I am so much enjoying reading John Chamber's book, "Connecting the Dots-Lesson for Leadership in a Startup World," that I have pulled some elements from it that could portend trouble ahead for Nvidia. I am not predicting that Nvidia will go under quickly or anything like that. They have tremendous assets and momentum. But I am in the strategic planning business using scenarios; so why not think more openly? Here are the six ideas from John Chambers that Jensen Huang might want to ponder:
1. Great success attract great competitors, in all forms, large and small. In today's world even small competitors can be dangerous. Winning against competitors is not an easy game. Chambers also suggest that over-focusing on competitors is backward looking. He suggest looking forward to industry transitions and figuring those out and getting a leading position there. It is easy to lose track of this when current competition is also attacking. But Nvidia has to play the transition issue correctly.
2. Great power attracts others who want to use it for their purposes. U.S. political leaders in their concern about the rise of China want to use the power that Nvidia has to address those so-called "national security" concerns. This is what is bothering Jensen now as he sees those interests not aligning with market and industry realities. Building his company in a silo-ed market is truly dangerous considering the barely out of infancy of the whole AI industry. A mistake here could be very costly. Chambers suggest having clear winning end points and playing out the entire games (using scenarios) is key here.
3. Chambers is really clear that doing "too much of the right thing" can kill you. This is a form of the innovators dilemma, as protecting current success and making incremental improvements IS NOT innovation. He suggests that a company must disrupt itself. This is very hard to do with a Board being too conservative and focused on current stock prices. So yes, Nvidia can be disrupted by others, which seems to be what DeepSeek is showing.
4. Chambers suggest that charting future disruption means thinking big and sometimes taking big risks. As AI is in its infancy, clearly there is room for transitional moments and step changes. Being blind-sided by one of those can kill a company. Chambers explains how CISCO managed through some of those. It took some heart-rending work to do it. This is about the people running the place. Chambers heart-breaking explanation on the fall of Wang Computer lays this out. A brilliant creative scientific mind, just got attached to his own fears and missed a turn. This is another example of how people find it very difficult to deal with total context shifts. Maybe Jensen has an internalized belief that could cause him to mis-play a market transition as Dr. Wang did.
5. In thinking through scenarios Chambers also isolate what I call macro-scenario shifts. This is when larger scale forces impact those at lower levels. This of the recent storms in Texas where the weather system destroyed land-based systems. In CISCO's past the collapse of the internet bubble was such a case. Clearly in light of the global implications of AI, its energy and water use issues, its massive capital needs, and other issues expose market developments to macro-level shifts. Some of this work requires thinking about the unbelievable. Chambers suggest that talking to customers and diverse group of people and reading small signals can help here. I trust Jensen and his team are doing some of that.
Again, I am not suggesting that any of the above will happen, but that in some form they CAN happen. Thinking them through and developing paths forward would be helpful to Nvidia.
I am sure that Jensen has some of the smartest people in the world advising him, and a little unknown like me can be largely ignored. But here is something from John Chambers, Chairman Emeritus of Cisco Systems from his book, "Connecting the Dots."
"You have to compete in the moment but also rise above the short-term wins and problem to think 3, 5, and even 10 years out to pursue bigger and bolder dreams.
At Cisco, we were sometimes too early or we took on too much, but the reason we ultimately stayed on top is that we focused on connecting the dots. We developed a playbook for everything from how we acquired companies to how we managed people, how we dealt with customers to how we digitized countries."
This is the kind of thinking that both micro and macro scenario analysis tools can help with. Micro scenarios target smaller areas like product market evolution. Macro scenarios look at the broader forces shaping the larger business environment. Having both types in dialogue with each other in the strategy process of a company is how playbooks that Chambers is talking about get developed.
Here are two stories from the NYTimes that point toward my SW corner scenario. They argue for more nationally and locally related regulation and oversight of AI that pushes against broad standards and protection for AI services companies.
