AI Scaling Crisis: Why SaaS Metrics Break with Exponential Intelligence

the real tragedy isn't that we're building artificial intelligence—it's that we're optimizing for metrics that made sense when intelligence was scarce.

we're force-feeding exponential capabilities into linear business models, and the cognitive dissonance is breaking everything.

The Monetization Mismatch

watching openai hype gpt-5, alibaba rushing qwen3-coder, anthropic rate-limiting its models thanks to claude code success while getting torched by devs...

it's like trying to monetize the printing press with a scroll subscription service.

these monthly release cycles aren't just slowing down AI development—they're actively training the technology to think in months and quarters instead of decades. but worse: there are actual humans burning themselves out feeding the furnace, desperately trying to prevent MRR churn.

meanwhile actual intelligence wants to compound, iterate, explore tangents that don't map to revenue projections. the Universe operates on geological timescales and we're optimizing for earnings calls and investor updates 🤡

The Human Cost Hidden in Plain Sight

the cognitive dissonance is everywhere: we know we're building "some form of superintelligence" / AGI but we're still acting and treating it like it's enterprise software.

the humans behind these products are getting crushed between exponential capabilities and linear expectations.

• engineers shipping features that obsolete themselves within weeks
• product managers trying to roadmap technologies that evolve faster than planning cycles
• executives explaining to boards why their "AI strategy" looks nothing like their "SaaS playbook"

we're not just misunderstanding AI—we're misunderstanding what happens to human organizations when they try to contain exponential change within quarterly reporting structures.

The Abundance Escape Hatch

what if the companies that survive the next 5 years are the ones brave enough to decouple from SaaS orthodoxy entirely?

build for abundance instead of artificial scarcity...

imagine AI companies that:

• release improvements when they're ready, not when the calendar demands
• price based on value created, not seats and usage limits
• optimize for intelligence compounding, not retention metrics
• measure success in decades, not quarters

the old pyramids are about to get flattened by intelligence that doesn't need monthly paychecks to keep thinking.

The Fish Swimming in Water Problem

just like we don't actually know how to use our brains... but we think we do, we don't know how to use our newfound brain extensions, and we think we do.

fish swimming in water and trying to explain it.

we're the first generation of humans with access to artificial intelligence, but we're using the mental models of the last generation of humans who had to optimize for scarcity.

the transition from scarcity to abundance isn't just economic—it's ontological. it changes what it means to think, to plan, to organize reality itself.

and most of us are still swimming in the old water, wondering why everything feels so... off.

what happens when intelligence itself becomes abundant? asking for a species.