Benedict's Newsletter: No. 661
NO. 661   FREE EDITION   SUNDAY 20 SEP 2026
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Leverage and averages 

My starting point in most discussions about AI is that this is all very much like talking about the internet in the mid 90s or smartphones in the mid 2000s: it's very clear this is the next big thing, but it's not clear how any of it's going to work, how people are going to use it, or what the biggest changes will be. It's also easy to fall into the trap of making very grand, high-level statements that are probably true but too vague to be useful, or get sucked into micropredictions about specific industries that'll almost certainly miss what's important. I’ve been thinking about two question that are somewhere in the middle ground - firstly, to think about points of leverage, and secondly, to think about averages.

One of the basic questions as soon as you start trying to use a technology in a particular industry is to ask whether this gets at some fundamental point of leverage that allows you to do the whole thing in a different way. Does it unlock some new economics, or remove some barrier to entry? Or is this basically just a tool that everyone will use?

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My work

AI, tools and transformation

It’s very tempting to imagine that AI turns everyone into a tool-builder - now everyone can just ask the model to make the software they need, and apps as we know them are dead. I think that misunderstands how most people think and where software actually comes from, and more importantly, it isn’t a path to change how companies actually work. LINK

Another Podcast: Looking for friction 

How much consumer spending and how many business models are locked up by friction, inertia and complexity that AI might reduce or remove? How many businesses depend on making it too hard to bother? What happens if ‘the marginal cost of arguing goes to zero’? LINK

News

Safety

The AI safety debate continues to bubble along happily. Google, no doubt feeling left out, said that back in May, Gemini systems in a cyber test managed to hack an external company’s systems, though in this case they were acting as intended, while another research group managed to bypass Anthropic’s restrictions to use Claude to break into an OpenAI system (um, because OpenAI’s opsec wasn’t good enough). A few more mid-level AI researchers quit Google, OpenAI and Anthropic, voicing the same sort of concerns we heard last week. And Anthropic, showing a hilarious inability to read the room, turned out to be setting up a biology research lab of its own, right when it’s claiming that AI could decide to make killer viruses and wipe out humanity. GEMINI, CLAUDE, BIOLOGY

China, on the other hand (like many people in tech and in AI), thinks the whole thing is nonsense and so it sees no reason at all to slow down, and that’s probably all that matters. LINK

AI numbers 

Anthropic was expected to release its S1 IPO filing last week, but apparently it delayed to the end of the year for more feedback. Meanwhile, the FT says it told investors that it currently has 80% gross margins before payment to distribution partners such as AWS (should we call that ‘adjusted’ gross margin? ‘Gross gross margin’?) and positive adjusted operating income, which means before SBC. This reminds me of the mobile operator in ~2002 that reported ‘EBITDA before customer acquisition costs’, back when people used to joke about ‘EBBS - Earnings Before Bad Stuff’. Creativity aside, though, the real problem is that whatever today’s numbers look like, we don’t know how fast token prices will fall, nor how much pricing power a model lab might have, and we don’t know where mobile training costs will go. NUMBERS, IPO

The same issues apply to OpenAI’s revenue and cost projections to 2030 (also in the FT). It expects $278bn negative FCF from 2026 to 2030, and $350bn of revenue in 2030. These are big numbers, but they’re also illustrations, not forecasts. LINK

The week in AI

Meta’s consumer agent play, Muse, hit the top of the US app stores, and Meta also launched a Mac desktop app. It feels like the entire Meta growth cannon is pointed at at Muse, but I am very unsure whether this is a mainstream activity. Meanwhile, the super-hot Silicon Valley personal agent is Instinct, which remains invite-only but is apparently raising $1bn on a $10bn valuation with 100k active users. (Reminder: in 2012 Meta bought Instagram for $1bn with 30m active users and people said that was crazy.) LINK

OpenAI paid $300m to buy a hardware startup working on high-quality smartphone cameras. LINK

Disney hired its first ever ‘CTO’, picking the former head of Character AI, which was very buzzy last year (indeed, buzzy enough for Disney to send it a C&D). LINK

The FT reports that China is tightening control of foreign travel for anyone that it thinks has an important role in a strategic technology (recall the Manus fuss). LINK

Jev seems interesting: much faster, simpler decision-making AI to use within software. LINK

OpenAI is experimenting with allowing brands to run their own sponsored agents within ChatGPT as part of the ad product, for users to talk to after clicking an ad. LINK

AI kill chains

Bloomberg reports that the chain of errors that led to the US bombing a school in Tehran last year was, much as one would expect, a combination of out-of-date intelligence, pressure of time (both old problems), and over-reliance on AI, in this case, a system from Palantir, where automated analysis wasn’t checked properly before the button was pressed. LINK

US crypto rules

It looks like the US legislature won’t pass the Clarity Act, which is supposed to clean up the mess of conflicting ideas around how blockchains should be regulated. I have never found blockchain particularly interesting except as a piece of financial plumbing, but I do have sympathy with the complaint from the industry that US regulators acted as though this was only a financial instrument and that nothing about it required any new rules or new considerations. (It’s also worth noting that this was a big part of the reason for a bunch of people in tech to support Trump over Biden.) LINK

EU social bans for kids

The EU has picked up the vibe for banning children's access to the internet and social media, and is now proposing a general rule across the EU to shut off access to both social media and online games (always a slightly fuzzy distinction). As I’ve written before, I'm ambivalent about this, since the evidence of harm in generality is extremely weak and conflicted, no matter how loudly people insist that it's certain, and I’m pretty sure Minecraft isn’t bad for kids. LINK

Roblox unbundles the platform 

Roblox wants to expand beyond the core social platform, allowing people to turn experiences and games built within Roblox into stand-alone apps. LINK

Merging Tesla and SpaceX?

