The companies building AI cannot agree on where it is going. Their contradictions, more than their product launches, tell you what comes next.
SpaceX raised $75 billion in the biggest stock market debut on record. Press coverage has been euphoric, with the Economist calling it “capitalism at its most remarkable”. Its 277-page prospectus, however, shows that artificial intelligence accounts for 93% of its claimed $28.5 trillion addressable market, with little engagement on how Elon Musk’s lab, xAI, will manage that work. xAI’s safety team is reported to number two or three people, against roughly 200 at OpenAI. Under oath in April, Musk said he was “not sure what a safety card is”. Four AI safety organisations, including The Midas Project, read the filing so the market wouldn’t have to. Their conclusion was that investors cannot price a risk the company will not disclose. Since trading began, the shares have fallen back, and Musk’s trillionaire status with them.
OpenAI’s listing is next, though reports suggest the company may now delay it into next year, given how SpaceX’s share price has fallen back since trading began. The trial Musk brought against Sam Altman ended on a technicality, with no court ruling on whether OpenAI had betrayed its nonprofit mission. The testimony itself produced the most detailed audit of a frontier lab to date: Greg Brockman’s private diary asking “maybe we should just flip to a for-profit”; Mira Murati testifying that Altman gave mixed orders and bypassed safety reviews; and Altman disclosing over $2 billion in personal holdings in companies that do business with OpenAI. The governance question moves from a courtroom, where it was at least asked, to public markets, where it will simply be priced.
Anthropic filed confidentially on 1 June at a reported $965 billion valuation, briefly surpassing OpenAI’s $851 billion. Dario Amodei used the same week to publish an essay arguing that voluntary restraint in the AI race has reached its limit, calling for FAA-style mandatory third-party testing of frontier models with government power to block deployment. He committed $350 million to research on AI’s labour-market fallout. The generous reading: this is the only honest position available to him; voluntary restraint has hit its commercial ceiling. The harder reading is that funding labour research constrains nothing on its own. Indeed, the rules that would actually bind Anthropic remain untested, and the company keeps its foot on the accelerator while it waits.
Google announced no IPO since it didn’t need to. But Apple’s WWDC press release described Siri AI as “profoundly more capable” and “rebuilt from the ground up” without mentioning that its cloud tier runs on Google’s infrastructure or that its foundation layer is built on Gemini, in what Bloomberg reports as a roughly $1 billion-a-year arrangement. Gemini now has 900 million monthly users, and Brian X. Chen at the New York Times calls Google the dark horse winner of the consumer AI race. The Economist supplies the cost of that ubiquity: 3.2 quadrillion tokens a month, $190 billion of capital expenditure this year, and usage caps quietly introduced after the I/O keynote. So the competitive race that the press keeps talking about seems to sit inside a distribution race that may already be settled.
Meta took a different path. In April it released Muse Spark, its first frontier model in over a year, and made it closed source. After three years of Mark Zuckerberg publishing manifestos in defence of open AI, and after Llama reached 1.2 billion downloads, releasing weights for free was no longer compatible with capital expenditure that will reach between $115 and $135 billion in 2026. The exit leaves the open-weight ecosystem dominated by Chinese labs and their models: Alibaba’s Qwen, Moonshot’s Kimi, Z.ai’s GLM, and DeepSeek.
Indeed, while these five American companies have been busy contradicting themselves, the people who actually pay for AI have been quietly making other choices. DeepSeek’s V4 lands at a fraction of the price of GPT-5.5 with a million-token context window, even though the Economist judged the sequel failed to impress (the company has just raised $7.4 billion at a valuation above $50 billion). Z.ai’s GLM-5.2 runs at roughly an eighth the cost of Claude Opus 4.8 and ranks third worldwide for AI tasks. In fact, six of the top ten models globally are now Chinese. Rest of World even reports that US developers are switching in numbers that have moved from interesting to material. Now ChatGPT’s global market share has fallen below 50% for the first time.
Watching this play out, I see the familiar pattern of incumbents fighting so hard for each other’s customers that they fail to notice the customers walking out the side door. The Chinese models are not yet the best, but they are cheap enough to make that question feel academic and open enough to run on your own infrastructure. Meanwhile, the gap is closing. Indeed, when American labs are valued in the high hundreds of billions on the assumption that their pricing power holds, and that pricing power is quietly being routed around, something has to give.
