Episode Overview

Title: Why AI will dwarf every tech revolution before it: robots, manufacturing, AR glasses from CES 2026
Podcast: All-In with Chamath, Jason, Sacks & Friedberg
Date: January 8, 2026
Guests: Bob Sternfels (Global Managing Partner, McKinsey & Company) and Hemant Taneja (CEO, General Catalyst)

The All-In crew gathers at CES 2026 with special guests to tackle the biggest topic of the decade: the world-altering acceleration and impact of artificial intelligence. The group discusses how AI is reshaping every industry, why its impact will tower over prior tech revolutions, the future of work and education, private capital's changing playbook, and the rise of robotics and physical AI. The latter half features a fun “gadget time-capsule” celebrating hits and misses from past CES innovations.

Key Discussion Points & Insights

1. AI’s Unmatched Acceleration and Societal Impact

• AI Dwarfs Past Tech Revolutions:
  "Everything we've seen over the last 30 years of technology... is going to be dwarfed in comparison to the impact that AI is going to have on society." - Jason Calacanis [00:06]
• Compared to the PC, Internet, and mobile revolutions, AI's pace and potential reach are on another level. The entire economic and innovation landscape is shifting around LLMs and agents.
• Explosion of CES and Industry Convergence:
  • CES 2026 is back, stronger and more cross-disciplinary than ever, reflecting how AI is central to every industry. "You see not only the technology leaders, the investors, but you see folks from almost every industry vertical that are here now..." - Bob Sternfels [03:25]

2. Compression of Innovation Cycles and Value Creation

• Companies now release transformative products and reach massive scale (e.g., $100M to $1B in revenue) in months rather than years.
• Anthropic as the Case Study:
  • Anthropic’s journey: $880M revenue jumping 10x YoY, now aiming for multi-billion-dollar run rates at staggering speed.
    "That business, when we invested, was doing about $880 million, which was a 10x growth from the year before... and they're growing another 10x or more." - Hemant Taneja [06:55]
  • OpenAI reportedly trends toward $20B revenue, showing how quickly winners are establishing vast market dominance.

3. Enterprise Adoption, AI Transformation, and Organizational Challenges

• Enterprises are leveraging LLMs at an unprecedented rate, but legacy non-tech companies struggle more to realize value.
• The Internal Dilemma for CEOs:
  • "Typical non-tech CEO might say, hey Bob, do I listen to my CFO or my CIO right now? ...CFO is saying we spent all this money, why do we need to be the fast adopter?... CIO saying are you fricking crazy? This is the moment..." - Bob Sternfels [09:46]
• Many firms stuck in "pilot purgatory"; real transformation demands aligning tech/policy/capital to break through.

4. Venture’s New Playbook: Buying Incumbents to Transform

• Venture capital firms, especially General Catalyst, are now acquiring struggling industry incumbents (e.g., health systems), not for traditional PE plays but as platforms for injecting AI and rapid transformation.
• "We're going to buy it so that we can take our startups and accelerate whether it's healthcare, financial services, or customer support and outsourcing..." - Jason Calacanis [13:39]
• This is seen as creating a new asset class—private capital as a force for radical transformation.

5. The Future of Work and Workforce Transformation

• Workforce Bifurcation at McKinsey:
  • "We're growing that [client-facing] body at 25% next year... At the same time... we're down 25% [non-client] with 10% increase in output." - Bob Sternfels [18:09]
• Client-facing employees “move up the stack” into more complex work, while support roles shrink, enabled by AI.
• This kind of simultaneous hiring + layoffs is unprecedented and marks a new paradigm.
• Societal Communication Challenge:
  • The need to explain rapid job transitions, new skills, and shifting entry pathways to the broader public.
    "What was it? Essentially it looks like a C corp with a bunch of engineers. But in the world where code self writes, what is that next level innovation?" - Hemant Taneja [21:14]

6. Skills for an AI-Infused World

• Human value migrates to:
  • Aspiration: Setting bold visions.
  • Judgment: Framing the right problems and parameters.
  • Creativity: Asking the right questions, not rote problem-solving.
  • "What can the models not do? Aspire... Human judgment... true creativity." - Bob Sternfels [23:40]
• Lifelong learning and resilience, rather than pedigree or credential, become paramount.
  • "Your relationship with learning is that it's a lifelong skilling and reskilling kind of an experience." - Hemant Taneja [27:53]

7. Rethinking Education for Lifelong Adaptability

• The current model—education for 22 years, then work for 40—is obsolete.
• New models:
  • Colleges as lifetime partners, not four-year vendors.
  • Skills must be fluid; workplace ROI for traditional degrees shrinks.
  • "For an employer, the return on investment that you give an employee... has shrunk by about half over the last 30 years..." - Bob Sternfels [28:58]
• The skill of coordinating/judging agentic teammates (AI) will be critical.

