MIT's Alex Zhang on Recursive Language Models, 10,000-agent swarms and the future of harnesses

a1zhang · x · 2026-10-02

Latent.Space features a long interview with MIT PhD Alex Zhang, first author of Recursive Language Models (RLMs). Key points:

Claude Code, Codex and Pi are basically the same: they are different harnesses around the same powerful models, and primitive wrapping leaves much capability on the table.
RLM idea: let models treat their own prompts as objects in an external environment, use code execution for context offloading and recursive subagents to generalize across tasks.
Expert vs brute force: a single expert agent can sometimes replace a trillion-token brute-force search, making harness design matter more than raw compute.
OpenAI experiment: a 10,000-agent experiment producing 130B output tokens hints at where LLMs are heading.
Academia's edge: freedom to take weird, ambitious research bets — Zhang follows star PhDs like Shunyu Yao and Jack Morris previously featured on the pod.

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