Benedict's Newsletter: No. 639

NO. 639 FREE EDITION SUNDAY 19 APRIL 2026

My work

How will OpenAI compete?

OpenAI has some big questions. It doesn’t have unique tech. It has a big user base, but with limited engagement and stickiness and no network effect. The incumbents have matched the tech and are leveraging their product and distribution. And a lot of the value and leverage will come from new experiences that haven’t been invented yet, and it can’t invent all of those itself. What’s the plan? LINK

Another Podcast: what jobs are AI jobs?

How do you know what AI will do to your industry? Your company? Your job? The easy, obvious answer is to add up the things you do that can be automated, but it’s probably better to ask how the job will change, and to ask what your job really means. Is AI tackling the easy part or the hard part? What are your customers really buying? LINK

AI eats the world

Twice a year, I produce a big presentation exploring macro and strategic trends in the tech industry. The latest edition: ‘AI eats the world’. LINK

News

Anthropic does surge pricing

With software engineers suddenly using thousands of times more tokens for agentic coding, Anthropic is having capacity problems, with outages increasing, users complaining of suddenly limited responses, OpenClaw being cut off, and a succession of price increases. It was always clear that some of the pricing plans were cheaper than the real cost of heavy users, and Anthropic has invested least in capacity of all of the big labs (partly reflecting the lack of a consumer story), but now, with agentic coding finding massive product-market fit, that’s become a real problem. There are lots of long-term discussions about where this will end up, with the extreme case arguing that token budgets will rise to match headcount budgets, which is all like trying to forecast internet use in the late 1990s, but it seems to me that a good comparison is mobile data in the late 2000s, when the iPhone’s flat rate data swamped AT&T’s network. The natural end-state of all these situations is a segmented range of flat rate bundles. LINK

Allbird AI

Meanwhile, after announcing last week that it would sell the remains of the once-buzzy shoe business for pennies, this week Allbirds (effectively just a cash shell) announced that it would now do something vague in AI data centres, and the stock went up 5x. That’s the kind of thing that happens in bubbles, but it also reflects a basic shortage of ways for public markets investors to get a clean investment in AI. You can short existing software companies, and buy Nvidia (and to some extent TSMC and ASML) and random Japanese speciality ceramics companies, but what else? LINK

Meta Manus

China’s reaction to Meta’s acquisition of Manus (agentic AI platform) seems to be escalating: the FT reports that it looks like orders came from the very top to crack down, with multiple ministries ordered to take an interest. Moving your co-founders to Singapore to get around Chinese limits on foreign acquisitions might not have been as clever as it seemed, especially in such a strategic sector. Hence, China is only investable if you can get a domestic exit? Would that matter for Beijing - is there a shortage of capital for AI? LINK

The week in AI

OpenAI continues to build out its adtech stack. LINK

Google has joined Anthropic and OpenAI with a desktop Mac app. The shift from the web to local apps is partly driven by practical go-to-market considerations (get your own icon on the dock), but rather more by the scope to interact with local apps and files - using the operating systems as an actual operating system, not just a place to run browser tabs. Meanwhile, it’s also notable there is a Mac app but no Windows app. LINK

The US plans to require data centres to report their energy use. LINK

Back in January, when Elon Musk tried to juice demand for Grok by letting it produce deepfake porn, Apple was concerned enough to threaten to pull the app from the App Store if Grok didn’t add more safeguards. LINK

The Information reports that Apple has sent several hundred developers on the Siri team on a ‘bootcamp’ to learn how to code with AI. I would have guessed that if anyone at Apple considered it an essential part of their job to know everything about this stuff already, it would be the Siri team, but apparently not. LINK

Uber goes back to robots

Uber got out of robots back in 2018, realising that while ML got us 90% of the way, the next 10% was 50% of the work, and meanwhile Uber was spending both too much money and not enough (also, remember the Levandowski lawsuit). But now physical AI is hot again, Waymo is kind of working, and Uber is back: the FT calculates that it’s committed $10bn over the next few years towards vehicle purchases and equity stakes across more than a dozen different tech companies (it had almost $10bn of FCF last year). That’s a portfolio model, rather than the previous attempt to build the whole thing itself. LINK

Amazon buys Globalstar

As rumoured a couple of weeks ago, Amazon has bought the LEO satellite operator Globalstar to bulk up its satellite Internet project. Apple (which has a stake in) remains an anchor customer for the emergency connectivity in iPhones. LINK

Meanwhile, Jeff Bezos’s Blue Origin rocket company had a semi-successful launch. LINK

About

What matters in tech? What’s going on, what might it mean, and what will happen next?

