Speaker · Updated
Jack Altman: latest market views
Benchmark
Summary
Jack Altman is a General Partner at Benchmark, the founder and former CEO of Lattice, and the host of the Uncapped podcast.
Chorus has 32 views from Jack Altman across 2 episodes on Uncapped with Jack Altman since October 29, 2026. Their latest calls: bullish on Anthropic, Sequoia Capital and Tesla; bearish on NVIDIA.
Where they stand
Their latest bullish or bearish call on each company.
- AnthropicBullish ·
- NVIDIABearish ·
- Sequoia CapitalBullish ·
- TeslaBullish ·
What they talk about most
- Venture capital & startups · 5
- Open-source AI models · 3
- Robotics & autonomous vehicles · 3
- Software & SaaS · 3
- AI infrastructure & data centers · 2
- AI pricing & unit economics · 2
- Frontier AI labs & model race · 2
- Enterprise AI adoption & AI software · 2
- Pharma & biotech · 2
- AI & jobs · 1
- AI: overall outlook · 1
- Anthropic · 1
The latest views
Newest first. Every quote is checked against the episode's transcript.
AnthropicBullish
Anthropic's IPO should go well and price in the expected range, with hedge funds as eager buyers.
The offering is large but not so big that enough capital won't be available. Hedge funds love the frontier labs and Anthropic in particular, so they will be the buyers and holders of the stock. Jack expects the IPO to price in roughly the range discussed and to go fine, with plenty of demand.
“my guess is it goes well, honestly. My guess is it comes out in this kind of price range. There's going to be a lot of buyers.”at 5:32
Uncapped with Jack Altman: Benchmark Breakfast #2 | November 12, 2026 ·
AI lab stock volatility is rational because their possible outcomes are far wider than a stable company's.
Coca-Cola's operating range is narrow, so its stock trades in a tight distribution. For a lab like Anthropic, the outcomes are not a small band around a likely revenue number. It could be 5 or 9, or something terrible could happen, so the range of outcomes is wide. Daily news can push the stock sharply one way or the other, so the volatility is a rational response to that uncertainty.
“the volatility is sort of rational. And it's rational because you think about Coca Cola stock. It's like the bands of what that company is going to do are very narrow.”at 9:34
Uncapped with Jack Altman: Benchmark Breakfast #2 | November 12, 2026 ·
NVIDIABearish
Nvidia will find it harder to ship chips to China and to be vocally pro-China and pro-open source.
Jensen Huang has argued for exporting chips to China, for open source, and for using Chinese models to strengthen an American AI epicenter. The spy allegations make it harder for chips to reach Singapore and China. Jack also thinks Jensen will find it hard to be publicly supportive of China and open source in the same way. Combined with anti-distillation pressure from the labs, this could change the landscape for Nvidia's China business. Nvidia's stock is already down about 30% from its peak.
“it'll be hard for chips to make it to Singapore and to China and all of that. And I also think it's going to be hard for Jensen to be vocally supportive of China and open source in the same way.”at 11:41
Uncapped with Jack Altman: Benchmark Breakfast #2 | November 12, 2026 ·
On net, the Nvidia news is positive for American open source, even as closed labs push their own case.
Frontier labs will likely push the message that closed source is the safer, cheaper option while the situation is unclear. Still, many people care about open source and correctly believe it makes sense. Jensen is not the only advocate, so the forces behind open source will largely offset the losses and leave American open source a net positive.
“I would still on net take the side that this is positive for American open source, though. There's too many people. It's not just Jensen.”at 16:47
Uncapped with Jack Altman: Benchmark Breakfast #2 | November 12, 2026 ·
Token buyers will eventually rationalize AI spend, so consumption grows but not at an exponential rate.
Within penetrated accounts, AI consumption will show exponential growth at first. Then buyers reach saturation for their tasks, decide the last model is good enough, and move to cheaper models. Spending then flattens instead of eating the whole margin. Growth continues because AI is still far from penetrating the rest of the economy and each new frontier model can drive another spending step-up. Jack expects that to happen fast by normal standards, but diffusion will take time and won't follow an infinite exponential path.
