Pure capability no longer translates directly into a moat.
Words found on the source page on Nov 6, 2026.
More from Ben Thompson
BlogFrontier OverhangsSep 21, 2026
A world with sufficient compute is one where intelligence is a commodity, and in commodity markets margin comes from a superior cost structure, which I would expect the leading model providers to have, in part because they have a meaningful lead in scaling and can apply superior AI to their infrastructure.BlogFrontier OverhangsSep 21, 2026
Indeed, that’s probably the overhang that matters most of all: competition. Anthropic is fine with Anthropic being in the lead; anyone else requires government intervention.BlogFrontier OverhangsSep 21, 2026
Once you have put all of your information into a personal agent and actually incorporated it into your day-to-day life, it is much more of a challenge to change to something else.BlogFrontier OverhangsSep 21, 2026
The fact of the matter is that LLMs are, if anything, too obsequious; there simply isn’t any evidence of LLMs having a will or operating with malevolence.BlogFrontier OverhangsSep 21, 2026
Truly effective defense will mean truly trusting agents to act autonomously, but most companies won’t do that until they are forced to by regular and unremitting hacks by fully autonomous attackers.BlogFrontier OverhangsSep 21, 2026
What this means is that model performance isn’t the only thing that matters: the integration between model and harness is where true agent differentiation is found.BlogWho's Afraid of Chinese Models?Jul 20, 2026
And, in the long run, this imperative to move up the stack does mean that frontier models are absolutely a threat to software providers, including Microsoft.BlogWho's Afraid of Chinese Models?Jul 20, 2026
Second, intelligence isn’t in fact a perfect commodity, in part because applied intelligence makes itself smarter.BlogWho's Afraid of Chinese Models?Jul 20, 2026
The long and short of it is this: marginal costs are back in a big way, both in terms of short-term implications of state-of-the-art free models, and in terms of the long-term structure of the industry.BlogWho's Afraid of Chinese Models?Jul 20, 2026
The reason this matters is that we are rapidly approaching a state in which intelligence for many economically beneficial tasks is in fact a commodity.BlogAgents Over BubblesMarch 2026
Agents, however, will tilt much more heavily towards pure acceleration, making those drivers of value much more impactful.BlogAgents Over BubblesMarch 2026
AI, however, not only gives the aforementioned excuse to undo that bloat, but also moves the “rightsize” point significantly towards a much smaller workforce.BlogAgents Over BubblesMarch 2026
I’ve come to a different conclusion: I don’t think we’re in a bubble (which, paradoxically, maybe is the truest evidence we are).BlogAgents Over BubblesMarch 2026
The economic imperatives are going to be impossible to resist, and will fuel demand for even more compute over time, further supporting the case that this is no bubble.BlogAgents Over BubblesMarch 2026
Yes, AI still needs agency; it just doesn’t need agency from that many people for its impact to be profound.
On the same topics
BlogThe Most Important Market in AI is the MiddleSep 23, 2026
But the right tail of the market is thinner than almost anyone forecast.BlogThe Most Important Market in AI is the MiddleSep 23, 2026
Demand for intelligence is not a pyramid with a small, wealthy peak paying for everything beneath it.BlogThe Most Important Market in AI is the MiddleSep 23, 2026
Most business AI use is the messy middle: multi-step workflows that need a smart enough model at a price a company can afford. It is the most important part of the market today, & it is where the competition is fiercest.BlogAI Comes for the If StatementSep 21, 2026
If this is the first of many primitives specialized for production, then harnesses are about to capture a lot more margin.BlogAI Comes for the If StatementSep 21, 2026
They also highlight the bifurcating economics of AI: state of the art models for discovery & optimized models for production. We use the largest frontier models to train new models, & the most capable models to architect systems. But once a system is engineered & hardened, running it thousands or millions of times through a workflow benefits from narrower AI.BlogAI politics & the future of growth #602Sep 19, 2026
We have to hold in our heads that most Americans appear to loathe AI, but businesses and consumers seem to like it enough that Anthropic is well on its way to $100bn in annualised revenue this year. And despite being on track to be the fastest-growing company ever, Anthropic’s leadership believes they might kill all their customers.
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