Key Moments
How Jeetu Patel Runs Cisco Like the World’s Largest Startup
Y CombinatorKey Moments
Cisco is repositioning itself as the "picks and shovels" provider for the AI gold rush, aiming to build infrastructure that enables AI, not just optimizes costs. Their hyperscaler AI business has already seen $9.3 billion in orders in two years, vastly exceeding initial projections.
Key Insights
Cisco's hyperscaler AI business secured $9.3 billion in orders within two years, significantly surpassing their initial $1 billion projection and doubling their second-year target.
Patel emphasizes that AI should unlock new capabilities and solve previously intractable problems, rather than solely focusing on cost reduction or job displacement.
Cisco is employing a "rule of thirds" for its leadership team: one-third internal experts, one-third external market hires, and one-third founders from acquired companies.
The company experienced significant initial resistance from its 32,000 engineers towards AI adoption, leading to a strategy where employees were guaranteed they'd lose their jobs if they *didn't* use AI.
Cisco is building an integrated, co-designed infrastructure spanning silicon, optics, systems hardware, and software, with silicon development cycles lasting up to five years, while AI model development cycles are as short as weekly.
Patel's personal journey involved escaping a dangerous situation in India, working as a waiter, and overcoming personal insecurities to eventually lead significant transformations at companies like EMC, Box, and now Cisco.
Cisco as the AI infrastructure provider for the gold rush
Jeetu Patel, President and Chief Product Officer at Cisco, describes the company's strategic pivot to become the essential "picks and shovels" provider for the AI era. This means building the foundational infrastructure – from networking GPU clusters to securing AI agents – that will power the current AI revolution. He contrasts this with the approach of companies simply hoping to strike gold. Cisco's ambition is to ensure AI can run safely and reliably at scale. This transformation is relatively recent, as this positioning wasn't associated with Cisco just four years ago, indicating a rapid and significant shift for the large enterprise.
Leading transformation with a founder's mindset
Patel emphasizes that significant company transformations are often driven by the team's efforts, not just leadership. His role has been to set the direction, hire the right people, and establish mechanisms for market targeting. He likens his approach to that of a founder, especially during market shifts. This means having a sense of ownership and a willingness to intervene across different departments if something isn't working. He believes this "founder's mindset" allows for a different pace of work, enabling the company to operate like the "world's largest startup" by combining speed with scale. He even feels like a "late-stage co-founder" of Cisco, despite joining 36 years after its inception.
Balancing experience with entrepreneurial drive
To manage such a large-scale transformation, Cisco employs a "rule of thirds" for its leadership: one-third are seasoned Cisco internal experts who understand large-scale operations, one-third are external hires with deep market knowledge, and one-third are founders from acquired companies. This mix aims to balance operational efficiency with fresh market perspectives and entrepreneurial agility. Patel acknowledges that while a purely founder-driven approach can lead to chaos, the blend ensures both strategic vision and effective execution. He stresses the importance of empowering these acquired founders with even broader authority than they had in their own companies.
The AI opportunity: Infrastructure demand and agent control
Patel identifies two primary challenges and opportunities for Cisco in the AI era. The first is the sheer scale of infrastructure demand; with less than 2% of the world's population using AI agents intensely, the current infrastructure is already being consumed. He projects a massive increase in demand as more people adopt AI, leading to a significant supply shortage. The second challenge is the reliability and safety of AI agents, referencing the 'paperclip maximizer' problem, where agents might act with unintended consequences or even malicious intent. Cisco aims to provide the necessary safety, security, and monitoring capabilities to ensure AI is trustworthy and doesn't become a source of fear, highlighting its dual role as a networking, security, and device data leader.
AI's impact: More engineers, not fewer
Contrary to the notion that AI will primarily lead to job cuts, Patel argues that Cisco will likely need *more* engineers. The goal is not just efficiency, but leveraging AI to unlock innovative insights and solve previously unimaginable problems. He points out that AI advancements often create new bottlenecks, such as code review when programming is automated, or defining what to build when code reviews are automated. To foster AI adoption among its 32,000 engineers, Cisco adopted an unconventional strategy: emphasizing that employees would be at risk of losing their jobs if they *didn't* embrace AI, drawing a parallel to not hiring someone who can't use a computer. This approach, combined with providing unlimited AI tokens and extensive training, aimed to drive widespread adoption and adaptation.
