Calvin French-Owen (Segment co-founder) has been living in a small, cheap model for weeks — coding, searching thousands of emails, running research threads — and the bill barely moves. His essay makes the case that the real AI story this year is at the cheap end of the market, not the frontier.
Why it matters for consumers and businesses:
- Small models now run at roughly 100 tokens per second, with complex jobs costing tens of cents instead of dollars
- The old consumer playbook (cheap site, virality, ads) breaks when every request carries a real inference bill — which is why investors keep asking where the consumer AI companies are
- His test case: a personalized daily news site that cost ~$1 per run with last-generation models now costs ~$0.10 — the difference between a demo and a viable product
His co-founder Peter Reinholdt splits work into two buckets: “IQ 180” work (rare, novel breakthroughs) and “token spewer” work — being ultra-responsive, nudging people, pushing the ball forward. Peter estimates 95% of his day is the second kind, and most hiring is for it too.
The thesis: frontier models keep compounding for research and hard engineering, but the fast/cheap/good-enough tier is what unlocks consumer apps and the responsive work that dominates real organizations. The bottlenecks left are harnesses, prompt-injection safety, and roles and permissions — not model quality.