“at some point, then, what you see is the buyers of tokens get to a place where they decide, Okay, we're ready to rationalize costs. We have saturated the task.”at 23:57
Uncapped with Jack Altman: Benchmark Breakfast #2 | November 12, 2026 ·
AI infrastructure & data centers
The data center buildout will eventually overshoot and halt, and price per gigawatt cannot keep rising.
Jack says the odds of a massive buildout ending smoothly are effectively zero. At some point everyone will stop and admit they have overbuilt, and spending will fall sharply. He adds that the price per gigawatt cannot keep rising from $30B to $200B. Ground-level information suggests strength over the next 12 to 24 months, but the trend cannot continue forever and will need to find an equilibrium.
“There will come a moment when everybody screeches to a halt, and they say, we have just... Like, we gotta stop. We've overbuilt.”at 27:35
Uncapped with Jack Altman: Benchmark Breakfast #2 | November 12, 2026 ·
Robotics & autonomous vehicles
A lab demo of perfect robot control will come and cause a major stock rally, as scaled models reach robotics.
Under the bitter-lesson view, enough compute and model size applied to robotics could produce good robots and a very large S-curve, possibly bigger than coding. Jack expects one day a lab such as Tesla, OpenAI or Anthropic will demonstrate perfect control of a robot. That would drive a huge upward move in the stocks, and similar surprises will cause shocks both up and down before then.
“there will one day, there will be a demo where one of the labs will show that they have perfect control of a robot.”at 30:03
Uncapped with Jack Altman: Benchmark Breakfast #2 | November 12, 2026 ·
AI infrastructure & data centers
Americans broadly dislike AI and data centers, and tech has not yet connected with ordinary voters.
People resent AI billionaires and trillion-dollar companies dropping large, ugly data centers into their towns during a huge wealth creation event and telling them these are their jobs now. In Texas and other places, this sentiment is strong. Tech made progress connecting with DC but has done a poor job connecting with ordinary America, though it has started trying harder in recent months.
“We're like, America hates AI, big time. And America hates data centers.”at 31:38
Uncapped with Jack Altman: Benchmark Breakfast #2 | November 12, 2026 ·
The 36% US versus 93% China AI-optimism gap reflects a narrative problem, not real differences in AI's impact.
Jack cites a Gallup poll in which 93% of Chinese respondents said AI will mostly help the country versus 36% of Americans, which is near the bottom of the countries surveyed. He argues the gap cannot be explained by real differences in how AI will affect the two countries' lives, so it comes from sentiment and narrative. He thinks the US public's dislike is probably rooted in real concerns, and that AI can be a real problem for people. But he says the gap points to a large narrative problem, because the public's experience of AI's benefits does not match its fears.
“There is no real reason for that discrepancy between the two. It is not going to impact the lives of one country that much differently than the other. That is sentiment and narrative.”at 38:30
Uncapped with Jack Altman: Benchmark Breakfast #2 | November 12, 2026 ·
The fear of AI taking jobs is a narrative problem; automation is not remotely starting to do that yet.
Jack says the industry has been telling people that AI will take their jobs and that data centers will automate away the work they have spent 20 years learning. He argues this framing is why people push back. He says that automation of that kind is not even remotely starting to happen. He treats the job-loss fear as a narrative problem rather than a current economic reality, which helps explain the poor public sentiment on AI.
“We've gone around telling people, we're going to take all their jobs. ... It's not even remotely starting to do that.”at 39:28
Uncapped with Jack Altman: Benchmark Breakfast #2 | November 12, 2026 ·
Largest VC firms will raise roughly $50-60B in the next one to four months.
Jack and Everett tallied the funds they had heard were raising, including reports of $5B, $11B and $16B raises, and reached about $60B from five or six firms, probably not counting everything. All of these firms raised their last funds only about 12 months earlier, which Jack says is the typical gap. Jack notes that if the funds deploy over a more typical two to two-and-a-half years, the outlays are very large, and he asks where the money comes from and where it goes. He says the firms are probably right to raise now because the money is still available, and that the market's tough times will also bring opportunity.
“we believe that something like 50,000,000,000 to $60,000,000,000 of venture capital is going be raised by the largest firms over the next, I don't know, one to four months.”at 41:15
Uncapped with Jack Altman: Benchmark Breakfast #2 | November 12, 2026 ·
Outside SpaceX, Anthropic and OpenAI, most great startups do not need anywhere near this much capital.
