Braden Hancock(@bradenjhancock):The bitter lesson rejects domain-specific structure. Problem decomposition & recombination (what RLMs make first-class) is about as general-purpose of a problem-solving tool as it comes. Reminds me of the march of processor speeds: CPUs got faster every year until ~2004, when clock speeds hit a heat wall around 3 GHz. Transistors kept getting cheaper, but the only way to keep getting gains was to decompose workloads into pieces and go parallel. As the tasks we give LLMs get longer (context length/time horizon) and more complex, scaling up to 100T parameters will probably help...but my money is on big-O-improving innovations like this improving generalization faster.

2026.07.20 16:56

The bitter lesson rejects domain-specific structure. Problem decomposition & recombination (what RLMs make first-class) is about as general-purpose of a problem-solving tool as it comes. Reminds me of the march of processor speeds: CPUs got faster every year until ~2004, when clock speeds hit a heat wall around 3 GHz. Transistors kept getting cheaper, but the only way to keep getting gains was to decompose workloads into pieces and go parallel. As the tasks we give LLMs get longer (context length/time horizon) and more complex, scaling up to 100T parameters will probably help...but my money is on big-O-improving innovations like this improving generalization faster.

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