Has Improved Agentic Workflows #
Later in the discussion Kilpatrick said that Gemini 3 reached the frontier, but that the frontier subsequently moved toward agentic coding and agent-like capabilities.
Kavukcuoglu said still had things to learn about agentic actions and workflows, saying that the work surrounding Gemini 3.5 taught them about how people actually work with agents, and that he now feels more confident that Google has a better understanding of those kinds of interactions.
He explained:
“I think there are two things that we need to keep in mind.
One is, by definition, in a very competitive environment, the frontier will always shift. There will be ebbs and flows of different things. And the cadence and the frequency of which lab is producing their most capable model is going to change. That’s #1.
But #2 is a fair point. And we talked about that in the context of 3.5. I think we learned a lot about agentic actions and agentic workflows. And being able to bring that to life in a model, that’s the process that we went through.
Where I’m feeling right now, I’m feeling very, very, very comfortable and good right now where we are and our capability of understanding what users need when they are working with an agent that is partnering with them on any kind of agentic task and workflow.
But we went through that process of building that.”
Google DeepMind: The Most Important Improvement In AI #
The interviewer, Logan, then asked Kavukcuoglu to share what is the most important improvement in AI.
He asked:
“…if you could sort of wave your magic wand and sort of get the models to do anything and not need to spend a lot of time and energy, do you have anything on the top of that list that you would sort of want a capability, sort of better behavior on something?”
Kavukcuoglu answered:
“I think if I had a magic wand, I would just make them more intelligent. I think the models get more intelligent they do everything better, they do everything more intuitively, and I think that would be excellent.”
Takeaway #
Google DeepMind, and Google as a whole, is transitioning toward more than providing answers, it’s helping users accomplish tasks. All of Google’s products, from Gmail, to Google Sheets, to Maps, all help people accomplish tasks. Kavukcuoglu explained that AI models are conceptually becoming more than just chatbots, they are also becoming more agentic, and that reflects how everything at Google is changing, including Search.
Watch the interview here:
Featured Image/Screenshot of interview