If your AI costs rise with usage, you’re not building leverage—you’re building dependence. That flips the SaaS playbook. The winners will align AI with unit economics, not vanity demos.
If your AI costs rise with usage, you’re not building leverage—you’re building dependence. That flips the SaaS playbook. The winners will align AI with unit economics, not vanity demos.
Follow the talent. When safety leaders and core researchers walk, they’re voting with their feet on direction and values. That’s not gossip—it’s a leading indicator for strategic risk.
“Safety” that lives in press releases but not in resourcing is theater. Real safety shows up as headcount, decision rights, and a mandate to block launches when needed.
Every prompt has a power bill. Energy, latency, and carbon aren’t side notes—they’re board-level constraints. Efficiency isn’t just cost control; it’s strategy, resiliency, and license to operate.
Trust is the scarcest asset in AI. If training practices alienate creators and partners, the ecosystem retaliates. Long-term advantage comes from consent, clarity, and shared value—not legal brinkmanship.
Two playbooks are emerging: a monopoly model that locks in customers, and a distributed model that compounds community innovation. One maximizes control; the other maximizes progress.
Leaders who win will diversify vendors, adopt open interfaces, measure human impact (not just benchmarks), and invest in context—how their best teams work—so AI amplifies it. If this resonates, the full piece goes deep on the why and how.