The Latest 20VC x SaaStr: NVIDIA’s $1T Forecast, Why Meta’s 16,000 Layoffs Are a Feature Not a Bug, and Adobe’s CEO is Out

Harry Stebbings, Rory O’Driscoll, and Jason Lemkin break down the biggest stories in tech and venture right now.

Harry Stebbings of 20VC, Rory O’Driscoll of Scale Venture Partners, and Jason Lemkin of SaaStr sat down to work through the week’s biggest stories: NVIDIA’s trillion-dollar forecast, a new wave of purposeful layoffs at Atlassian and Meta, what AI fluency actually means when you’re hiring, Anduril’s $20B army contract, Travis Kalanick back at the table raising at up to $20B, and Adobe — a company with one of the most beloved product suites in history — facing a leadership vacuum and a real disruption problem.

NVIDIA: $1 Trillion … and the Market Yawned

Jensen put a trillion-dollar revenue forecast on the table at GTC. The stock moved less than 1%.

That flat reaction is the real story. As Jason put it, you could just feel the energy: “This is summer at NVIDIA. They’re on fire on everything.” New hardware. Nemo Claw, their open-source model push. A partnership with Thinking Machines. Data centers in space. The company is firing on every cylinder simultaneously.

But Harry broke down why the number itself surprised no one: NVIDIA did $215B last fiscal year, the analyst forecast for next year was already in the mid-300s, and the “trillion dollar” headline was essentially a salesman’s round-up of two years of consensus estimates already priced in. The stock processed it in ten minutes.

What the announcement actually confirmed is the bigger bet: capex investment at these levels continues for four to five more years. When NVIDIA is doing $600B in revenue, the global capex spend behind it is probably north of $1.2 trillion. Jason’s view on the longer arc: cumulative revenue of $10 trillion over the next five to seven years is plausible, driven by inference running at scale across a growing share of the global workforce.

Rory flagged the one real tension in the math: token consumption may grow 3,000x over the next five years, but if the price per token falls 6x simultaneously, revenue growth is not linear. The bull case on NVIDIA requires demand to outrun price compression at a massive scale. So far, every data point says it is. But it’s a bet worth naming as a bet.

The counter-risk is real but so far theoretical. Inference prices keep falling. Customers are building on Google TPUs and Amazon chips. And railroad-boom-level capex assumptions require nothing to break for half a decade. Harry put the probability of something going wrong at around 30%. Not enough to bet against NVIDIA — but worth noting.

The Layoffs at Atlassian and Meta Are Not What They Look Like

Atlassian cut 1,600 people. Meta is reported to be heading toward 16,000 out of 79,000 — roughly 20% of its workforce. The coverage frames this as AI forcing companies to downsize. That framing misses what’s actually happening.

As Jason said plainly: “Neither of these companies has to lay off anybody.” Atlassian has substantial free cash flow. Meta’s operating margins are still in the 40s. These are not distress moves.

Rory laid out four categories of what’s actually driving this wave:

• First, companies that overhired in 2021 and are now correcting — using AI as a convenient explanation, but the efficiency metrics never justified the headcount.
• Second, businesses that were growing at 20% and are now growing at 2%, and need to give Wall Street what it wants. As Rory said: “Wall Street is simple. If you give them growth, they leave you alone. If you don’t give them growth, you better give them profitability. And if you don’t give them either, they’re going to bust your chops.”
• Third, companies where AI tooling has genuinely replaced functions that previously required humans — coding being the clearest example right now.
• Fourth, and this is the Meta case specifically: you spent tens of billions on compute. The depreciation is coming. You don’t have the operating cash flow to have both Nvidia and people. As Harry put it, “compute eats jobs.” That is literally what is happening at Facebook. The fifth category — which Jason added — is arguably the most important and most underappreciated: companies cutting not to shrink, but to restock. They don’t need 20 engineers who know C++. They need eight who are genuinely elite at building with AI. They’ll pay twice the salary for half the headcount. This is a talent shuffle happening in real time, and it probably should be happening at every company regardless of whether any of the first four factors apply.

The One Question That Tells You If Someone Is Actually AI Fluent

Harry asked Jason for a concrete hiring test. The answer was blunt.

“What commercial AI tool have you brought into your organization this month? That’s the test.”

Not which tools they’ve read about on Twitter. Not which demos they’ve watched. What did they actually buy, configure, deploy, and put in front of their team — in the last 30 days. Anyone on the bleeding edge has done this repeatedly. There are enough great products now that there’s no excuse for any functional leader — sales, marketing, engineering, product — to not have evaluated and partially deployed at least one agentic tool recently.

Jason was direct about where the bar actually sits in practice: “Of all even of the best startups I’ve invested in, maybe 30% of the management team meets this standard at best.” In general interviews, it’s single-digit percentages.

The role that matters right now isn’t a prompt engineer — that job existed for about a year and is already gone. It isn’t “go-to-market engineer” either, a title Jason thinks is also fading. The job is what Jason coined on the call: agentic deployment expert. Someone who finds the best tools, deploys them, trains them properly, and measures the output. From C-suite to junior.

Rory and Harry pushed back gently — anyone can learn this, provided they’re willing to put in the time. It isn’t a generational filter or a technical one. Harry made the point explicitly that it applies to investors too: if you’re not using these tools yourself, you probably shouldn’t be writing checks into them. Harry called Rory out directly as the most AI-equipped investor he knows — sitting genuinely at the bleeding edge in terms of using the tooling, understanding where the bottlenecks are, understanding constraints. That’s what good looks like on the fund side.

And critically: you do not need to be technical to do this. “You do not need to be even 1% technical,” noted Jason. If you’ve successfully deployed a piece of enterprise software — Salesforce, HubSpot, Outreach, anything — in the last few years, you have the skills to deploy AI agents. The only genuinely non-intuitive part is training them. Everything else is just software. The people who figure this out now become heroes in their companies. The people who don’t, as Jason said, are “going to get laid off because they’re not going to matter.”

Anduril Just Became the $20B+ Default OS for the U.S. Army

Anduril landed a $20B, 10-year army contract — five-year base with a five-year option — consolidating 120 separate procurement actions into a single enterprise agreement.

The structure is what matters. This isn’t a new program; it’s the army saying “you’re our prime supplier, let’s stop doing 120 separate contracts and just systematize this.” The product at the center appears to be Lattice, Anduril’s software connectivity layer that ties disparate hardware systems together in real time.

In modern conflict, you have seconds to respond to an incoming drone. You don’t have time for a slow connectivity protocol and you definitely don’t have time for a human in the loop. The military needs all its offensive and defensive systems talking to each other autonomously. Anduril’s product is becoming the default layer for that. The Pentagon has essentially said “you’re the dominant provider of this layer — let’s systematize the contract.” It picks them as the clear new prime.