Second, intelligence isn’t in fact a perfect commodity, in part because applied intelligence makes itself smarter.
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
Pure capability no longer translates directly into a moat.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
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
BlogArguments in Favor of AI Fair UseSep 7, 2026
As LLMs continue to scale up, the value of any particular source continues to diminish.BlogArguments in Favor of AI Fair UseSep 7, 2026
Much, if not most, of the value of LLMs derives from their ability to generate new benefits beyond what the source material alone can yield.EssayMaking Startups PowerfulSeptember 2026
The obvious AI variant is to let your users opt in to training your model on their interactions with it. Many will resist that, but if some don't, the model they get to use will outperform the vanilla one used by the others.FilingPalantir Q2 2026 earnings release (SEC Form 8-K, Exhibit 99.1)Aug 3, 2026
Our customers trust us to provide them with maximal control over their operations, data, and decisions. Their competitive advantage should never become the training data for future models.BlogThe Reverse Information ParadoxJul 12, 2026
If learning flows in only one direction, economic value converges toward the owners of the learning infrastructure rather than the creators of the knowledge itself.BlogThe Reverse Information ParadoxJul 12, 2026
In the AI age, the buyer risks giving away knowledge, just in order to use what they bought. You essentially pay for intelligence twice, once with money, and again with something even more valuable: the proprietary knowledge you must reveal to make that intelligence useful.
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