The meta-question as agent swarms scale: can models beat gradient descent at its own game?
JensHonack · x · 2026-11-08
As we scale swarms and ultra long-horizon persistent agents, the most exciting meta-question is whether agents can discover fundamentally better approaches than human-designed algorithms built on decades-to-centuries of priors. The author highlights "weight space programming": seeing if models can discover better ways to transfer information from data to weights than gradient descent. Swarms are today's agent topology for scaling compute toward discovery — and a good target is for a swarm to discover what a swarm should actually look like. Tons of algorithms sit in the shadows waiting for a compute allocator to test their viability.
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