Jack argues that outside the largest capital consumers, the rest of the venture market does not need that much money. He gives Databricks and Stripe as examples of great businesses, and says they do not need anything like $150B. The point undercuts the case for the very large venture funds, since most of their capital cannot be absorbed productively by the companies they back.
“anthropic open AI, the rest just don't need that much capital. ... how much money do Databricks and Stripe really need? It's not that it's not 150,000,000,000”at 43:43
Uncapped with Jack Altman: Benchmark Breakfast #2 | November 12, 2026 ·
Mega VC funds are squeezing midsize funds as LP capital concentrates in the biggest firms.
Jack argues that there is always room for small early-only funds, but that midsize funds are being squeezed by LPs as the largest firms grow. The mega funds are pushing up against the total demand for venture investment, so they absorb the capital that would otherwise go to midsize managers. Everett agrees, calling the mega funds suffocating squeezes on midsize funds. Jack says historically the well-known firms raised less than LP demand, which allowed a broad ecosystem to form, and that if the funds keep growing, they will take all of the available dollars.
“there's always room for a small early only fund. But I think there is a group of funds that's midsize that I do think gets a lot of LP squeeze as a result of these other funds just being so big that they truly are starting to push up against the total desire for venture capital investment.”at 47:21
Uncapped with Jack Altman: Benchmark Breakfast #2 | November 12, 2026 ·
Seed valuations are now permanently expensive, as seed has become a safe haven for capital.
Jack argues that the logic of the private traffic jam led investors to treat seed as always safe, since a seed round is the cheapest round and always has a safe haven unless the company fails outright. Large firms now write seed checks that do not change their economics, so the check size no longer constrains price. Founders also skip angel rounds and go straight to Series A, which means fewer early-stage rounds are available at lower prices. He concludes that seed has moved into unexplored territory and that seed valuations will stay permanently high.
“the knock on effect to that has been that seeds have just become permanently expensive. ... Seeds are now permanently expensive. Because you have this oscillating traffic jam ahead of you.”at 51:21
Uncapped with Jack Altman: Benchmark Breakfast #2 | November 12, 2026 ·
Sequoia CapitalBullish
Sequoia's restructuring was smart: a bulk-then-cut move that simplifies the firm back to its core.
Jack says he initially read the Sequoia changes as smart, and he compares them to YC's expansion and later cutting under Gary Tan. He argues that organizations need both bulking and cutting moments, trying many things and then simplifying back to the core, as the best founders do with shipping and cutting features. He says Sequoia moved along the spectrum toward simplicity, in contrast to Andreessen Horowitz's maximalism and Benchmark's focus. He also cautions that the real risk lies in failing to make the transitions between expansion and contraction when the firm's identity is uncertain.
“Those are good changes. Those are smart. Makes sense. ... generally speaking, I think you need these moments where you do a bunch of things, you try stuff, and then you simplify back to the core.”at 59:07
Uncapped with Jack Altman: Benchmark Breakfast #2 | November 12, 2026 ·
Customers pay for the leading-edge model even at higher prices, so frontier leadership carries outsized momentum and pricing power.
Labs have swapped the lead all year, and momentum follows whoever has the best model, even by a small margin and even when the older model handles most tasks. Users seem to pay for top intelligence despite price sensitivity because individual value is in the thousands or tens of thousands of dollars, and that surplus is large. For unbounded-upside tasks such as coding, sales, drug discovery and robotics, users will keep buying the better model. Jack also notes that price per gigawatt and the monetization of frontier tokens have surprised everyone.
“And the leading edge, even if it's by a little bit and even if the last model could do most of the tasks, it just seems like it's worth a crazy amount of momentum.”at 7:18
Uncapped with Jack Altman: Benchmark Breakfast #1 | Jack and Ev ·
Enterprise AI adoption & AI software
Token buyers are not yet proven more productive in all cases; broad enterprise diffusion still has a long way to go.
Token sellers are clearly doing well, but Jack doubts buyers are proving much more productive across the board. Coding was unproductive a year ago and now looks productive, but much of the economy has not yet adopted AI. He says there is still a long way to go before ordinary businesses can buy AI productively. He still believes it will get there, so this is a cautious view about the pace of diffusion rather than a rejection of it.
