# Thoughts on LLMs in 2026

DevFeed: [Thoughts on LLMs in 2026](<https://devfeed.tech/articles/thoughts-on-llms-in-2026-40606.md>)

Original publisher: [Read original article](<https://www.nateberkopec.com/blog/thoughts-on-llms-in-2026/>)

Published: 2026-05-23T00:00:00Z

Content type: opinion

Language: en

Sources: [Nate Berkopec](<https://devfeed.tech/sources/nate-berkopec.md>)

Topics: [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [LLM evaluation / benchmarking](<https://devfeed.tech/topics/llm-evaluation-benchmarking.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [language-models](<https://devfeed.tech/tags/language-models.md>), [llms](<https://devfeed.tech/tags/llms.md>), [thoughts](<https://devfeed.tech/tags/thoughts.md>)

## AI overview

An opinionated assessment of LLMs in 2026 argues that they are not general artificial intelligence but increasingly useful tools for verifiable, agent-assisted software work. It describes progress as uneven and mostly steady rather than evidence of an imminent singularity, emphasizing persistent weaknesses in visual understanding and simple reasoning despite stronger language and mathematics capabilities.

## Source excerpt

In May 2026, we are now five months post-Opus-4.5 and the great "Christmas Break Revolution" that saw us all hunkered down in front of our laptops over the new year. I'm now about nine to twelve months into not writing code by hand anymore. I more or less spend 100% of my time that I used to spend typing in IDEs instead talking to LLMs in Pi.11 Seriously, have you tried Pi yet? You're a hacker, aren't you? Why are you eating at the sloptrough of a trillion dollar company and whatever their product managers think you need in an LLM harness, and instead build your own like the hacker you were meant to be? Has the great Singularity come to pass yet? No. There's literally only one benchmark graph of LLMs which shows exponential progress22 , so of course that's the one everyone looks at. However, the rest of the synthetic benchmarks, and my own subjective experience, feel more like a steady, linear pace of progress. Artificial "intelligence" continues to be the wrong lens through which to view this technology we call large language models. "AI" gets us tripped up by a vision of a kind of "superset" of human intellectual capability, an artificial entity which meets or exceeds us on all dimensions. But LLMs and agents aren't like that at all, and they're not becoming less like that either. Their jagged "intelligence", as far as it can be said to be intelligence, simply gets more jagged over time as this radar chart of capabilities looks more and more ragged. LLMs can solve Erdős problems but not simple brain teasers about car washes, et cetera, et cetera. Their visual intelligence and comprehension in particular continue to be much worse than their command of language and mathematics. This word--intelligence--is leading people into fun science fiction thought experiments and useless "the singularity is around the corner!" drivel, and away from what LLMs are actually really useful for.33 The AI bigwigs essentially treated effective altruists as useful fools who kept saying "A