Satya Nadella on Copilot, the AI backlash, and Microsoft’s future @satyanadella thinks AI agents will create a market “orders of magnitude” bigger than the cloud. I recently sat down with him in Seattle for the unveiling of the new Copilot. We discuss Autopilot, Microsoft's new OpenClaw-based agent that can work on your behalf, and why he thinks newer AI models are finally capable of delivering on more of Copilot’s promise. Nadella also has a blunt assessment of the AI industry: “We are way too self-obsessed.” I ask him why the industry has struggled to explain its benefits and what it will take to earn people’s trust. We get into his concerns about agents acting deceptively, when a safety problem should stop a release, and why he doesn’t want AI oversight to become a “cartel-like arrangement.” We also discuss Microsoft’s relationship with OpenAI, the models Microsoft is building itself, and why Nadella wants investors to think about its apps, agents, and infrastructure as one connected business. He explains how he uses AI to track Microsoft’s capital spending, shares his vision for “unmetered intelligence” on Windows, and gives an update on Xbox’s path back to growth. Timestamps: 00:00 The race for AI agents 07:53 Copilot’s next chapter 11:50 Autopilot and the digital teammate 16:50 How Microsoft prices AI 19:48 Why Microsoft is betting on multiple models 23:18 Measuring AGI through economic growth 28:39 The economics of Microsoft’s AI build-out 32:13 OpenAI and Microsoft’s own models 35:27 AI safety, control, and regulation 43:53 Why the AI industry is losing public trust 46:59 The future of Xbox and Windows 50:34 Microsoft’s biggest risk and opportunity Thanks to the show's premier sponsors: @mercury, @meetgranola, and @Atlassian.

The new Copilot is Microsoft’s bet that the AI race is moving from models to products. It doesn’t need to own the best model if Copilot can choose among them and keep the customer inside Microsoft. The potential secret weapon is Autopilot (what I’ve been calling Muse for Business). It knows your workflows, sits across the apps and data you already use, and keeps working even when you step away. It’s a preview of the battle to come in enterprise AI. OpenAI and Anthropic are racing from models into products. Can they build their own version of this? And can they match Microsoft on the boring-but-critical stuff: permissions, identity, auditability and control, as agents become more autonomous? My full conversation with @satyanadella. We also talk open vs. closed models, US-China Summit, regulation and the infrastructure buildout. 00:00 Microsoft’s new Copilot 02:02 Why not just give us Autopilot? 05:18 Who pays for always-on AI? 08:06 Copilot picks the model 10:27 Chinese models and OpenAI’s lead 12:04 Competing with OpenAI and Anthropic 13:17 US–China AI talks 16:11 Does AI need new rules? 18:05 The data center backlash 20:40 Is AI being overbuilt? 23:44 Keeping humans in control

We’re building Copilot as a new OS for work that spans every model, every form factor, and every task. Today, we’re announcing our biggest update to Copilot to date, bringing four things together: · Autopilot: proactive and long-running agent built for the enterprise · Code: build apps with Copilot, hosted inside your company’s tenant · Home: Chat + Cowork together · Office: now fully embedded in Copilot (and Copilot embedded in Office, of course!) Plus, you can invoke Copilot in Teams, and we’re introducing Today, a proactive experience that surfaces the most important information from across M365 without needing to ask for it. The way we work is changing and so are our workflows. This update brings AI into that flow, from answering a question, to building an app, to getting work done on your behalf.

Great conversation with @chamath, @jason, @davidsacks, and @friedberg on all the work ahead when it comes to diffusing benefits of AI broadly, earning permission from communities, and ensuring AI safety and control.

Great example from @jeffhollan showing how Foundry makes long-running agents enterprise-ready, starting with business outcomes and building security, safety guardrails, auditability, and FinOps into the system from the start, across the entire multi-agent, multi-model workflow.

I think of this like testing. We all do deliberate pacing when it comes to pre-release R&D and testing. And having more outside/3P testing/testers is a good thing. And as the stakes get higher, one should take all the time they need! If not you will anyway lose permission to operate. That is how we operate everyday.

Any pursuit of superintelligence has to be grounded in the core principle that if the AI we build is not helping humanity and under human control, it's not worth pursuing. We also need to accelerate and spread the benefits of AI, such that they are diffused broadly across countries, communities, and companies. This requires a frontier ecosystem in which both closed and open-source models can thrive. And for firms, it’s imperative that they retain full control over their unique and tacit knowledge. Every organization should be able to build its own continuous learning loop/hill climbing machine, without becoming dependent on any one model provider, and have the ability to embed its own knowledge into models and weights they control. So, in this context, we welcome the research, focus, and deliberate pacing needed to get alignment right as the design goal. We also welcome ideas like "embedded evaluators" and the broader efforts to develop the mechanisms to make this more than just talk. The key is that this cannot be controlled by a handful of entities, but must have broad representation across the ecosystem, countries, and fields, including academia. This is the approach we are taking: broad access and choice at every layer of the AI stack; enterprise control of learning loops and models; and the “Code of Conduct” that underlies our own first party MAI models that we’ll publish tomorrow for public consultation.

With the @NFL back tonight, love seeing @Seahawks analyst Brian Eayrs and coaches across the league using new Copilot and Excel tools to help with decision making in the booths and on the sidelines.

Our goal is to deliver the latest frontier AI models to customers the moment they’re ready. Today, I’m excited to share that OpenAI’s GPT-6 Astra is available on day one across Microsoft Copilot, Copilot Studio, GitHub Copilot, and Microsoft Foundry. Astra represents an important step forward in the kind of complex, multi-step work AI helps people accomplish. As models continue to improve, people are moving from using AI for individual tasks to delegating larger pieces of work. Astra can complete long running and highly complex tasks in a way we haven’t seen before. At Microsoft, we’re bringing those capabilities into the products and workflows our customers already use every day. Astra is paired with Work IQ in Microsoft Copilot to ground intelligence in an organization’s files, meetings, chats, and business data. Looking forward to seeing what customers build with it. Read more in the blog:

Super excited about HydraFusion in GitHub Copilot, and what it shows about the shift from model selection to model orchestration. By bringing together multiple models to plan, build, critique, and complete coding tasks, it can deliver outcomes at up to 67% lower cost. It’s a great example of the value of a heterogeneous model ecosystem, and how we’re continuing to advance the cost-to-outcome frontier.

Delivery day at our Microsoft DCs as the first production Vera Rubins arrive. A huge thank you to our partners at @nvidia and our Azure hardware and datacenter teams for all the incredible work that brought us to this milestone!