“I don't think that in all cases, the buyers of tokens are proving to be that much more productive in all cases.”at 9:04
Uncapped with Jack Altman: Benchmark Breakfast #1 | Jack and Ev ·
Enterprise AI adoption & AI software
AI coding adoption is near saturation among likely users, so 10x growth will fade; the runway is elsewhere in the economy.
Jack compares AI coding to Zoom during the pandemic. Everyone who wanted the product got it in a burst, growth was extreme, and then it saturated. Anyone in the Benchmark world who might use AI programming already does, so from here growth comes from market-share shifts, not 10x years. The larger opportunity is in the many places in the economy where adoption is far behind, so coding growth should slow even as AI broadens.
“everybody who might want to use AI programming has been using AI programming for a while... you don't get 10x year over year from that forever.”at 10:38
Uncapped with Jack Altman: Benchmark Breakfast #1 | Jack and Ev ·
Venture demand for AI code-adjacent startups is so intense that other good businesses now struggle to raise.
The code-adjacent AI wave has made venture demand in those spaces extremely strong, and LPs are doing well and funding it. Jack calls it one rational circus. The result is an opportunity-cost squeeze: investors can get a ridiculous ride in AI, so founders of solid non-AI businesses find it hard to raise capital.
“it's making it so that venture demand in these spaces is so obscene. And then LPs are obviously doing great and they're funding it.”at 18:54
Uncapped with Jack Altman: Benchmark Breakfast #1 | Jack and Ev ·
The growth bar for software companies has risen sharply; a 5-to-18 growth story no longer clears a raise.
Ev cites Datadog's historical path from about 5x to 18x revenue, then up to 40 to 50. Jack says a 5-to-18 company used to draw interest, but now investors ask why it isn't 5-to-40. Being credible today requires believing in an 18-to-100 story or a company doing something so hard that growth durability is unusually high. He ties this to the current code-driven pull on growth.
“that used to be enough where everybody would be super interested if all you heard was it's a software company going five to 18.”at 19:59
Uncapped with Jack Altman: Benchmark Breakfast #1 | Jack and Ev ·
Durability of application software is now hard to call; sentiment has flipped within months as models improve.
In the last cycle, investors could tell durable software from competed-away software because the patterns were familiar and enterprise buying was predictable. Now that is harder. Six months ago application software was seen as dead, and now it is seen as alive. The labs could move into these applications, but applications add value through edge cases, data and UI. Jack expects sentiment could flip again if code gets good enough to make those advantages disappear.
“I don't know, six months ago, everybody was kind of like, it's dead... At the moment, I think people are like, it's alive and it's good.”at 22:19
Uncapped with Jack Altman: Benchmark Breakfast #1 | Jack and Ev ·
Robotics & autonomous vehicles
Robotics will work and become common, so investors can bet ahead of it even though it is not working yet.
Robots cannot yet do much of what a human can, and no one has one at home. Jack still believes they will arrive, pointing to the early signs of autonomy in Tesla vehicles and to demos at robotics startups. He concludes that this is the kind of trend investors can bet on ahead of time. No date is given.
“I think we all believe robotics will work... But I think we all believe we'll have one.”at 23:09
Uncapped with Jack Altman: Benchmark Breakfast #1 | Jack and Ev ·
AI for biology is likely to work; early signs show target identification now possible that wasn't before.
Jack says the smartest people at the labs believe AI for biology will work. Early indications show that target identification and other tasks are now possible when they were not before. He cites this as one of the areas where the next big bet is forming, alongside robotics. The evidence is anecdotal.
“the smartest people at the lab seem to be saying it's going to work. There seems to be early indications that target identification and other things are possible that didn't used to be.”at 23:41
Uncapped with Jack Altman: Benchmark Breakfast #1 | Jack and Ev ·
Frontier labs likely keep a per-inference cost edge over inference providers, though training amortization complicates it.
Frontier labs must recover training costs through their prices, while an open model is free to use, so it carries no amortization. Inference still has to be run either way. Jack thinks labs still have the advantage per unit of inference over inference companies, but that gap could be offset by other factors. He says he mostly buys Ev's economic case for closed labs, but he doesn't have the margin numbers to be sure.
