tech
AI Skills
For the past few years, artificial intelligence has been discussed almost exclusively in terms of models. Bigger models, faster models, smarter models. More recently, the focus shifted to agents, systems capable of planning, reasoning, and acting autonomously.
TL;DR
- The true leap in AI usefulness occurs at the 'Skills' layer, not with models or agents.
- Skills are applied, reusable units of procedural knowledge that allow AI systems to perform specific tasks reliably from start to finish.
- Skills transform user intent into execution, encapsulating domain-specific know-how and producing concrete, usable results.
- The AI stack consists of foundational models (raw intelligence), agents (coordination and planning), and Skills (application layer for real work).
- Skills encode procedural knowledge (how to do something) rather than descriptive knowledge (what something is), turning general intelligence into expert behavior.
- Skills are modular, reusable, and composable, offering better scalability than custom-built agents for each task.
- Skills are products that can be packaged, licensed, and monetized, as users buy capabilities and outcomes, not just abstract reasoning.
- The competitive advantage in AI is shifting to those who build and distribute the most useful Skills.
- AI systems will ultimately be judged by their effectiveness in converting intelligence into action, with Models thinking, Agents coordinating, and Skills executing.