Last gasps of the rent seeking class?

Rent Seeking, Free Markets, and Enclosure

• Many argue “rent seeking” in the article is misused; it should mean extracting economic rent via regulation and enclosures, not just “business models I dislike.”
• Others use a broader, more colloquial sense: any pursuit of monopoly‑like rents or moats, especially via friction, subscriptions, and platform lock‑in.
• Several comments link modern rent extraction to historical enclosure (turning commons into private property), with IP framed as a new enclosure of ideas.
• Disagreement over whether what we have is a “free market,” a “capitalist market,” or a heavily captured system shaped by lobbying and policy.

AI, LLMs, and Local vs Cloud Inference

• Some see open‑weight models and cheap local hardware as a serious challenge to centralized, token‑priced AI APIs.
• Others think centralization will continue: big players will train larger, proprietary models tied to their chips and clouds; the rent‑seeking just moves to LLM access.
• Skeptics note that running powerful models at home requires money, hardware, and electricity many people lack; most will end up on paid subscriptions.

Agentic Commerce and Marketplaces

• Optimistic view: AI “agentic commerce” could bypass rent‑taking marketplaces by going directly to sellers, doing comparison shopping and due‑diligence.
• Counter‑view: you just swap Amazon’s 15–20% cut for an AI platform’s cut, affiliate fees, or hidden “marketplaces” inside the model.
• Concerns that LLMs are bad at judging trust; trust and logistics (warehouses, delivery) remain strong moats for incumbents.

Consumers vs Corporations in an AI World

• One camp: AI equalizes time; if both sides use AI, it becomes too expensive for companies to weaponize friction and call centers.
• Opposing camp: corporations will deploy more and better AI, tuned at scale on millions of interactions; it becomes “your bots vs theirs,” and they still win.
• Expectation that AI will often exacerbate asymmetries, not flatten them.

Self‑Driving Cars and Broader Automation

• Some argue self‑driving is necessary given aging populations, labor shortages, and safety gains.
• Others see it as a way to replace workers so value shifts from drivers to tech firms, mirroring broader automation‑driven concentration of wealth.

Moats, Platforms, and SaaS

• View that the durable moats will be at the application layer: distribution, network effects, proprietary data, “systems of record,” and perceived stability.
• Even with democratized model access, large platforms can still dominate via scale, marketing, and integration.

Optimism vs Pessimism about Collapse and Democracy of Tech

• Optimists cite past tech waves (web, YouTube, smartphones) reducing barriers and creating more creators and builders.
• Pessimists reply that power merely re‑concentrates in new gatekeepers, and that calls for a US economic “collapse” are reckless given global interdependence.