“And it's probably right that on a per inference unit basis, the labs are still going to have the advantage over the inference companies.”at 32:46
Uncapped with Jack Altman: Benchmark Breakfast #1 | Jack and Ev ·
For some industries, owning open models is worth it even without savings, as open models get good enough.
Enterprises cannot fully trust any vendor with all of their data, so they want to own their intelligence, a theme Jack links to Alex Karp's argument. For certain industries that control will justify the trade-off. As open-source models improve, a company gets control even if it saves no money. Post-training an open model on proprietary data can also outperform a newer closed model, and founders say they hear this often. He expects open models to be good enough for most tasks, while frontier labs focus on the frontier.
“I think there is an argument to be made there. I think for certain industries, that trade is going to be worth it. And particularly as the open source models get good enough, even if you're not saving any money, you're in control.”at 34:30
Uncapped with Jack Altman: Benchmark Breakfast #1 | Jack and Ev ·
Open source likely stays mid-single-digit to ~12% of AI revenue unless total spend changes.
Jack treats the market as the answer. Inference companies together are doing mid-single-digit percent of total revenue, which he takes as a reasonable proxy for open-source usage because that is where open models run. He says mix shift could move this, but the trend suggests open source at around 5% to maybe 12% of the total unless overall AI spending changes. He frames this as the synthesis of the open-source and frontier-lab views.
“The market's telling us the answer. And the answer is that the inference companies in combination are doing mid single digits worth of total revenue.”at 36:26
Uncapped with Jack Altman: Benchmark Breakfast #1 | Jack and Ev ·
Frontier AI labs are very important but unlikely to be $6 trillion companies; a middle outcome is the happy path.
Jack says the earlier fear was either a Terminator-style AI takeover or that AI wouldn't matter, like crypto. He points to the market's positive reaction to Anthropic as evidence that the outcome is landing in the middle: the labs are extremely important, but not trillions-of-dollars companies, and the technology is useful. He calls this the happy path and says his odds of it have risen. The argument rests on the market's reaction and his view of AI's usefulness, with the caveat that RSI could change things.
“where the labs are extremely important, but they are not [$6 trillion] companies”at 40:19
Uncapped with Jack Altman: Benchmark Breakfast #1 | Jack and Ev ·
AI-driven cyber risk is imminent, so it is a good time to be a security company.
Jack says cyber risk is the most imminently expressed AI risk. Recent CEO conversations described pointing frontier models at their own systems and finding them breakable. He notes that attacking from inside has advantages an outside attacker lacks, since insiders have the data and code base. Still, he argues this is a good time for security companies and a scary first real exposure. He expects enterprises, governments and hospitals to move faster than the old 36-month software cycles, though not within three months. He hopes that in about twelve months people can do a lot.
“obviously, it's probably a good time to be a security company.”at 41:58
Uncapped with Jack Altman: Benchmark Breakfast #1 | Jack and Ev ·
Enterprise software buying is faster now than the slow, 36-month cloud-era cycles.
Jack compares the cloud era, when customers bought Workday and Salesforce on long timelines and government, hospital and law-firm buyers took about 36 months, with today's software purchasing. He says it's not really like that now, and people are alert. He hopes buyers will treat security as a top priority and react faster than expected. He still doesn't think that means it happens in three months.
“people bought Workday and Salesforce on these really elongated timelines. And they were slow... That's not really how it's going right now on the purchasing of software side.”at 47:04
Uncapped with Jack Altman: Benchmark Breakfast #1 | Jack and Ev ·
AI-driven bio could be among the best outcomes, as labs build teams and buy data for it.
Jack argues software improvements have a ceiling because the world's biggest gains are physical: housing, longevity, health, food and transport. Bio would be one of the best outcomes if AI finds drug targets and new drugs quickly. He points to labs talking publicly about bio, building teams around it and buying large amounts of data as evidence it is on the horizon. He calls bio and robotics the two areas where this is most visible.
“bio, to me, would be one of the very best possible things if we're discovering drug targets and finding amazing new drugs quickly.”at 48:31
Uncapped with Jack Altman: Benchmark Breakfast #1 | Jack and Ev ·
2 older views from Jack Altman are on the episode pages, and all of them are a question away in your AI with Chorus.
Shows
- Uncapped with Jack Altman · 2 episodes
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