LLMs are a general-purpose data solvent.
LLMs are a general-purpose data solvent. To extract structured data from unstructured input is extraordinarily expensive to do mechanistically. Each scrap...
Topic: llms
1,598 mentions · 615 chunks · 117 episodes
169.8× distinctiveness vs baseline
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How much more common this term is here than in ordinary English. Higher values mean the topic is more characteristic of this corpus.
Topic summary
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A short read on the topic's time range, peak episode, and strongest associations. Use it as the quick orientation before drilling into examples.
- llms appears in 615 chunks across 117 episodes, from 2023-11-06 to 2026-04-20.
- Its densest episode is Bits and Bobs 2/2/26 (2026-02-02), with 15 observations on this topic.
- Semantically it travels with ChatGPT, Claude, and prompt injection attack, while by chunk count it sits between Claude; its yearly rank moved from #3 in 2023 to #1 in 2026.
Over time
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Raw mentions over time. Use this to see absolute attention, not relative rank among all topics.
Observations
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The primary evidence view for this topic. Sort it chronologically when you want concrete examples behind the larger pattern.
The scarce input for applying reasoning models is skilled human effort.
...ity, but often a gilded turd[we]. This effect gets stronger the more believably LLMs can give superficially high-quality answers[wf] on more topics.
The Chatbot frame leads LLMs to be treated like genies.
The Chatbot frame leads LLMs to be treated like genies. Genies are simultaneously god-like and also a slave. The default LLM presentation of a human-ilke superintelligence trappe...
I think this tweet about finding the right UX for AI-native tools is directionally correct.
...ds and adapts to them seamlessly. I think that would be the killer use case for LLMs. Chatbots are (compelling!) demos of LLMs, but ultimately, for most use cases, not the right modality. There are some use cases that will always be b...
It could be useful to have multiple LLM participants in a conversation.
...ction is similar to how chain of thought works. One problem with using multiple LLMs in a conversation though: LLMs always respond to every message. In a 1:1 conversation, this is reasonable: one person talks, then the other one does,...
I wish LLMs would sometimes speak in a lo-fi mode when they weren't very sure.
I wish LLMs would sometimes speak in a lo-fi mode when they weren't very sure. LLMs have this uniformly professional tone, but they are often not particularly au...
A pattern to work well with software generated by LLMs: start with the smallest artifact that works and then build on top of it.
A pattern to work well with software generated by LLMs: start with the smallest artifact that works and then build on top of it. If the first iteration doesn't work, don't try to keep building on it. Iter...
LLMs are significantly better at writing smaller chunks of functionality.
LLMs are significantly better at writing smaller chunks of functionality. Every additional feature in an app leads to combinatorial complexity. Assembly T...
Most of the world isn't legible to computers.
...because of reasoning missing, but also sensing. Reasoning is easy now thanks to LLMs, so real-world sensing is the long pole. Even if there physically is a camera in the location, the idea of connecting it to a system that can always ...
Cluetrain.com is a blast from the past of earlier eras of the web, but still deeply relevant.
...ization. Sounds like one voice but is actually inhuman. Not too dissimilar from LLMs and why their "view from nowhere" voice sounds hollow.
I don't want AI, I want IA.
...r humans vs centering the models. A test if you've done this: if you turned off LLMs, would the system still work (just with more friction)?
LLMs allow qualitative nuance at quantitative scale.
LLMs allow qualitative nuance at quantitative scale.[yf] Before, to get scale, we had to throw away a lot of nuance to get scalar values that could be eas...
The original autocompletion LLMs are "System 1" models.
The original autocompletion LLMs are "System 1" models. The reasoning models are "System 2" models. What are the "System 3" models? Systems that plug into the emergent, online, colle...
An implication of LLMs allowing perfectly adaptable media: less marketing, more selling.
An implication of LLMs allowing perfectly adaptable media: less marketing, more selling. Think of a traveling salesman selling a vacuum back in the day. Or think of a makeu...
LLMs don't have memories of their interactions with humans.
LLMs don't have memories of their interactions with humans.[yr] Another way that the "LLMs are basically a virtual human" mental model is wrong. LLMs have...
Voice input to legacy computer systems felt excruciating, but voice commands to LLMs feels like flying.
Voice input to legacy computer systems felt excruciating, but voice commands to LLMs feels like flying. When we talk it's a stream of consciousness. It's non-linear; with ums, ahs, corrections, and disfluencies. Stream of consciousnes...
LLMs make it so any text is "executable," so a possible injection attack.
LLMs make it so any text is "executable," so a possible injection attack. This is because it allows english to be converted, explicitly or implicitly, to ...
If the web wasn't open then LLMs could never have been created in the first place.
If the web wasn't open then LLMs could never have been created in the first place.
One user talking to a fixed model is a sub-linear business.
...hat's possible. An ecosystem of emergent collective intelligence, lubricated by LLMs, is a super-linear business. The quality of the LLM sets the floor of what is possible. The floor that the collective intelligence can accrete on top...
You can't live on a little random island in the middle of the sea.
... via bridges, then it's way more likely to be survivable. Software generated by LLMs today are little islands, isolated from everything else you want to do. LLMs can only do shitty software in the small (without a human significantly ...