AI models have commoditized as prices fall 41% while tokens surge 50%. The winning strategy is partnering, owning the interface, & harvesting routing data.
Vercel's COO on how the company actually built an inbound sales agent: a 125-line prompt written by the top SDR, six weeks of human QA, & the moment the prompt grew to 1,000 lines & had to be replaced by 14 rules in code.
AI inference will pass the $161b database market on its way to ~$350b in 2027, mutating every application into an inference reseller & upending classic software unit economics.
Vibe-coding is growing software in parallel petri dishes. State machines and formal verification design it. In this new era, we'll need both.
Tokenized real-world assets are compounding at 53% a month, more than twice as fast as Anthropic. Stocks & commodities now trade on blockchains 24/7, powered by Allium, which now runs Bloomberg's RWA terminal dashboard.
Anthropic & OpenAI both re-rated their run rates in 2026 by segmenting : a mandatory enterprise repricing against an 80% price cut on the cheapest tier.
GPU rental prices doubled in six months while inference prices kept falling. The reconciliation is efficiency : the hinge that turns scarce silicon into cheap intelligence.
Software engineering has evolved into systems architecture. 37signals, Artemis & SpaceXAI all report the same shift : agents write the code, engineers design the systems that decide whether it is right. The scarce resource was never the talent, it was the foundation to verify against.
The AI market's center of gravity is mid-tier inference, & three forces are driving its prices down : lab rivalry, open weights & fine tuning.
Machine-native models replace human-facing text generation with zero-token typed execution, cutting inference costs by orders of magnitude for basic programming primitives.
