If I take the Bitter Lesson into account, I would frame this as needing more focus on enabling a general intelligence to use tools more effectively and when appropriate to essentially stop making mistakes.
A basic example being a calculator. The AI needs to recognize its default thinking pattern doesn't work well for math calculations, so it delegates it to the available calculator tool / skill / MCP instead. An LLM should not be relying on LLM prediction to give a mathematical resultant figure, ever. It should come from a deterministic tool. If anything, the LLM may interpret the problem and convert it into starting math figures to use for calculation.
If we can enable AI systems to learn and apply that for themselves, and even develop their own deterministic tooling and sense of what tool to use for what job, that starts to sound promising to me.
Skills feel like a conceptual stepping stone to the next useful abstraction.
If I take the Bitter Lesson into account, I would frame this as needing more focus on enabling a general intelligence to use tools more effectively and when appropriate to essentially stop making mistakes.
A basic example being a calculator. The AI needs to recognize its default thinking pattern doesn't work well for math calculations, so it delegates it to the available calculator tool / skill / MCP instead. An LLM should not be relying on LLM prediction to give a mathematical resultant figure, ever. It should come from a deterministic tool. If anything, the LLM may interpret the problem and convert it into starting math figures to use for calculation.
If we can enable AI systems to learn and apply that for themselves, and even develop their own deterministic tooling and sense of what tool to use for what job, that starts to sound promising to me.
Skills feel like a conceptual stepping stone to the next useful abstraction.