I’ve spent 25 years analysing mobile, media and technology, and worked in equity research, strategy, consulting and venture capital. I’m now an independent analyst, and I speak and consult on strategy and technology for companies around the world.

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Ideas

A long and fascinating interview with Nvidia’s Jensen Huang, conducted by an AI influencer, Dwarkesh Patel. Frankly, he’s a bit out of his depth, throwing challenging questions at Jensen but not really able to handle tough answers: it reminds me a bit of an overconfident undergraduate trying to argue with their professor. That said, we get a lot of good material from Jensen - in general, his elucidation of how Nvidia’s model differs from other chip companies, and in particular (which is where Dwarkesh gets into trouble), on his view on US export controls. Jensen argues that Chinese chips aren’t as good as Nvidia’s (true), but China has an abundance of cheap energy (also true) and so Chinese labs can just use way more chips to get the same result. Hence, withholding Nvidia chips doesn’t slow down Chinese AI - it just cuts off the market for US companies and the US ecosystem and pushes China to build its own tech stack instead. That’s fine as far as it goes - where he runs into trouble (and where Dwarkesh didn’t push him) is that he says we should stop China from using that capacity to build Mythos-style cyber capabilities, by, um, asking them nicely not to be mean to us. We already know that doesn’t work, but the real answer might be ‘we can’t’. LINK

Pulling up the ladder - two important pieces about high-tech manufacturing. First, the FT argues that after the ‘China shock’ of cheap low-value manufacturing, there’s now a growing second China shock of high-value, high-tech manufacturing, where the same model of ferocious, Darwinian competition, backed by subsidies and cheap energy, produces a handful of very efficient and capable winners in each space, plus a lot of overcapacity, that then moves to exports. Second, Bloomberg says that Chinese export controls in those high-tech industries are crippling India’s attempt to build its own tech manufacturing base. INDIA, CHINA

The debate within China about AI and data privacy. LINK

Two analyses of the report that OpenAI is hoping for $100bn of ad revenue by 2030. The current global ad market, excluding China, is close to$1tr, but new things create new TAMs. LINK 1, LINK 2

Someone leaked an internal memo from OpenAI talking to employees about Anthropic. Mostly predictable, but note the confirmation that OpenAI is reporting revenue net and Anthropic is reporting gross, which means their public revenue statements are not comparable (though the growth clearly is). LINK

The UK’s AI Security Institute assesses Anthropic’s Mythos impact on cyber. LINK

OpenAI should buy Snap? LINK

Email and Slack archives from dead companies are the new source of AI training data. LINK

Mondelez on how they’re planning for agentic commerce. Mostly, best practice for SEO. LINK

How accurate is AI health advice? It depends a lot on small differences in precisely how you ask the question. LINK

Outside interests

The album of tributary peoples. LINK

Data

The 2026 Stanford AI report: a huge number of charts on the state of AI. LINK

Newzoo’s latest games industry report. LINK

Emarketer forecasts that Meta’s ad revenue will overtake Google’s this year (but only by subtracting Google’s TAC). LINK

Google’s latest ad safety report shows a surge in attempts at placing scam ads using AI. LINK

Gallup’s latest survey of US public opinion, like many other surveys, shows rising worry around ‘AI’. It’s almost as though the heads of two of the big labs have spent the last three years trying to get regulatory capture by saying loudly that people should worry. LINK

Bain survey data on US consumer use of generative AI for search. LINK

Preview from the Premium edition

What’s the TAM for AI?

Way back in 2014 an NYU finance professor got a lot of attention with a piece arguing that Uber was massively overvalued, on the basis that the global ‘taxi and car service market’ was worth $Xbn and Uber would get X% share at Z% margin. He estimated that the total market in 2024 would be 183bn and Uber would have 10%: in fact, Uber’s gross bookings for mobility in 2024 were $83bn, and total gross bookings were $162bn - off by almost 10x.

This wasn’t just wrong in hindsight. As a few people pointed out at the time, it was based on a fundamentally flawed premise - sometimes a new thing can just take share of the existing market, but often it finds an entirely new market.

What does that mean, though, if we’re investing half a trillion dollars a year and growing in AI data centres? The simple answer is that demand

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