There is such a profound shift occurring in the way that Agents alter our infrastructure requirements. We are entering a networking supercycle. It’s not because humans are consuming more content. It’s because machines are beginning to think, act, and transact continuously. Cisco's latest research on AI traffic patterns points to something much bigger than incremental bandwidth growth. Enterprise WAN traffic without agentic AI was projected to grow roughly 2.5x over the next decade. With agentic AI, that projection jumps to ~9x. And here’s the craziest part! After following this data closely, I believe even those numbers may prove to be wildly conservative. This is the first time when we have published a study like this where I feel that the projections might be off significantly and what we might think takes a decade happens in 3 years. Why? Because most people are still modeling AI like software. It is not. AI behaves more like a new species of digital labor. A SaaS app waits for humans. Agents do not. Agents continuously reason, retrieve, coordinate, negotiate, execute, and loop. At software speed. Without pause. 7x24. They never get sick. Don’t need a vacation. Dont get tired. Don’t need sleep. That creates a fundamentally different traffic architecture. The industry spent decades optimizing networks for bursty downloads, video streaming, and human-paced interactions, almost all of it flowing downstream to a person on the other end. AI traffic inverts that. A single agentic task can generate 450% more traffic than a human doing the same work. Roughly 70% of that is inference. And nearly 10% of AI flows now carry more upstream than downstream data, versus 0.5% for typical web traffic, because context continuously moves back into models. Network traffic is not just increasing in bandwidth. It is fundamentally getting reshaped. This last point matters most. The internet was built as a distribution system for content. AI is turning it into an active system for cognition. The path between agents and models is becoming the spinal cord of intelligence itself. When that path degrades, the agent degrades. Networking stops being a passive transport layer and becomes part of the intelligence stack. That changes everything about how we think about resiliency, observability, security, and capacity at the edge. We may be grossly underestimating what is coming. The future will not simply have more users online. It will have trillions of digital coworkers operating continuously on behalf of humans, enterprises, applications, and eventually physical systems. Humans click. Agents swarm. That difference is what creates a supercycle. This supercycle of inference infrastructure will not just be compute bound, but also memory and network bound. Take a look at the report here: cisco.com/c/dam/en/us/soluti…

So obvious. So hard to follow. 👇🏾

It’s also a master class on a perfectly executed product release. So well done!

There are product launches and then there are PRODUCT LAUNCHES 🚀! So crazy!

💯 👇🏾

In a world of agents where we are largely supply constrained in Datacenter capacity starting from land, power and shell to compute, memory, networking, the solution is to not just build more data centres, but to make sure that the current data centers we already have are operating in a far more efficient and performant manner. Innovations on getting more tokens per dollar spent on existing data centers is going to be necessary in this supply constrained world we will be living in for the foreseeable future.

So nuts! 👇🏾

Another great add to the @Cisco Board of Directors! Welcome Girish. Thrilled to have you on the Board at Cisco.

As we enter into the phase of personal agents, the infrastructure requirements will continue to ride the exponential curve. Today, a tiny percentage of humanity (sub 2%) uses agents in any kind of power user capacity. I predict that in the next 12 to 15 months, we might have 30% of humanity using agents. If we live in a supply-constrained world with only 2% of humans using agents, we are gonna need to get far more creative when a much larger population becomes dependent on agents. The point being that the supply shortage on infrastructure for power, compute, memory, network bandwidth, and data center capacity seem durable. The answer to this is not just to build more datacenters, but also get the most out of existing ones. This is why USFP is such an important innovation. The demand will evolve to not just for a couple hundred thousand GPUs coherently clustered within a datacenter which is where we are today, but a future where we approach close to a million or more GPUs coherently clustered within a single datacenter. We at @Cisco are delighted to continue to keep partnering with @nvidia to push the limits of physics. We are also obsessed with combining the bandwidth density with the practicality of easy implementation. USFP scales bandwidth 4x with 16 lanes at 400Gb/s scalable to 32 lanes, coupled with 1.3x power efficiency. The other key point is that it’s built, deployed, serviced, and managed the same way as today’s pluggables. Thanks to all the members of both teams that worked tirelessly to making this happen. Read the details below on post from @ChuckRobbins 👇🏾

The pace at which software reconstruction will happen will be staggering. Fascinating times. 👇🏾

None however are contradictory concepts. Great to see you @villaumbrosia. Congrats on a fantastic event. Love enthusiastic product people that want to learn. This is an exciting time to be alive in tech. Possibilities are limitless.

💯. The agentic breakthrough we need is a 1,000,000X token efficiency acceleration for agents. Much easier at this point to figure out a way to use less than build more. Current course and speed keeps us in a perpetually supply constrained world, which is ironic given that AI is the abundance engine. But the good news is that more compute and infra is being built all over.

Thanks for having me on the pod @snowmaker. One of the most fun convos in a while. 🙏🏽

I just realized that it is pretty pointless posting this on X. No one that really needs the help would actually benefit from this post 🙈

Yes, but highly likely that’s about to change. I might be wrong on timing but not on the end-state

That’s bonkers! 👇🏾

I am blown away at the degree of disadvantage someone is in if they are a leader of a company and not on X. Like literally, how does that even work?

How do software companies adjust to this world where all software effectively gets to be open-sourced due to AI-powered reverse engineering? Frankly even the open source model could get disrupted because opensource assumes that a reliable albeit less attractive margin business and monetization vector that is available for the software developer is a services/support layer on top of free software. But we now can have universal agents as a layer above the software. So the company that builds the best universal agents that deliver a basket of services and support on top of the opensource software might end up becoming the new business model. The differentiator is the best performing agents as a layer of service and support sitting on top of the software. This will create a fair bit of disruption in classical software models. Insane!

It’s actually very similar to what Facebook has done with most of their major products. Their sequence has been to perfect user growth before worrying about monetization. It is truly the right way to do it In consumer tech. It doesn’t work as well in the enterprise because most enterprise buyers won’t buy anything that might get them locked in. So they want predictability upfront. But for consumer tech, especially with an ad supported business model, this is a very common mechanism. Also because their ad buys are more effective once they have a user base. @dee_bosa

Three worries every CEO should have about AI 1. Agent safety & security We need to rethink cyber defense. Attacks will happen at machine speed. Our defenses need to keep up and also operate at machine scale. Human scale defenses won’t suffice. 2. Token economics (or Tokenomics) A company’s or country’s ability to produce tokens efficiently and securely will shape its economic strength and security posture. Every CEO should be thinking of building a muscle in their company for being token efficient. 3. Agents between brands and customers If everyone has a personal agent handling purchases and services, those agents could become the new gatekeepers. CEOs should ask whether customers will still come directly to their brands, or rely on their agents to decide what to see and buy. These are structural shifts, not minor side effects of AI. Companies need to think through what a world full of personal agents means for their business, then keep adjusting as that world takes shape.