This will not be popular—- Everyone is selling you tokens. They’re telling you to build more skills. More prompts. More agent wrappers. More orchestration. More context files. The more tokens you burn, the more they win. You don’t. The current obsession with “skills” architectures is a transitional phase, not the destination. Yes, they work. Yes, they can accelerate specific workflows. But they’re also creating tomorrow’s technical debt. Every new skill adds: • More maintenance • More prompt engineering • More governance • More testing • More vendor lock-in • More tokens consumed The dirty secret? As frontier models improve, many of these handcrafted layers become obsolete. You’re investing engineering effort to compensate for limitations the next generation of models will solve natively. This is exactly why I keep talking about AI factories, not AI assistants. An AI factory is deterministic where it matters, agentic where it creates leverage, and designed to continuously improve itself. Agents build the software. Deterministic services execute the business logic. Memory, evaluation, and governance become the architecture—not thousands of brittle skills stitched together with ever-growing prompts. That’s how you reduce costs instead of multiplying them. The next generation of enterprise AI won’t be measured by: * Number of skills * Size of prompts * Tokens consumed It will be measured by: * Cost per business outcome * Speed of autonomous execution * Quality of decisions * Ability to improve itself over time We’re still early. Many organizations are optimizing for token consumption instead of architectural efficiency. They’re building businesses that rent intelligence instead of owning capability. Build systems where AI creates assets—not token bills. The companies that understand this distinction today will have a structural cost advantage tomorrow. How you build matters. #AI# #EnterpriseAI# #AgenticAI# #Architecture# #DigitalTransformation# #CTO# #CIO# #ArtificialIntelligence#