AI's economics don't make sense

Subscription vs Usage-Based Pricing

• Many see flat-fee “all you can eat” plans as fundamentally misaligned with AI’s variable compute costs; heavy users (agents, coding tools) can burn hundreds of dollars a day.
• Others note all subscriptions cross‑subsidize light users to heavy ones; that alone doesn’t make the model broken.
• Several predict a shift to “electricity-style” metering by tokens or tasks, with tiered plans and better controls for overruns.
• A recurring user concern: metered billing makes it hard to predict costs, echoing past surprises with cloud/hosting.

Token Costs, Margins, and Profitability

• One side claims frontier labs enjoy very high gross margins per token; current API prices are far above marginal inference cost, especially with caching and hardware advances.
• Others counter that even if marginal tokens are profitable, huge R&D and datacenter capex leave companies overall cash‑negative; training must be treated like an expensive, ongoing requirement, not a one‑off asset.
• There is disagreement whether claims about “profitable models over their lifecycle” are meaningful without audited financials.

Scale, Capex, and Bubble Risk

• Skeptics argue valuations and build‑outs (tens or hundreds of billions) cannot be paid back with modest per‑seat pricing; back‑of‑envelope math suggests payoffs stretched over decades, if ever.
• Some compare this to WeWork or other overhyped sectors; others to capital‑intensive industries like pharma or semiconductors where big R&D is normal.
• Many expect consolidation; not all current players will survive.

Value to Users and Employers

• Multiple comments say coding assistants and agents already deliver significant productivity gains, especially for well‑paid knowledge workers, making even high hourly AI costs justifiable.
• Others stress diminishing returns: more generated code can overload review and process bottlenecks; junior hires or process fixes may beat more tokens.
• There’s concern that AI may depress wages while core living costs still rise.

Competition: Frontier vs Open / Local

• Several note strong open‑weight models approaching frontier quality but requiring hefty hardware; local or shared clusters may become attractive for companies with predictable heavy use.
• Intermediaries that resell frontier APIs (e.g., dev tools, search wrappers) are seen as especially exposed if they pay full retail for tokens.

Business Models and Monetization

• Some expect advertising or subtle “sponsored” outputs to emerge, analogizing to search and other media. Others note this could sharply erode utility, especially for agentic use.
• A few argue that companies may ultimately aim more at large enterprise and government contracts than consumers.