Firms like OpenAI and Meta claim a compute shortage while also exploring selling compute capacity. This isn't a contradiction but a strategic evolution. They are buying all available supply to secure their own needs and then arbitraging the excess, effectively becoming smaller-scale cloud providers for AI.

The biggest opportunity for AI isn't just automating existing human work, but tackling the vast number of valuable tasks that were never done because they were economically inviable. AI and agents thrive on low-cost, high-consistency tasks that were too tedious or expensive for humans, creating entirely new value.

The price mechanism in capitalism is a successful but lossy compression of complex economic information into a single number: money. AI agents can operate on the uncompressed, real-time data of supply and demand across the economy, creating a more efficient system that avoids the waste inherent in capitalism's information loss.

As AI agents become sophisticated, they'll need to pay for services. Traditional banking is too slow and fragmented for them. Crypto, as the internet's native money, provides the instant, global, low-fee rails for AI agents to transact with each other and with web services, creating a major new use case.

When developers use AI to code, the AI agent itself selects the underlying infrastructure like databases. This shifts the purchasing decision from human developers and central IT teams to the AI, fundamentally disrupting how the multi-trillion dollar enterprise infrastructure market operates.

The cost for a given level of AI capability has decreased by a factor of 100 in just one year. This radical deflation in the price of intelligence requires a complete rethinking of business models and future strategies, as intelligence becomes an abundant, cheap commodity.

Businesses with moats based on network effects or consumer friction are vulnerable to "agentic commerce." AI agents, tasked with finding the absolute best price without experiencing the tedium of comparison shopping, will bypass brand loyalty and platform stickiness. This threatens any business model that relies on being the default or convenient choice.

The current oligopolistic 'Cournot' state of AI labs will eventually shift to 'Bertrand' competition, where labs compete more on price. This happens once the frontier commoditizes and models become 'good enough,' leading to a market structure similar to today's cloud providers like AWS and GCP.

The cost of AI, priced in "tokens by the drink," is falling dramatically. All inputs are on a downward cost curve, leading to a hyper-deflationary effect on the price of intelligence. This, in turn, fuels massive demand elasticity as more use cases become economically viable.