Models are commodities. The accumulated context a vendor holds about your organization is not, and it is becoming the stickiest layer in the AI stack.
Inference is a real, usage-scaling cost of goods sold. It is pulling software gross margins toward infrastructure territory, and buyers pay for it either way.
Stablecoins were supposed to disintermediate the card networks. Instead Visa and Mastercard are running an incumbent defense: co-opt, contain, collect.
Agent interop standards are not neutral plumbing. Whoever owns the protocol layer between agents and enterprise systems owns the distribution chokepoint.
AI capacity is consolidating into a utility with three chokepoints. The strategic question is no longer which model to use, it is who controls your inference.
AI build versus buy is not one decision but six, one per stack layer. A decision matrix with defaults, override conditions, and traps for each.
Open weights do not commoditize AI. They relocate the toll booth to compute, distribution, and evaluation, and reshape who captures the AI margin.
Visa, Mastercard, and Stripe are backing an open stablecoin consortium. The playbook is older than it looks: own the new rail's governance before it owns you.
Agents rarely shrink payrolls. They convert doing-work into checking-work, and winning org charts are redesigned around that conversion, not headcount.
AI agents break the per-seat model at the root. The pricing ladder replacing it, the failure modes of each rung, and the buyer playbook for the transition.
The durable moat in applied AI is not the model. It is the eval suite: the one asset competitors cannot rent, and the one due diligence should price.
Secondary markets already price 2024-2025 fintech Series B rounds 30 to 50 percent below last paper. A founder's playbook for the next twelve months.
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