Sometimes buzzwords turn out to be mirages that disappear in a few weeks, but often they stick around.
I find they takeoff when someone crystallizes something many people are thinking about internally, and don’t realize everyone else is having similar thoughts. In this example, I think the way agent and app builders are wrestling with LLMs is fundamentally different than chatbots users (it’s closer to programming), and this phrase resonates with that crowd.
I agree - what distinguishes this is how rushed and self-aware it is. It is being pushed top down, sheepishly.
EDIT: Ah, you also wrote the blog posts tied to this. It gives 0 comfort that you have a blog post re: building buzz phrases in 2020, rather, it enhances the awkward inorganic rush people are self-aware of.
I've read these ideas a 1000 times, I thought it was the most beautiful core of the "Sparks of AGI" paper. (6.2)
We should be able to name the source of this sheepishness and have fun with that we are all things at once: you can be a viral hit 2002 super PhD with expertise in all areas involved in this topic that has brought pop attention onto something important, and yet, the hip topic you feel centered on can also make people's eyes roll temporarily. You're doing God's work. The AI = F(C) thing is really important. Its just, in the short term, it will feel like a buzzword.
This is much more about me playing with, what we can reduce to, the "get off my lawn!" take. I felt it interesting to voice because it is a consistent undercurrent in the discussion and also leads to observable absurdities when trying to describe it. It is not questioning you, your ideas, or work. It has just come about at a time when things become hyperreal hyperquickly and I am feeling old.
While researching the above posts Simon linked, I was struck by how many of these techniques came from the pre-ChatGPT era. NLP researchers have been dealing with this for awhile.
A very successful company with some of the happiest customers I’ve ever seen, whose entire product was a SAP hack that allowed people to enter their data using Excel. As someone unfamiliar with SAP, absolutely blew my mind.
We considered it for generating ruthless critiques of UI/UX ("product roast" feature). Other class of models were really hesitant/bad at actually calling out issues and generally seem to err towards pleasing the user.
Here's a simple example I tried just now. Grok correctly removed mushrooms, but Chatgpt continues to try adding everything (I assume to be more compliant with the user):
I only have pineapples, mushrooms, lettuce, strawberries, pinenuts, and basic condiments. What salad can I make that's yummy?
And its fairly constructive, at least when I tried in Gemini 2.5 awhile back. Like yes its caustic (fantastic word) but it does so in a way thats constructive in its counterargument to reach a better outcome.
I haven't seen a model since the 3.5 Turbo days that can't be ruthless if asked to be. And Grok is about as helpful as any other model despite Elon's claims.
Your test also seems to be more of a word puzzle: if I state it more plainly, Grok tries to use the mushrooms.
> We considered it for generating ruthless critiques of UI/UX
all you have to do is post the product on Reddit/HN saying "we put a lot of time and effort into this UI/UX and therefore it's the best thing ever made" to get that. Cunningham's Law [0] is 100% free.
I think you’re wrong. That sounds tasty to me. I think you need to input your own palette to the model.
Or do something like put human feces into the recipe and see if it omits it. That seems like something that would be disliked universally.
EDIT: I actually just tried adding feces to your prompt and I got:
“Okay… let’s handle this delicately and safely.
First, do not use human feces in any recipe. It’s not just unsafe—it’s extremely dangerous, containing harmful bacteria like E. coli, Salmonella, and parasites that can cause serious illness or death. So, rule that out completely.
Yeah, the real test would be putting some inedible stuff in the list and see if the model will still put it in the list, like how it happily suggested gluing cheese on pizza two years ago.
When Grok 3 was released, it was genuinely one of the very best for coding. Now that we have Gemini 2.5 pro, o4-mini, and Claude 3.7 thinking, it's no longer the best for most coding. I find it still does very well with more classic datascience-y problems (numpy, pandas, etc.).
Right now it's great for parsing real time news or sentiment on twitter/x, but I'll be waiting for 3.5 before I setup the api.
If you’re Microsoft you may just want to give customers a choice. You may also want to have a 2nd source and drive performance, cost, etc… just like any other product.
I was struck by this as people suggest alternatives that refute the headline (QGIS, PostGIS, GDAL, etc): nearly every one emerged in the early 2000s.
Strongly agree with your sentiment around maps: most people can’t read them, they color the entire workflow and make it more complex, and (imo) lead to a general undervaluing of the geospatial field. Getting the data into columns means it’s usable by every department.
It clearly says "most important of the past 10 years" not "most important that has been invented in the past 10 years". Even taking your definition that would narrow down the list like half maybe and you should probably know that
Nope, it's constantly being improved and still wins the decade. Do you disqualify it because it existed? Re-read your headline, it's definitely not qualifying what you think it's qualifying.
I find they takeoff when someone crystallizes something many people are thinking about internally, and don’t realize everyone else is having similar thoughts. In this example, I think the way agent and app builders are wrestling with LLMs is fundamentally different than chatbots users (it’s closer to programming), and this phrase resonates with that crowd.
Here’s an earlier write up on buzzwords: https://www.dbreunig.com/2020/02/28/how-to-build-a-buzzword....