8. Physical AI: Self-Driving, Robotics & Manufacturing

• "2026 CES as self-driving CES... 2027 as robotics, humanoid robotics specifically." - Jason Calacanis [35:26]
• US innovation dominates, but manufacturing cost advantages skew to China. Winning the “physical AI” race, especially in robotics and next-gen manufacturing, is essential for strategic autonomy.
• "If you have good robotics models, what's next? You don't have a hardware capability that's like an API infrastructure that diffuses those models fast." - Hemant Taneja [38:41]
• Robotics revolution may take slightly longer than anticipated due to hardware diffusion challenges.

9. Gadget Time-Capsule: Hits, Misses, and Lessons

• Fun recap of past CES innovations (Motorola “brick” phone, Google Glass, Palm Pilot, Blackberry, Sony Discman, pagers).
• AR glasses:
  • "The new ones aren't much better. The form factor is better, but the utility isn't there yet." - Hemant Taneja [42:48]
• Theranos micro-blood analyzer:
  • The fraudulent, but still inspiring, vision of health-tech innovation.
  • "The challenge with this is... can you actually manufacture those nano devices... Technology wasn't there. But I think they will catch on to enable this." - Hemant Taneja [43:56]
• Comparing music hardware’s unreliability to current LLM “hallucinations.”
  • "My answer is the LLM hallucinations. Because... it's actually unreliable in a lot of ways. Just like the music was unreliable with this." - Hemant Taneja [49:19]
• Social and behavioral changes: nostalgia for “off” time leads to revived interest in basic tech (digital cameras, flip phones, pagers).

Notable Quotes & Memorable Moments

• "The tools of implementation as technology... keeps changing. So what the technologies can build today versus what the LLMs could do, let's say two years ago... is fundamentally different.”
  — Hemant Taneja [05:02]

• "We saved 1.5 million hours in search and synthesis last year. But we're dividending that to solve more complicated problems and do different things."
  — Bob Sternfels [18:09]

• "This is not private equity. This is about how do you transform incumbent entities into something different."
  — Bob Sternfels [14:34]

• "It's almost like we need to train people to go from being part of the orchestra to everybody being the conductor and everybody having their own orchestra of agents working for them."
  — Jason Calacanis [31:00]

• "Learning has to become much more fluid and we need to become a community of lifelong learners..."
  — Hemant Taneja [27:53]

• On Tesla’s Optimus robot:
  "No one will remember that Tesla ever made a car. They will only remember the Optimus and that he is going to make a billion of those... It is going to be the most transformative technology product ever made in the history of humanity."
  — Jason Calacanis [39:15]

Timestamps for Key Segments

| Segment | Topic | Timestamp | |---------|-------|-----------| | Opening framing: AI dwarfs prior revolutions | [00:06] | | Pace of enterprise innovation post-ChatGPT | [03:25] | | Startup speed & Anthropic case study | [06:29]-[06:55] | | Tech adoption in legacy industries | [08:14]-[09:30] | | New venture capital transformation playbook | [11:05]-[13:39] | | McKinsey: workforce bifurcation & future of work | [17:16]-[19:40] | | Societal, industrial, and youth career implications | [19:57]-[21:14] | | Skills for an AI world: aspiration, judgment, creativity | [23:35]-[24:40] | | Lifelong learning, education system overhaul | [27:07]-[28:58] | | Agents and teamwork between humans + AI | [30:09] | | AI in every department, redefining org charts | [32:24]-[33:52] | | The coming physical AI: self-driving, robots, manufacturing challenge | [34:18]-[39:15] | | Gadget time-capsule (phones, AR, Theranos, BlackBerry, pagers) | [40:53]-[51:09] |

Episode Tone and Style

• Energetic, candid, and irreverent with a mix of strategic vision, business storytelling, and nostalgia.
• Frequent banter, personal anecdotes, and wide-ranging industry references.
• Realism about disruption and opportunity—no sugarcoating the challenges for workers, businesses, or policymakers.

Summary Conclusion

This episode offers a front-row seat to how technology leaders perceive AI’s present and future: as the true epochal revolution, with the power to rewrite industries, labor markets, educational paradigms, and even society’s basic structures. It’s a robust, sometimes sobering, always insightful discussion on what it takes to thrive in the coming decade of AI—and which “ghosts” of techs past can still teach us about how fast fortunes can shift.