Sources with Alex Heath

Even Google can’t get enough compute. I sit down with Google and Alphabet CEO Sundar Pichai shortly after the wider release of Gemini 4 Argon to discuss its early reception, where he still wants the model to improve, and what it takes to keep Google at the frontier of AI.
Pichai explains the recent leadership shakeup at Google DeepMind and why building frontier models has become an “all-consuming” job. We also get into Google’s answer to the personal agent race, how he predicts Gemini will do more work on your behalf, and whether agents will finally bring Search, Gmail, and Gemini together.
I ask him about Google turning free cash flow negative, the risks in the AI infrastructure buildout, and how he plans for demand years before knowing what the models will be capable of. He explains the signals giving him confidence to keep spending and how he uses AI agents to follow model development and compute usage inside Google.
We also discuss Project Suncatcher, Google’s new effort to put AI data centers in space, and why he thinks it belongs alongside bets like Waymo. He shares what’s next for Waymo and Wing, and when he expects quantum computing to become a real business.
This episode's presenting sponsor is Hyperagent - https://www.hyperagent.com/ . Thanks to the show’s premiere sponsors: Atlassian, Granola, and Mercury.

Robinhood wants to put an AI hedge fund in your pocket.
CEO Vlad Tenev tells me how Robinhood Agents brings AI trading into the app, and why he expects agents to generate a growing share of individual investors’ trading activity.
We discuss how much control to give an AI that can trade your money, why Robinhood keeps agents in separate accounts, and where investors will find an edge when everyone has access to powerful models.
He also explains his push for every Robinhood employee to have agents working while they sleep. Tenev argues that the AI backlash is partly an ownership problem: most people can’t invest in the companies driving it. We get into Robinhood’s push to open private markets to everyday investors, the coming AI IPOs, and his response to criticism of tokenized stocks. We also discuss prediction markets and why he objects to AI labs keeping their most powerful tools to themselves.
Thanks to the show’s premier sponsors: Atlassian, Granola, and Mercury.

AI could give people a reason to buy a new phone again.
Qualcomm CEO Cristiano Amon tells me why he expects a smartphone supercycle as AI agents start using our apps and acting on our behalf. His company makes the chips behind Android phones, Meta’s smart glasses, and coming devices from AI companies like OpenAI, giving it a stake in several competing visions for the next big AI device.
We discuss why he thinks phones aren’t going away, how agents will use our personal context, and why he expects smart glasses to become the biggest category of AI wearables. We also cover differences in consumer AI adoption between China and the US, Qualcomm’s acquisition of Modular to offer developers an alternative to Nvidia’s software, and what 6G could change about the devices we use.
This conversation was recorded live at Qualcomm’s recent Snapdragon Summit in Hawaii
Thanks to the show’s premiere sponsors: Atlassian, Granola, and Mercury.

Reflection is soon releasing Beam, its first open-weight AI model, in a bid to become the DeepSeek of the West. Trained from scratch, Beam is designed for coding, reasoning, and AI agents. Reflection's benchmarks put it alongside the strongest open models, with substantially more efficient token economics.
To mark Beam’s debut, I'm joined by Reflection's co-founders: CEO Misha Laskin, who led reward modeling for Google’s Gemini, and CTO Ioannis Antonoglou, who helped create AlphaGo and AlphaZero before leading Gemini’s RLHF effort. Reflection has raised $4.6 billion from investors that include Nvidia, Sequoia, and Lightspeed.
We discuss why Chinese labs pulled ahead in open AI models, how Reflection built Beam, and why the founders think companies and countries will increasingly want to control their own models. I ask how they plan to make money from open-weight AI, whether openness can make these systems safer, and what comes next for Reflection.
Thanks to the show’s premier sponsors: Atlassian, Granola, and Mercury.

OpenAI’s next big bet is Dots, personal AI agents that can find ways to help you without waiting for a prompt.
Alexander Embiricos, OpenAI’s Dots product lead, tells me why the company is moving beyond chatbots and what that means for the future of ChatGPT. We discuss why Dots have their own computers, how they share context across the places you talk to them, and why he thinks most people will only need one personal agent.
I ask him how much control people should give these agents, how OpenAI approaches permissions and privacy, and why Dots ask before taking action by default. He also explains Space, a new workspace where people and agents can collaborate on documents, data, and projects.
We get into how OpenAI plans to price an always-available assistant, how these capabilities could eventually reach free ChatGPT users, and the story of an employee who woke up to discover his Dot had helped fix a bug.
This conversation was recorded in front of a live audience at OpenAI's 2026 DevDay conference.
Thanks to the show’s premiere sponsors: Atlassian, Granola, and Mercury.