Jason Calacanis hosts a discussion at CES 2026 with Bob Sternfelt, senior partner at McKinsey & Company, and Hamant Tanasia, managing director at General Catalyst venture capital firm with $40 billion in assets under management.

The conversation explores AI's transformative impact on business, comparing the current pace of change to the previous 30 years of technology evolution from PCs to mobile computing.

Key topics include enterprise AI adoption, workforce transformation, venture capital's new playbook of acquiring declining businesses, and the future of autonomous vehicles and robotics.

The discussion concludes with a nostalgic review of past CES innovations, from mobile phones to Palm Pilots, examining what current technologies might seem antiquated in 30 years.

The 10X Revenue Revolution in AI Companies

Anthropic demonstrated unprecedented growth, scaling 10x year-over-year multiple times, with General Catalyst investing at a $60 billion valuation that reached hundreds of billions.

"When we invested, was doing about 880. 10x year over year. 10x growth the year before. And then, and this last year they've announced this, they're growing another 10x or more" - Hamant

The compression of value creation means companies like Stripe took 12-13 years to reach $100 billion, while AI companies achieve similar valuations in 2-3 years with actual business growth backing the valuations.

McKinsey's Radical Workforce Transformation

McKinsey is executing an unprecedented organizational split: hiring 25% more client-facing consultants while simultaneously reducing non-client staff by 25%.

"We saved, we looked at it, we saved 1.5 million hours. But we're dividending that to solve more complicated problems and do different things" - Bob

AI agents generated 2.5 million McKinsey charts in six months, allowing consultants to move up the value stack to more complex problem-solving.

This represents the first time in firm history that growth occurs without total headcount growth, creating a new paradigm for professional services.

General Catalyst's Acquisition Strategy Revolution

General Catalyst raised $9 billion and acquired a nonprofit hospital in Akron, Ohio, converting it to create a testing ground for AI healthcare transformation.

"We bought it to actually have a place where we can work with our founders and transform with AI, create abundance and resilience for this health system" - Hamant

The strategy involves acquiring declining businesses with valuable customer bases to accelerate startup deployment, rather than traditional private equity optimization.

This creates a new asset class focused on transformation rather than optimization, targeting businesses facing disruption from AI.

The Skills Gap in an AI-First World

Three uniquely human capabilities remain irreplaceable: aspiration (setting goals), judgment (establishing parameters), and true creativity (orthogonal thinking).

"What can the models not do? Aspire. Set the right aspiration. Do you go to low Earth orbit? Do you go to the moon? Do you go to Mars? That's a uniquely human capability" - Bob

Educational systems must shift from 22 years of learning followed by 40 years of working to lifelong learning models, as skill half-life shrinks from 7 years to 3.6 years.

Young professionals should bypass traditional hiring processes by directly contacting CEOs with spec work and company improvement suggestions rather than relying on training programs.

The Physical AI Revolution in Manufacturing

50,000 US manufacturing jobs remain unfilled while demographics worsen, making robotics essential for competitive manufacturing costs against Chinese producers.

Korea leads with one robot per 10 workers, while Germany and China tie for second place, with the US trailing in third position.

Tesla's Optimus robot represents the most transformative technology product in human history, with potential for one-to-one human-to-robot ratios.

"Nobody will remember that Tesla ever made a car. They will only remember the Optimus" - Jason, after visiting Tesla's Optimus lab

Enterprise AI Adoption Reality Check

Large enterprises show massive AI technology uptake, but realizing value at scale proves harder than expected, creating tension between CFOs and CIOs.

"Typical non-tech CEO might say, hey, Bob, do I listen to my CFO or my CIO right now? CFO is saying, we've spent all this money. Why do we need to be the fast adopter?" - Bob

Every department needs AI teammates, with the critical question being whether they function as co-pilots providing efficiency or full pilots handling complete tasks.

Startup founders now universally use LLMs for job descriptions and AI-powered resume screening, eliminating traditional HR functions in resource-constrained environments.