We Are About To Experience The Personal Agent Supercycle AI is rarely accused of being underestimated. But I think the movement forming around personal agents is highly underestimated. We have been talking about agents for a while. But outside the AI-pilled corner of X, I don’t think most people have internalized what happens when anyone can have a capable coworker that keeps working after they close their laptop. My thesis is that personal agents will trigger another compounding AI supercycle. Consumer adoption, enterprise demand and infrastructure consumption will accelerate together. Consider the early signals. In August, @OpenRouter data shared by @a16z showed agents consuming nearly 5x as many tokens as human-driven usage on its platform. @Deloitte projects inference will account for roughly two-thirds of AI compute in 2026. One person delegating a goal can set off an extended chain of planning, execution and verification. The amount of work we delegate becomes a new driver of demand. Now combine that with mass consumer distribution. @Meta’s @Muse brings personal agents into @WhatsApp. Meta knows how to make sophisticated technology accessible to enormous audiences. That is a meaningful advantage in a category where adoption depends on people experiencing something they struggle to understand from a description. Whether it is @Muse, Instinct, @Grokbot, @OpenAI or another player, personal agents could make power-user capability available through an ordinary conversation. People won’t need to master a collection of tools to experience what those tools can accomplish. My bet is that the next 12 to 15 months will bring a much faster move toward mainstream adoption than most companies are planning for. And that experience will travel into the enterprise. Once people routinely delegate meaningful work in their personal lives, they will expect similar capabilities at work. Consumer adoption becomes a training ground for enterprise adoption. Companies will face growing pressure from their own employees to make this possible. The biggest constraint, in my view, will be trusted delegation and infrastructure availability. An agent’s usefulness expands with the access we give it. So does the consequence of a mistake. Without access to our applications, data and tools, much of its potential remains inaccessible. Granting that access requires confidence in its judgment, clear limits on its authority, visibility into its actions and the ability to intervene. That makes safety and security central to adoption itself. Every improvement in trust can unlock more delegation. More delegation creates demand for the compute, memory, networking and power needed to support it. This is the compounding effect I think we are underestimating. More people discovering what agents can do. More work entrusted to them. More enterprise demand. More infrastructure required. We are approaching another ChatGPT moment in AI. I thought @OpenClaw might be that moment, but its setup complexity limited its reach. The next breakthrough may come from agents that hide that complexity entirely: a Muse, Instinct, Grokbot or OpenAI product that lets anyone delegate a long-running task in a simple conversation and return to a completed result. Delegation will feel natural, trustworthy and reliable at scale over the next few months. Every task users are willing to hand over will expand the market for agents and the infrastructure required to run them. The next ChatGPT moment is fast arriving. The next AI supercycle is forming right in front of our eyes. 3 months from now will look very different for personal productivity provided safety and security make progress which they will, however we will continue to have demand outstrip supply in infra if personal agents proliferate as much as I think they will.

The debate this week around the risks of safety and security with AI was the strongest we've seen. I happened to be in London earlier today and met with @cnbcKaren, Steve Sedgwick and @Benboulos from @CNBC. We discussed a range of issues including safety and security, margins for hyperscalers, durability of demand, slowing down AI, global coordination to handle security risks and more.

Your data can stay where it is. AI can come to it. At #splunkconf26#, Splunk shared how @Cisco Data Fabric, powered by the Splunk Platform, helps orgs connect distributed machine data & turn it into trusted operational context for AI. Dig in:

Today, BRT Chair @ChuckRobbins announced Kristen Silverberg as BRT’s next President and Chief Executive Officer. Ambassador Silverberg, who currently serves as President and Chief Operating Officer, will succeed current BRT CEO Joshua Bolten when he retires on January 31, 2027.

Exciting day for NVIDIA and @huggingface. Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty. They allow every developer, startup, university, industry and country to build with, customize and benefit from AI. Thank you @ClementDelangue for coming to me. NVIDIA is going to be a great home for Hugging Face, its community and the future of open models. 🤗

I have some really fun news. I’m delighted to announce that @sunilpotti is joining @Cisco and will lead our Security, Observability and Data Platform teams, bringing our Security and Splunk businesses together under one leader. Sunil will join my leadership team and report directly to me. He has spent years building and scaling some of the most important security platforms in the industry, most recently leading Google Cloud Security. There are very few people who combine deep technical instincts, product leadership and the ability to operate at enormous scale the way Sunil does. I could not be more excited to have him here, and I think it says something about the opportunity in front of Cisco that exceptional builders like Sunil want to come help us create what is next. The timing could not be better. We are squarely entering the agentic era, where AI agents will increasingly act autonomously across applications, infrastructure and data. This creates an entirely new set of problems. When something goes wrong, was it a breach, an infrastructure issue, a software failure, or did a perfectly legitimate agent simply exercise spectacularly bad judgment? Those distinctions are going to become much harder to make. Security tells us whether something might be malicious. Observability tells us what actually happened. Data gives us the context to understand why. I believe these three areas are going to become increasingly inseparable, which is a big reason why bringing these teams together now makes so much sense. This is also where I think Cisco has a very unique opportunity. In this new world, we have to operate with the assumption that the adversary may already be inside the environment, and increasingly that adversary could itself be an agent. The job is no longer just keeping threats out. It is detecting them, understanding what they are doing and preventing lateral movement once they are inside. And where does lateral movement happen? On the network! Few companies in the world have the depth of network telemetry and context that Cisco has. When we combine that telemetry with security, observability and data, and co-design it with the rest of our stack across silicon, networking and compute, we can build something fundamentally different. That is the vertically integrated platform we are building for the AI era. There is a tremendous amount of innovation already in the pipeline, and I think we are only beginning to scratch the surface of what is possible. I am super stoked to work with Sunil and the entire team to go build it. Welcome to Cisco, Sunil. Let’s make the world safe, secure, observable and open!

Honored to join @aalswaha and @TareqAmin_ at @LEAPandInnovate. Congratulations to @humain on the tremendous progress over the last year. Excited to announce our first clusters with @humain and @cisco are live in the Kingdom with lots more to come.