Accelerating hardware and software development cycles
Cisco develops silicon, optics, systems hardware, and software. While AI's impact on software development is rapid, hardware and silicon cycles are inherently longer, with silicon design potentially taking up to five years. Patel explains that his team must plan for mass production five years out, making strategic investments today. However, AI is beginning to compress these cycles. Silicon design might take 18-30 months, operating systems 12-18 months, and AI models and applications can have planning cycles as short as weekly. The strategic advantage lies in building a cohesive, co-designed infrastructure where all these layers work in sync, a feat difficult for competitors to replicate. This integrated approach is key to developing products that can scale to billions of dollars in revenue.
Massive data center expansion and the "not overbuilding" argument
The current build-out of data centers is unprecedented. Patel explains that unlike the dot-com bubble, where infrastructure was built in anticipation of demand, today's AI infrastructure is being consumed almost immediately. The demand is so high that there is a critical shortage. He highlights that an AI agent consumes 450% more network bandwidth than a human for the same task. He dismisses concerns about overbuilding, stating that with less than 2% of the population intensely using agents, the infrastructure needed for 25-50% adoption will be astronomically larger. He uses his personal experience of having over 170,000 unread emails, which an AI agent helped him manage, as an example of the vast data processing required, underscoring the immense compute and bandwidth demands.
A founder's journey: From India to Silicon Valley leadership
Patel shares a compelling personal story, starting from a difficult childhood in India marked by his father's fraudulent activities and abuse. He escaped to the US at 19, working as a waiter at Sizzler while attending college. Despite early academic struggles and a stutter, he found his voice by entertaining customers. A pivotal moment was an internship at DocuLabs, where he eventually helped secure funding to buy the company he had interned at, even as a student earning minimum wage. He led that company for 17 years, but realized it didn't align with his ambition to work in software and the Silicon Valley ecosystem. His tenure at EMC, where he learned more in a year than in his previous 17 years, and his time at Box, where he helped grow its valuation significantly, prepared him for his current role at Cisco, which he joined after a compelling call from CEO Chuck Robbins.
Lessons for aspiring entrepreneurs and innovators
Patel imparts several key lessons. Firstly, ambition, not innate ability, often dictates one's ceiling. He emphasizes hard work, thinking big, and the power of compound growth (a 1.27% daily improvement compounding to 100x over a year). He stresses the importance of long-term relationships and teamwork, and urges founders to align their ambition with their business model for fulfillment. He also advises against succumbing to pessimism when joining large companies, urging instead to learn from them, as all large companies were once startups. He encourages young people to seize the current "golden age" of technology and AI, recognizing the extraordinary opportunity to make a real impact on the world. His own journey highlights that even with a difficult start, the platform and opportunities available, especially in the US, can lead to immense possibilities if not wasted.
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Running Cisco Like a Startup: Key Principles
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Cisco views itself as the 'picks and shovels' company for the AI gold rush, providing the necessary infrastructure to support AI's massive growth and ensuring it operates reliably and securely.
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Mentioned in this video
A company where Jeetu Patel started as an intern and later invested in and managed, marking her first entrepreneurial venture.
A large company where Jeetu Patel worked and learned significantly, described as a valuable experience despite initial dislike.
A highly regarded organization that Jeetu Patel commends, especially for its role in fostering entrepreneurship and innovation.
A major technology company that Jeetu Patel is transforming by applying a founder's mindset and focusing heavily on AI infrastructure and integration.
An AI research organization that Cisco partnered with as a design partner, receiving dedicated full-time employees.
A data analytics company that Cisco is collaborating with, contributing to their strategy as a vital infrastructure provider in the AI era.
A ride-sharing company whose experts joined Cisco via the acquisition of Galileo, contributing to the Splunk team.
An AI research laboratory whose experts joined Cisco after the acquisition of Galileo, contributing to the Splunk team.
Jeetu Patel's mentor at EMC, who taught her more in the first year than she learned in 17 years managing her own business.
CEO of Cisco, who recruited Jeetu Patel and offered her significant autonomy to focus on product.
President and Chief Product Officer at Cisco, discussed for her approach to running the company like a startup and her focus on AI.
Co-founder of Box, where Jeetu Patel previously managed product.
Mentioned as an example of a con artist, drawing a parallel to Jeetu Patel's father's fraudulent activities.
An AI model developed by OpenAI that Cisco partnered with, contributing to the company's AI integration efforts.
An AI agent that Jeetu Patel uses to manage her email, significantly reducing her inbox backlog.
A company acquired by Cisco, whose experts from DeepMind and Uber now contribute to Splunk's team, enhancing security and monitoring capabilities.
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