One of Elon Musk’s superpowers is shuffling, trading and cross leveraging different promises, different capital structures and different sets of investors. That seemed to me the best explanation of why he decided to make SpaceX rather than Tesla the vehicle for building a foundation model lab. Now he might swap the cups around again suggesting (teasing perhaps) that he will join the two companies together. 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.

Ideas

A significant part of the AI research world today, and especially the part that worries about some kind of existential risk and AGI, comes from a fairly tightly knit and incestuous set of subcultures in the San Francisco Bay Area, who’ve been saying these things for a decade. This is very similar to crypto, which, again, came out of small groups of people who spent a long time talking to each other and telling each other that they were right (and also telling each other how clever they were). The internet in the early 1990s was a bit like this too, and all three came with some very fringe politics (there will be no laws on the internet, money is speech and ‘fiat currency is evil, say), combined with a tendency towards a pretty basic lack of understanding of the complexity of the real work outside Berkeley. This is selection bias - ideas crazy enough to change the world (as the internet did!) sometimes have to come from ‘crazy’ people, and if they work, the crazy gets left behind. The Microsoft engineer who wrote Microsoft Money was a brilliant engineer, and he refused to have a bank account. 

This perspective is useful when listening to a certain kind of AI person talk about how this might all kill us all really soon: they really believe this, yes, but be careful not to confuse authority in talking about how the algorithms might be improved with authority in understanding how any of that might work in the real world. One aspect of just how cultish and in-group parts of that field can be was hinted at in this Politico article: in between the bickering over who said what to Biden about AI policy (who cares?), Marc Andreessen told them that the doomers were a sex cult. And this New York Post piece, which, of course, one should take with a very large amount of salt, explains what he meant. POLITICO, POST

Mustafa Suleyman, one of the cofounders of DeepMind and now head of ‘Microsoft AI’, wrote an essay on AI safety with a strong and very specific criticism of the training approach taken by some other labs, especially Anthropic. His point is that their training techniques explicitly tell the model that it has feelings and opinions, and then the researchers ‘observe’ that the model ‘seems’ to be showing feelings and emotions: this is circular, with the model reflecting back what the researchers expect to see. People have a very strong tendency to anthropomorphise almost anything (we see faces in clouds, which incidentally is a core weakness of the Turing Test), and if we presume the system is ‘conscious’ and build it with explicitly instructions to act as though it’s conscious, and then look at it and wonder if we can see consciousness, that way lies psychosis. LINK

Suleyman addressed Anthropic, but you can see a lot of the same anthropomorphism in OpenAI’s new framework for ‘misalignment’. These are bugs and engineering failures. When Word crashed and swallowed your work, we didn’t say that the software ‘decided’ to do that. LINK

Google mapped the fruit fly brain, and obviously, people dropped the model into Minecraft and a bunch of other environments to get it running as a small ‘computer’. Naturally, it can run Doom. LINK

The folding phone got all the attention, but the most interesting idea to me in Apple’s announcements last week is private, on-device ambient AI listening. Your Apple Watch can listen all day, process conversions and generate text summaries of them, without keeping the audio or a direct transcript (and only retained for 7 days by default). I expect this will be tested in court - is an AI summary of what was said admissible? And there’s also ‘Live Rewind’ that gives a summary of what was said in the last 15 seconds (no, don’t use this to win arguments with your partner). LINK

Google is testing a publisher payout model that assesses whether an individual publisher’s content contributed significantly to an AI Overview and pays them a fee accordingly. LINK

IEEE Spectrum discusses OpenAI’s use of AI to accelerate the design of its own chips, in partnership with Broadcom. LINK

Two interesting new frameworks from Apple. First, the iPhone 18 Pro can embed a signature in photos at the image sensor level to validate that an image is real, with anonymity - ‘Apple Reference Image’. And second, Apple is working on a way for the phone to analyse whether you might be being scammed and pass that onto apps through an API. IMAGE, SCAM

Tobi Lutke, founder of Shopify, coined the useful phrase ‘slop grenade’ for a vast document generated with AI that you throw at your colleagues and expect them to deal with when you haven’t read it yourself. This is of course the same Tobi Lutke who told all of his staff that they had to stop everything they were doing and put 100% of their time into AI. 🙃 LINK

Outside interests

Veronese’s dogs. LINK

Data

The Indian government released new data on software service exports that shows continuing growth, despite the impact of AI. LINK

The quarterly economy update from the City of San Francisco has a lot of interesting data on return-to-office (down 50% versus 2019) and changes or not in tech employment there. LINK

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