LLMs are great at making a passable version of any shitty idea.
LLMs are great at making a passable version of any shitty idea. You can do a lot of damage and wasted time if you never ground truth it with people. If yo...
Topic: llms
1,749 mentions · 790 chunks · 131 episodes
184.9× distinctiveness vs baseline
?
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
?
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
?
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
?
Raw mentions over time. Use this to see absolute attention, not relative rank among all topics.
Observations
?
The primary evidence view for this topic. Sort it chronologically when you want concrete examples behind the larger pattern.
LLMs are for code what the Hall-Héroult was for aluminum.
LLMs are for code what the Hall-Héroult was for aluminum. Before the Hall-Héroult process was invented in 1886, aluminum was treated as precious. It was p...
LLMs are amplifiers.
LLMs are amplifiers. Like levers, that can be hugely valuable… but also hugely dangerous.
LLMs take away the puzzle part of programming.
LLMs take away the puzzle part of programming. The puzzle part of programming is where you can relax. Like doing sudoku puzzles that produce useful things...
An excellent piece from Venkat Rao about our Archival Selves.
..., the things we intended to do but never got around to. At a certain point with LLMs, you just kind of run out of a backlog. Contains this zinger: "Showing off your portfolio of bespoke aClaude Code projects and looking at others' por...
We're running out of features to spec!
...ion debt of product teams is going down as we can burn through the backlog with LLMs. Engineers were the bottleneck so PMs had time to plan and think. [bp] But not any more!
When software was expensive you had to go to the turf of the software creator, and that meant they got your data.
...that means the power accretes on their turf. A raw deal for users. But now with LLMs, software isn't precious.
LLMs can do fiddly slogs that are meticulous and require expertise.
LLMs can do fiddly slogs that are meticulous and require expertise. Vercel is all about lots of small fiddly details for a great developer experience. You...
AGI arising from a single model seems unlikely to me.
...nlikely to me. But a bottom-up AGI, where every person can marshal the power of LLMs to create compounding tools for themselves, feels way more plausible to me. It would also be a runaway process that it's hard to reason about the mul...
LLMs are great at complicated problems, but terrible at complex problems.
LLMs are great at complicated problems, but terrible at complex problems. Humans are bad at both. But LLMs have patience, which is the main requirement fo...
Emergence is precisely the part of the system that doesn't fit into human brains.
...eces and layers and the outcome still feels like a miracle. Markets, evolution, LLMs, and life itself all have this characteristic.
I wonder if the whole focus on AGI is downstream of LLMs talking like humans.
I wonder if the whole focus on AGI is downstream of LLMs talking like humans. Like, the idea of a planetary scale omniscient personality is easy to imagine, and also terrifying. Chatbots make this kind of f...
There's a difference between builders and coders.
... Coders see coding as an end unto itself. Before, they looked the same. But now LLMs reveal the difference. Builders love LLMs, and coders hate them.
Systems that assume LLMs will be nearly perfect won't work.
Systems that assume LLMs will be nearly perfect won't work. LLMs will never be perfect. Resilient systems assume that they can be confused.
LLMs can be made to be default-converging.
LLMs can be made to be default-converging. Every input to them, if scoped small enough, it will do what a reasonable person would with that information. S...
Confused deputy attacks are about tricking someone who is powerful but kind of dumb.
...b. The expected danger of them is the multiplication of "powerful" and "naive." LLMs with access to sensitive data are the most confusable deputies ever!
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.
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...