Perhaps all this is much like John Banville writes in The Sea:
“What is money, after all? Almost nothing, when one has a sufficiency of it.”
For more inspiration, here are some of my favourite Seth Godin quotes from his 2025 blog posts, together with a recommended title from Blinkist.
“Begin. Learn. Succeed. Then add complexity.” ~ Complex systems
Learn more: The Startup Lifecycle
“Don’t find customers for your products, find products for your customers.” ~ Building blocks of marketing
Learn more: Me, My Customer, and AI
“Entrepreneurship isn’t about building a giant company that makes money. Instead, it’s the attitude of solving problems, creating leverage and building something bigger than one’s self. When people are enrolled in this journey, they’re open to possibility and optimism.” ~ Finding your cohort
Learn more: The Resilient Founder
“Even if you charge by the hour, you’re not selling hours. You’re selling something clients can use. Clients will pay more for something useful than something that was difficult.” ~ Kinds of value
Learn more: Sell or Be Sold
“Find the smallest viable audience.” ~ Notes to myself
Learn more: Build a Business You Love
“Hustling is a race to the bottom, and our competitors lean and hustle in response… which means that we’re now under pressure to hustle more than we think is appropriate, driven by the same forces that led us to hustle in the first place.” ~ The hustle loop
Learn more: Buoyant
“If you work on your own, your productivity choices are up to you. But when you involve others in your project, the default should be to honour the habits of the most productive member of the team.” ~ Simple and painless productivity
Learn more: Team Intelligence
“Instead of seeking to fail your way to enough, it makes more sense to commit your way to better.” ~ Big scale, big impact
Learn more: 10x is Easier than 2x
“It’s tempting to seek out the easy gigs and the straightforward projects. But of course, if they’re the easy ones, there’s probably quite a few people eager to do them. So your ability to add unique value goes down.” ~ Finding the difficult work
Learn more: The Idea is the Easy Part
“Just because it’s useful, needed or worthwhile doesn’t mean it’s a good business.” ~ A good business
Learn more: A Cure for the Common Company
“Scale is rarely the first signal of important work.” ~ The NSE confusions
Learn more: The Song of Significance
“Tell me what your tactic is trying to accomplish and I’ll be halfway to understanding what your strategy is.” ~ Every tactic…
Learn more: Myths of Strategy
“We get to choose who we’re here for.” ~ Picky or particular?
Learn more: Finding Clarity
“We get to pick which sort of projects we take on.” ~ Rigor and curiosity
Learn more: Pivot or Die
“When fans commit to a movement and help it grow, they benefit. Not every group is going to become a movement, but if we don’t bring others along, we’re not going to make a change happen. Movements move.” ~ 1,000 fans (which sort?)
Learn more: Irresistible Change
“When we acknowledge that the people we’re teaching, leading or selling to see the world differently than we do, we can improve the user experience and deliver better results.” ~ Clarity about the benefits
Learn more: Mixed Signals
“When we can build connections between demographics and psychographics, it’s easier to surprise, delight and serve our customers.” ~ Surprising insights
Learn more: Growth Data Analytics Playbook
“When we shift from a focus on what we are owed to one based on what we can contribute, we’re free to get back to work.” ~ Overappreciated
Learn more: The Goodwill Jar
“When you deliver more than people expect, your overdelivery creates connection. The surprise and delight is remarkable. People talk about it, seek you out and come back for more.” ~ Seeking yoyu
Learn more: Irresistible
“When you give others the resources, trust and commitment to do the work, the work gets done. Sometimes, it even gets done better than you could have done it (if you had had the time and focus, which you don’t).” ~ Settling for better
Learn more: Unleashed
“You don’t get to 3% of the market by trying for 40% and failing. You get there by embracing the 1% and doing such a good job that the word spreads.” ~ Big scale, big impact
Learn more: Competition Demystified
“You don’t have to be a giant business to benefit from a consistent and powerful position, supported with a story. But it’s a good place to start if you want to get there.” ~ First impressions and second chances
Learn more: Wealthy and Well-Known
