At some point we'll see the mask-off moment for the aggregators.
...umbling along as cold war, but will become a hot one as the power of unleashing LLMs on your data heats up.
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.
I've seen a lot of approaches that mitigate the danger of malicious skills.
...t mitigate the danger of malicious skills. Or that mitigate the danger of naive LLMs confusing themselves. But still nothing in the market that credibly mitigates prompt injection.
LLMs will find a way, even if it's laughably wrong.
LLMs will find a way, even if it's laughably wrong. Someone this week told me about an agentic workflow they had that took an input image and some text an...
LLMs are persistent, so they can power through any non-resilient thing.
LLMs are persistent, so they can power through any non-resilient thing. They just eat away at it. If it's not regenerating itself, then it just gets groun...
Jenny Wen makes the case that our current best practice design process is obsoleted by LLMs.
...en makes the case that our current best practice design process is obsoleted by LLMs. The process that was the best practice fundamentally assumes that software is extremely expensive to create.
LLMs are the universal universal computer.
LLMs are the universal universal computer. Code is data in a very particular shape. Now it doesn't have to be in that particular of a shape. LLMs can make...
A 2026 burn about bad writing: "This would have been better if an LLM wrote it."
...have been better if an LLM wrote it." It's an insult… but it's also often true. LLMs are distinctly better than the average adult at writing.
StrongDM and OpenClaw are downstream of where LLMs hit a new scaling threshold of agentic ability.
StrongDM and OpenClaw are downstream of where LLMs hit a new scaling threshold of agentic ability. They were inevitable; the time had come. They were at the right place at the right time to surf the w...
We've left the Generative AI era and entered the Agentic AI era.
...ke a chatbot, but that's incidental. A couple of years ago people tried to wrap LLMs and create agents, but it was premature. The model quality wasn't there yet. So they concluded it wasn't possible. But it just wasn't ready yet. Now ...
In the Chatbot form factor the chat is a party trick.
...of durable ends. Those are the form factors that enable the potential energy of LLMs to blossom best.
A position of "It's OK to write code with AI but it has to be reviewed by humans" is untenable.
...f you try to review every line of AI code you will go crazy. It's not possible. LLMs can produce code so quickly the only way to tackle it is to use LLMs to review it.
LLMs are like C4 explosives.
LLMs are like C4 explosives. Moldable, powerful… and fundamentally explosive! Skills are just a hunk of C4, perhaps with some mechanistic code embedded th...
People use LLMs as interpreters more than compilers.
People use LLMs as interpreters more than compilers. An LLM as compiler could make guardrails for itself that then limit bad behavior.
Karpathy has spoken, enlightened AI-driven engineering is called "Agentic Engineering."
...red to write before: lightly held, possibly throwaway. But it's possible to use LLMs to help write code in much more disciplined ways that give compounding advantage, and that is not a flippant or unserious exercise. Agentic engineeri...
Before software had to be fractally mechanistic, all the way down.
...mall enough you can clear the threshold where any LLM can answer it reasonably. LLMs are more expensive than mechanistic code, but much more flexible and able to handle variance. When you have a working amalgam of LLMs and mechanistic...
Clawdbot Moltbot OpenClaw is the most interesting thing in AI that's happened since ChatGPT.
...have been too overwhelming so I decided not to. OpenClaw shows the raw power of LLMs when unleashed on your data. It's also self evidently, absurdly, catastrophically insecure. A friend described it this way: "It's basically a thought...
Another person noting that sandboxes are only a small part of the problem of securing LLMs.
...r person noting that sandboxes are only a small part of the problem of securing LLMs. "I think most people focusing on securing these are focusing on isolation, but that's really step 0 of a step 3 process they'll come to understand a...
Clawdbot makes the danger of LLMs more obvious.
Clawdbot makes the danger of LLMs more obvious. In the past, "prompt injection" was hard to get even developers to think about. "That sounds like SQL injection, that thing we've solve...
Don't use LLMs to do things you could have done before, but faster.
Don't use LLMs to do things you could have done before, but faster. Use them to take on meaningful projects that you never would have attempted before.
Peter Wang calls LLMs "essence extractors."
Peter Wang calls LLMs "essence extractors." Notably, this is not just photocopying ideas. It requires judgment, nuance, and produces something structurally valuable and di...