Karpathy: Master Foundational Models Before Building AI Agents

Andrej Karpathy recently questioned the AI industry's premature push for Agents. He warned that developers rushing to build agents without truly understanding the underlying models are ignoring the fundamentals, which could lead to long-term negative consequences.

Core Views and Controversy

Karpathy challenged the common assumption that better Agents must rely on larger models. He believes that excellent Agents do not necessarily require massive models; good results can also be achieved using small models, appropriate tools, and closed-loop feedback. However, he emphasized that the industry's biggest current misconception is forcing Agents to work rather than fully grasping the underlying models first. Multiple authors recounting his views mentioned that Karpathy believes Agents should follow models, and that the underlying model is the true product.

Historical Lessons and Impact

Karpathy compared this current rush for quick success to a similar mistake made by OpenAI in 2016, pointing out that skipping fundamentals to chase demos comes at a heavy cost and wasted 5 years. He reminded developers that turning a Demo into a mature product might take many years, and if the foundational principles and behavioral boundaries of models are ignored, the eventual system will easily collapse. Therefore, he advises thoroughly understanding the relevant fundamentals of LLMs before starting to build AI Agents.

2026-07-20 ~ 2026-07-21 · 5 related posts

• Karpathy: Master the Model Before Building Agents — leslysandra · 2026-07-20
• Karpathy Challenges AI Assumption: Better Agents Don't Need Bigger Models — Div_pradeep · 2026-07-21
• Karpathy’s point reframed: agents come after models, not before them — FinanceYF5 · 2026-07-21
• Karpathy’s LLM fundamentals are recommended before building AI agents — _jaydeepkarale · 2026-07-21

1 near-duplicate retellings: FinanceYF5