Master Models Before Building Agents
Roger_M_Taylor · x · 2026-07-11
The shared content emphasized: **master the model itself and its context before forcing an Agent**—this is the most common mistake in current AI development. Key takeaways include: - Don't build an agent just for the sake of having one; truly effective products usually start with a solid foundation in models and context. - Demos are easy, but viable products require long-term refinement; much like autonomous driving, foundational work matters far more than surface-level effects. - Those building agents today are at the cutting edge, but they must accept that it's more akin to systems engineering than simple wrapper building. It also referenced an article on building a self-improving agent system using **Fable 5**, highlighting keywords like loops, dynamic workflows, and routines.
Related event: Karpathy: Master Models Before Building Agents(2 posts)→
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