For a sense of the global silos that might be built read this from Scientific American's email blast:
AI Arms Race
Talk of an AI arms race is heating up with Meta CEO Mark Zuckerberg’s announcement that Meta will be consolidating its AI teams into its new Superintelligence Labs. This reorganization comes as Meta’s AI models have been falling behind those of competitors. Zuckerberg has been splashing out huge sums to lure star AI experts from rivals like OpenAI, DeepMind, and Anthropic. Though poached employees were rumored to have received $100-million signing bonuses, TechCrunch reported that no such bonuses were given, though the new hires did receive “hefty multimillion-dollar pay packages.” Meta even spent $14.3 billion for a large stake in data startup Scale AI to bring its CEO, Alexandr Wang, on board as Meta’s chief AI officer.
Meta’s rivals aren’t standing still. OpenAI, Anthropic, and xAI have been raising fresh funding. In China, AI companies enjoy significant state backing, and Zhipu AI has been securing government AI contracts in numerous countries. The strategy, according to an OpenAI post, is to “lock Chinese systems and standards into emerging markets before U.S. or European rivals can, while showcasing a ‘responsible, transparent and audit-ready’ Chinese AI alternative.” The U.S. Commerce Department added firms like Zhipu and others to export blacklists, cutting off access to critical U.S. components for AI development. Meanwhile, the Pentagon is actively courting top U.S. AI firms to use frontier AI models to streamline military logistics, improve healthcare for service members and bolster cyber defense. Tech execs have even joined the ranks of a new Army Reserve unit called Detachment 201 (the “Executive Innovation Corps”), with officers from Meta, OpenAI and Palantir serving as reserve lieutenant colonels to lend their expertise to military AI projects.
If this arms race talk is giving you flashbacks to the 1980s, then here’s a video from an AI-generated YouTube channel that features AI-generated 80s-style tunes along with AI-generated images that resemble a version of the 1980s somewhere else in the multiverse. Apparently, AI is also racing to take over YouTube.
For the latest in tech, follow me on X, Instagram and Bluesky @denibechard.
I am so much enjoying reading John Chamber's book, "Connecting the Dots-Lesson for Leadership in a Startup World," that I have pulled some elements from it that could portend trouble ahead for Nvidia. I am not predicting that Nvidia will go under quickly or anything like that. They have tremendous assets and momentum. But I am in the strategic planning business using scenarios; so why not think more openly? Here are the six ideas from John Chambers that Jensen Huang might want to ponder:
1. Great success attract great competitors, in all forms, large and small. In today's world even small competitors can be dangerous. Winning against competitors is not an easy game. Chambers also suggest that over-focusing on competitors is backward looking. He suggest looking forward to industry transitions and figuring those out and getting a leading position there. It is easy to lose track of this when current competition is also attacking. But Nvidia has to play the transition issue correctly.
2. Great power attracts others who want to use it for their purposes. U.S. political leaders in their concern about the rise of China want to use the power that Nvidia has to address those so-called "national security" concerns. This is what is bothering Jensen now as he sees those interests not aligning with market and industry realities. Building his company in a silo-ed market is truly dangerous considering the barely out of infancy of the whole AI industry. A mistake here could be very costly. Chambers suggest having clear winning end points and playing out the entire games (using scenarios) is key here.
3. Chambers is really clear that doing "too much of the right thing" can kill you. This is a form of the innovators dilemma, as protecting current success and making incremental improvements IS NOT innovation. He suggests that a company must disrupt itself. This is very hard to do with a Board being too conservative and focused on current stock prices. So yes, Nvidia can be disrupted by others, which seems to be what DeepSeek is showing.
4. Chambers suggest that charting future disruption means thinking big and sometimes taking big risks. As AI is in its infancy, clearly there is room for transitional moments and step changes. Being blind-sided by one of those can kill a company. Chambers explains how CISCO managed through some of those. It took some heart-rending work to do it. This is about the people running the place. Chambers heart-breaking explanation on the fall of Wang Computer lays this out. A brilliant creative scientific mind, just got attached to his own fears and missed a turn. This is another example of how people find it very difficult to deal with total context shifts. Maybe Jensen has an internalized belief that could cause him to mis-play a market transition as Dr. Wang did.
