Big Technology Podcast: OpenAI’s $100 Billion Funding Round, OpenClaw Acquired, AI’s Productivity Question — With Aaron Levie

Host: Alex Kantrowitz
Guest: Aaron Levie, CEO of Box
Date: February 20, 2026

Overview

This episode dives into some of the most significant developments in AI and the tech ecosystem:

• OpenAI’s monumental, possibly $100+ billion, funding round and what it signals for the AI sector
• OpenAI’s acquisition of OpenClaw, a viral agent technology, and the implications for the future of agents and software
• The ongoing debate regarding AI’s actual impact on productivity, tackling both optimistic business cases and skepticism based on recent studies
• Guest Aaron Levie, known for his engaging and thoughtful analysis as Box’s CEO, brings firsthand insight into both the enterprise cloud world and the evolving AI landscape.

The tone is candid, pragmatic, and occasionally playful, with both host and guest openly musing on industry drama and future trajectories.

Key Discussion Points & Insights

1. OpenAI’s Massive $100 Billion+ Fundraising Round

[02:41 - 23:36]

The Funding Details and Industry Context

• OpenAI is moving towards a record-breaking $100B+ round, with SoftBank, Amazon, Nvidia, and possibly Microsoft involved.
  • SoftBank reportedly with $30B, Amazon as much as $50B, Nvidia possibly $30B.
• Alex and Aaron compare these numbers to historic IPOs and gauge what this influx means for AI’s prospects.

Is AI Overhyped or Justified by Market Size?

• Aaron Levie:

  “We're looking at a really, really small percentage of the total change that is going to happen as a result of this. So we're in the earliest innings... But when you're talking about just intel, like one of the most fundamental fabrics of the economy in the next century, it's just entirely reasonable.” [05:33]

• The market for AI is expected to be in the tens of trillions, comprising chip and AI providers, app layers, and more.

• Multiple giants can coexist profitably; even if Google, Anthropic, or others catch up, the AI pie is enormous.

Additive Growth or Market Displacement?

• Discussion of whether AI’s growth will add to the economy or cannibalize existing sectors.

• Aaron Levie:

  “I kind of look at it as tens of trillions of dollars are spent on knowledge workers... could the major labs and applications take a 5–10% fee on that? That's sort of how you get to the math...” [11:04]

• Inference (running AI models for practical use) is increasingly profitable, and consumers will see business models like hyper-targeted advertising adopted by AI platforms.

The Strategic Dance Between OpenAI and Nvidia

• Early rumors had Nvidia committed to investing up to $100B in OpenAI; current reporting suggests closer to $30B.
• Alex and Aaron decode the signals, concluding that both companies seek to cement mutual dependency, with fluid dealmaking dictated by changing market needs rather than drama.
  • “We’re doing palm reading for the AI industry...” – Aaron Levie, [19:42]
  • Alex: “This whole thing was basically a signal from [Nvidia CEO Jensen Huang] to [OpenAI]: you better perform.” [21:18]
  • Aaron: “I don’t think OpenAI has a challenge raising money... Nvidia just needs to sell chips to OpenAI.” [21:35]

2. AI Hype vs. Reality: The India AI Summit and Leadership Drama

[23:52 - 29:30]

Claims of Superintelligence & Industry Dynamics

• At the India AI Summit, Sam Altman and Dario Amodei (Anthropic) make bold statements:

  • Sam: “We may only be a couple of years away from early versions of true superintelligence... by the end of 2028, most of the world’s intellectual capacity could reside inside data centers.” [24:15]
  • Dario: “Only a small number of years left for AI models surpassing the cognitive capabilities of most humans for most things.” [25:43]

• Aaron’s take: These statements, while aggressive, are reasonable “based on the trajectory” and definitions the leaders use. There are nuances around the meaning of “intelligence,” but rapid progress is clear.

  • Aaron: “That seems to be totally reasonable based on the trajectory we’re on. And I would bet that Sam has... a far higher bar for... intelligence...” [24:32]

The “Hand-holding” Meme and Industry Rivalry

• At the summit, an awkward photo of AI CEOs failing to join hands becomes a meme. Alex jokes:

  “If they can't figure out a way to hold hands for a picture, should we trust them to handle AI alignment?” [27:24]

• Aaron: “It's a great conundrum that we face, this microcosm of a broader issue...” [27:46]

3. Model Progress and the Underhyped Advance of Anthropic’s Claude

[29:30 - 33:24]

• Anthropic’s Sonnet 4.6 shows a major leap over 4.5, with improvements across accuracy in complex public sector, legal, and healthcare tasks:

  • Public sector accuracy: 77%→88%;
  • Healthcare: 60%→78%;
  • Legal: 57%→69%. [30:18–30:35]

• Aaron Levie:

  “The progress of these jumps that we’re seeing... I think that same trend is going to come to other fields of knowledge work.” [30:35]

4. OpenClaw Acquisition and the New Paradigm in Agents

[36:33 - 46:59]

What is OpenClaw & Why is it Important?

