LLM coding assistants are best thought of as interns.
...ject. But you would have them do the implementation. That's the best way to use LLMs for code, too.
Topic: llms
1,749 mentions · 790 chunks · 131 episodes
184.9× 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.
1.5x 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 790 chunks across 131 episodes, from 2023-11-06 to 2026-08-03.
- Its densest episode is Bits and Bobs 10/20/25 (2025-10-20), with 17 observations on this topic.
- Semantically it travels with ChatGPT, Claude, and Google, 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.
I liked this article that posits that LLMs are best seen as cultural and social technologies.
I liked this article that posits that LLMs are best seen as cultural and social technologies. LLMs are more like a market or a bureaucracy than a person. A social technology, not an agent. Tha...
The danger scales with both the amount of data and tool use.
...both the amount of data and tool use. Lots of data, no tools, little danger for LLMs. There might be prompt injections, but they can't cause anything to happen. No data, lots of tools, little danger for LLMs. There's lots of things th...
Which will win, kino or slop?
...ventions in tasteful ways.[uk] Algorithms have pulled us more towards slop, and LLMs accelerate that. At some point though might the pendulum swing back? This section is riffing on some ideas from Robinson Eaton.
Assistance (ala Alexa, Google Assistant) used to be gated on reasoning and sensing.
...la Alexa, Google Assistant) used to be gated on reasoning and sensing. Now with LLMs, it's only sensing that's left. That is, what things might matter to you in your current context. That's both a sensor problem, but also a "user havi...
I like this cool combination of LLMs plus novelty search.
I like this cool combination of LLMs plus novelty search. LLMs pull us towards the centroid; this process uses LLMs in a systematic way to skate towards interesting outcomes, not average...
The main LLMs are improving fast enough that building an adjacent business is hard.
The main LLMs are improving fast enough that building an adjacent business is hard. For example, a business to finetune models to specific use cases, or a carefull...
I loved Sam Schillace's piece about the problems that arise from viewing LLMs as humans instead of viewing them as a tool.
I loved Sam Schillace's piece about the problems that arise from viewing LLMs as humans instead of viewing them as a tool. This is as far as I'm concerned the canonical take on the pitfalls of engineers using this incorrect men...
Ideas that people bring up in conversations are ones that they implicitly vote are interesting.
...l of humanity, something interesting comes out. This is one of the reasons that LLMs can be powerful; they're trained primarily on the most distilled collective votes for interestingness across society.
A startup idea: "Mechanical Turk but the tasks use LLMs instead of humans"
A startup idea: "Mechanical Turk but the tasks use LLMs instead of humans" Surely someone is building this?
LLMs are kind of like caulk
LLMs are kind of like caulk That is, they are gap fillers Good enough to fill in the details for you once you give the imprecise high level structure.
Being precise is hard--you have to think through real-world fine-grained detail, and it takes time.
...ine-grained detail, and it takes time. That's a high activation energy bar. But LLMs can do a lot of that for you; you say an intention, it helps do the detail work for you quickly and with reasonable quality. So the effective activat...
When you're writing for other people, you have to meet your reader where they are as soon as you start affixing words down.
...d it front loads modelling how to reason about that topic with others. But with LLMs, you can write your notes in whatever form makes most sense to you. The LLM will be right there with you, understanding what you intend, adapt to you...
Someone should write a manifesto that is optimistic about technology and also fundamentally human-centered.
...e a vision for computing that is all of: Optimistic about technology (including LLMs). Centered around humans not corporations. Cozy and human-scale. Collaborative and prosocial. Aligned with our collective aspirations. The manifesto ...
Consensus always pulls towards mush.
...ntroid, the average. Notably, that centroid might not itself be a viable point. LLMs are inherently a kind of planetary-scale consensus mechanism. They can give outputs that sometimes are at the centroid of a phenomena but not themsel...
I thought the Stratechery interview with Ben Evans on AI was interesting.
...chery interview with Ben Evans on AI was interesting. A few of my highlights: "[LLMs] are good at things that don't have wrong answers."[vp] "With an intern, the power of the intern is, you can tell them why they did it wrong. … One o...
Hyper concentrated insight is now more valuable than before because it can be diluted by LLMs.
...centrated insight is now more valuable than before because it can be diluted by LLMs. Hyper-concentrated insight used to be hard to consume–too sickly sweet, too hard to gulp down. Just like concentrated orange juice; much cheaper to ...
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...
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...