Early 2026 LLMs in scaffolds, from simple ones such as giving the model access to a scratchpad/"chain of thought" up to MCP servers, skills, and context compaction &c are quite capable. (Obligatory meme link to the METR graph.)

Yet: If someone had told me in 2019 that systems with such capability would exist in 2026, I would strongly predict that they would be almost uncontrollable optimizers, ruthlessly & tirelessly pursuing their goals and finding edge instantiations in everything. But they don't seem to be doing that. Current-day LLMs are just not that optimizer-y, they appear to have capable behavior without apparent agent structure.

Discussions from the time either ruled out giant lookup-tables (Altair 2024):

One obvious problem is that there could be a policy which is the equivalent of a giant look-up table it's just a list of key-value pairs where the previous observation sequence is the look-up key, and it returns a next action. For any well-performing policy, there could exist a table version of it. These are clearly not of interest, and in some sense they have no "structure" at all, let alone agent structure. A way to filter out the look-up tables is [...]

The original text contained 3 footnotes which were omitted from this narration.

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First published:
March 17th, 2026

Source:
https://www.lesswrong.com/posts/a9KqqgjN8gc3Mzzkh/llms-as-giant-lookup-tables-of-shallow-circuits

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Narrated by TYPE III AUDIO.

“LLMs as Giant Lookup-Tables of Shallow Circuits” by niplav, Claude+

LessWrong (30+ Karma)