As AI floods the internet with perfectly optimized but synthetic content, the most valuable asset becomes that which cannot be easily replicated: proprietary data, original research, and unique human experiences. AI agents will be designed to seek out and reward this scarcity.

While AI agents promising perfect information sound beneficial, they may over-optimize for measurable specs. This devalues unquantifiable aspects like design, feel, and brand—the "soul" of a product. The result could be a marketplace of highly utilitarian but ultimately less human and desirable goods.

Future AI agents will make purchasing decisions based on perfect, real-time information about product quality and price. This erodes the value of brand and marketing, forcing companies to compete solely on the objective merits of their products.

As AI makes software development nearly free, traditional engineering moats are disappearing. Businesses must now rely on durable advantages like network effects, economies of scale, brand trust, and defensible IP to survive, becoming "unsloppable."

Leading AI models are becoming increasingly similar in capability. This rapid convergence suggests the underlying technology is becoming a commodity, and competitive advantage will likely shift to user interface, distribution, and specific applications rather than the core model itself.

As AI tools and templates make it easy for everyone to create "optimized" content, social feeds will become saturated with lookalike videos. This will force marketers to differentiate through substance and originality rather than just hacking algorithms.

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.

If AI makes intelligence cheap and universally available, its economic value may collapse. This theory suggests that selling raw AI models could become a low-margin, utility-like business. Profitability will depend on building moats through specialized applications or regulatory capture, not on selling base intelligence.

Unlike cable or power companies that benefit from regional monopolies, AI intelligence is a globally competitive, frictionless market. This dynamic is 'so much worse' for business because it allows for perfect arbitrage, driving the price of intelligence toward zero and making it incredibly difficult to build a sustainable, high-margin business on the infrastructure layer.