5. In thinking through scenarios Chambers also isolate what I call macro-scenario shifts. This is when larger scale forces impact those at lower levels. This of the recent storms in Texas where the weather system destroyed land-based systems. In CISCO's past the collapse of the internet bubble was such a case. Clearly in light of the global implications of AI, its energy and water use issues, its massive capital needs, and other issues expose market developments to macro-level shifts. Some of this work requires thinking about the unbelievable. Chambers suggest that talking to customers and diverse group of people and reading small signals can help here. I trust Jensen and his team are doing some of that.
Again, I am not suggesting that any of the above will happen, but that in some form they CAN happen. Thinking them through and developing paths forward would be helpful to Nvidia.
I am sure that Jensen has some of the smartest people in the world advising him, and a little unknown like me can be largely ignored. But here is something from John Chambers, Chairman Emeritus of Cisco Systems from his book, "Connecting the Dots."
"You have to compete in the moment but also rise above the short-term wins and problem to think 3, 5, and even 10 years out to pursue bigger and bolder dreams.
At Cisco, we were sometimes too early or we took on too much, but the reason we ultimately stayed on top is that we focused on connecting the dots. We developed a playbook for everything from how we acquired companies to how we managed people, how we dealt with customers to how we digitized countries."
This is the kind of thinking that both micro and macro scenario analysis tools can help with. Micro scenarios target smaller areas like product market evolution. Macro scenarios look at the broader forces shaping the larger business environment. Having both types in dialogue with each other in the strategy process of a company is how playbooks that Chambers is talking about get developed.
Here are two stories from the NYTimes that point toward my SW corner scenario. They argue for more nationally and locally related regulation and oversight of AI that pushes against broad standards and protection for AI services companies.
https://www.nytimes.com/2025/06/26/technology/ai-elections-democracy.html?searchResultPosition=7
https://www.nytimes.com/2025/07/01/us/politics/state-ai-laws.html?searchResultPosition=1
For a sense of the global silos that might be built read this from Scientific American's email blast:
AI Arms Race
Talk of an AI arms race is heating up with Meta CEO Mark Zuckerberg’s announcement that Meta will be consolidating its AI teams into its new Superintelligence Labs. This reorganization comes as Meta’s AI models have been falling behind those of competitors. Zuckerberg has been splashing out huge sums to lure star AI experts from rivals like OpenAI, DeepMind, and Anthropic. Though poached employees were rumored to have received $100-million signing bonuses, TechCrunch reported that no such bonuses were given, though the new hires did receive “hefty multimillion-dollar pay packages.” Meta even spent $14.3 billion for a large stake in data startup Scale AI to bring its CEO, Alexandr Wang, on board as Meta’s chief AI officer.
Meta’s rivals aren’t standing still. OpenAI, Anthropic, and xAI have been raising fresh funding. In China, AI companies enjoy significant state backing, and Zhipu AI has been securing government AI contracts in numerous countries. The strategy, according to an OpenAI post, is to “lock Chinese systems and standards into emerging markets before U.S. or European rivals can, while showcasing a ‘responsible, transparent and audit-ready’ Chinese AI alternative.” The U.S. Commerce Department added firms like Zhipu and others to export blacklists, cutting off access to critical U.S. components for AI development. Meanwhile, the Pentagon is actively courting top U.S. AI firms to use frontier AI models to streamline military logistics, improve healthcare for service members and bolster cyber defense. Tech execs have even joined the ranks of a new Army Reserve unit called Detachment 201 (the “Executive Innovation Corps”), with officers from Meta, OpenAI and Palantir serving as reserve lieutenant colonels to lend their expertise to military AI projects.
If this arms race talk is giving you flashbacks to the 1980s, then here’s a video from an AI-generated YouTube channel that features AI-generated 80s-style tunes along with AI-generated images that resemble a version of the 1980s somewhere else in the multiverse. Apparently, AI is also racing to take over YouTube.
For the latest in tech, follow me on X, Instagram and Bluesky @denibechard.
—Deni Ellis Béchard, Senior Reporter, Technology