• OpenClaw’s innovation: always-on, semi-autonomous “agent” that runs on users’ local machines, engaging proactively with tasks and users, not just passively awaiting commands.

  • “It gives you a little bit of a peek into what the future could be where you don't have these agents that you only sort of spin up and spin down...” – Aaron Levie [36:33]

• OpenClaw is seen as moving AI “agents” from one-off, user-triggered scripts to persistent, background co-workers that can handle multi-step or ongoing tasks.

What This Means for the Software Industry

• The future of software is API-first, with agents acting as primary users of applications, and humans collaborating with both agents and other people.

• Aaron Levie:

  “It’s becoming clear that the future of software has to be API first, but also enable human interaction for verification, collaboration with agents and people and working on the output.” [41:53]

• The business opportunity is for software providers like Box to serve as the secure, permissioned content platform for both agents and end-users, enabling new workflows while maintaining data safety:

  “We want to be the platform layer that connects all of that.” [42:40]

• Aaron also highlights the practical limits and risks (“blast radius”) of giving agents too much control, citing recent Amazon outages caused by overzealous AI automation. [45:16–45:34]

5. Is AI Delivering on Productivity? The Data and the Anecdotes

[46:59 - 56:21]

Mixed Signals from the Field

• Despite industry hype, a recent survey (Fortune, 2026) of 6,000 CEOs finds:
  • 2/3 use AI, but only ~1.5 hours/week
  • Only 10% reported an impact on productivity or employment over the last 3 years
  • 25% not using it at all in the workplace
  • 90% see “no impact” on productivity or jobs so far [48:16]

Aaron’s Analysis:

• The productivity impact is real but uneven—already profound among developers and in tech, where code is the medium and teams are primed to exploit AI.

  “In engineering we have products that we build five times faster because of AI coding... We will be able to solve significantly more problems.” [49:03]

• The “rest of knowledge work” is slower to change due to less tech fluency, less adaptable workflows, and often inadequate data systems or training.

• The next productivity leap will happen as workflows, data, and culture catch up—a process that took years during previous tech revolutions, like the shift to personal computers.

• Aaron on future outlook:

  “People should be probably prepared for this [AI adoption] will come from more areas of knowledge work. I’m the biggest optimist on the jobs impact of that, so I don’t see that as a scary thing. I think it’s just going to mean companies will have to sign up to do way more for their customers... We will wake up in five or ten years and it’ll actually kind of feel like relatively normal...” [54:35]

• The net result: more competitive, customer-focused businesses, not mass unemployment or disruption.

Notable Quotes & Memorable Moments

On the scale of the AI industry:

“If you’re talking about intelligence across the entire economy, you can get to pretty large numbers in a pretty reasonable way.” — Aaron Levie [09:24]

On the future of software:

“API-first, but also enabling human interaction ... It's becoming clear that the future of software has to be API-first, but also enable human interaction for verification, collaboration with agents and people, and working on the output.” — Aaron Levie [41:53]

On OpenClaw and agents:

“What if that agent is running on its own and it had access to your computer and your browser and all the services, and it’s just running on an ongoing basis? … That is a very new way to think about agents.” — Aaron Levie [36:33]

On meme culture and leadership:

“If they can't figure out a way to hold hands for a picture, should we trust them to handle AI alignment?” — Alex Kantrowitz [27:24]

On productivity claims:

“In engineering ... we’ll be able to ship significantly more capabilities to our customers... It’s just now a thing we do, because we have to deliver more and more value…” — Aaron Levie [49:03]

On the path ahead:

“We will wake up in five or ten years and it’ll actually kind of feel like relatively normal... We just have incrementally better consumer experiences and better services.” — Aaron Levie [54:48]

Timestamps for Key Segments

• OpenAI Fundraising & Market Analysis: 02:41–23:36
• India AI Summit & CEO Dynamics: 23:52–29:30
• Claude/Anthropic Model Progress: 29:30–33:24
• OpenClaw, Agents & Future of Software: 36:33–46:59
• AI & Productivity Debate: 46:59–56:21

Final Takeaways

• The magnitude of AI funding and the pace of technical progress continue to accelerate, with multiple players (OpenAI, Anthropic, Google, Nvidia) now established and huge market value at stake.
• The future of work will be shaped by AI “agents” and seamless human-AI collaboration, requiring software firms to build API-first platforms and rethink user experiences for both people and autonomous assistants.
• While concrete productivity gains are clear in engineering, broader economic effects remain slow—yet history suggests disruption is cumulative, not sudden.
• Despite industry rivalries and meme-worthy moments among AI leaders, consensus is that massive, if uneven, transformation is underway.