LLMs haven't seen significant traction in enterprise yet.
LLMs haven't seen significant traction in enterprise yet. That's where users are more sophisticated and willing to pay. Getting to low-sophistication, low...
Topic: llms
1,841 mentions · 834 chunks · 141 episodes
194.1× 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.
1.6x burst in 2025 Q1
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Peak quarter intensity across the topic's active span. Higher values mean attention was concentrated into a shorter stretch rather than spread evenly over time.
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 834 chunks across 141 episodes, from 2023-11-06 to 2026-10-12.
- Its densest episode is Bits and Bobs 10/20/25 (2025-10-20), with 17 observations on this topic.
- Semantically it travels with Claude, ChatGPT, and Meta, while by chunk count it sits between Claude; its yearly rank moved from #2 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 appropriateness of data being used is tied to the context it was collected and used in.
...ike a betrayal. That's why Google's data is a blessing and a curse in an era of LLMs. They're sitting on a trove of data for each user… but if they preprocessed everyone's decades of emails it would feel like a crazy beytral, an invas...
If the system assumes an LLM as the main loop then there's a floor of how cheap and performant it can be.
...p and performant it can be. Whereas if it assumes normal compute sweetened with LLMs there's no floor or ceiling. And also if you assume LLM in the loop the only way to improve is model quality or tools. Whereas normal code can accret...
The big companies are all on the chatbot train.
...mpanies can't bet on two contradictory things. What if the most powerful use of LLMs that is not chatbots?
LLMs are great at things that are expensive to generate but easy for a human to judge.
LLMs are great at things that are expensive to generate but easy for a human to judge. They're not good at things that are easy to generate but hard for a...
The first microprocessors went into calculators.
...nowable. Afterwards, it feels obvious, like it's impossible to unsee. The first LLMs are like word calculators. We haven't come up with word computers.[fb]
Stratechery: "it seems likely that LLMs have already generated more text than all of humanity ever has; the reason I cannot know is the same reason why it hasn't left a mark: AI content is generated individually for each individual user of AI."
Stratechery: "it seems likely that LLMs have already generated more text than all of humanity ever has; the reason I cannot know is the same reason why it hasn't left a mark: AI content is ...
A key question about a system: does it work without LLMs?
A key question about a system: does it work without LLMs? Are LLMs just lubrication for the system? Or are they the fundamental enabler? LLMs are expensive and slow. Systems that use them as lubrication can...
The meta-game can shift rapidly even from small changes.
...one to make bots to create the appearance of momentum. Especially in the age of LLMs. Keep that in mind when you see what looks like momentum.
Hollowed out things are about unthinking execution.
...llowed out things are about unthinking execution. "Just turn the crank faster." LLMs applied naively just turn the crank faster. It's even more important than ever before that the crank is attached to something resonant!
Centralization + LLMs + Authoritarianism will be an explosive combination.
Centralization + LLMs + Authoritarianism will be an explosive combination. LLMs aren't going anywhere. The push towards authoritarianism might be hard to reverse in the sh...
To use LLMs to their fullest potential today requires working in the terminal.
To use LLMs to their fullest potential today requires working in the terminal. If you aren't using tools like Claude Code every day, you will have no idea what t...
A friend points out that code is better seen as an exoskeleton to LLMs' muscle.
A friend points out that code is better seen as an exoskeleton to LLMs' muscle. Exoskeleton is both support and containment. LLMs benefit from both. LLMs aren't great at constraints, but old-school code is great at it.
Product surface discovery happens much slower than technical capability improvement.
...el performance is clearly seeing a plateau. But the interesting applications of LLMs are just at the very beginning.
Trade is only valuable if you have non-infinite time and different abilities than the entity you trade with.
... never noticed that "trade is good" is downstream of these assumptions. But for LLMs these assumptions don't obviously hold. LLMs have infinite patience. Agents that use the same model also have precisely the same capabilities. This c...
Last week I talked about humans at "liability meatbag" for LLMs.
Last week I talked about humans at "liability meatbag" for LLMs. Also known, in any system, as a "liability sink." I like Ethan Mollick's colorful frame: "sin eater." The entity that eats the sin allows progress t...
LLMs are kind of like magnets.
LLMs are kind of like magnets. If you sprinkle little iron filaments around, they snap into beautiful patterns. Those patterns make the hidden patterns of...
Don't train an agent to use Excel.
...se statistics in whatever way is natural to it. The affordances that humans and LLMs need might be disjoint.
LLMs have so much potential energy, just waiting to be catalyzed.
LLMs have so much potential energy, just waiting to be catalyzed. All we need is the right catalyst. We're seeing like 5% of the potential value they cont...
A situation good for society is "all of the model providers have to compete and none of them win" for LLMs.
...ociety is "all of the model providers have to compete and none of them win" for LLMs. Great for everyone but the LLM model providers, who are in a never-ending red ocean battle. But the rest of us benefit from the significant competit...