What he said about kids not needing to learn to read for example because of the AI world we are going into, that pushed him way past the line for me.

I agree after using DeepSeek for many tens of billions of tokens for this point. Yeah Fable/Astra has more "magic", but not running out of token budget 5 days into the month is the right place to be. Plus, learning to deal with dumber models, only keeps you sharper as the programmer/agent wranger.

Could you compare with FreeTube?

I just wanna say, it's okay to prefer different terminals, like there were so many back in the day. people's dev flows become hyper specific, depending on what tools, editors, features they need... I used to use `st` back in the day, but also `urxvt` and the classic `xterm`, or `guake` for adventurous. One of my absolute favs is https://github.com/uobikiemukot/yaft which was fun to rock on classic Thinkpad T62p laptops without any X11.

It is fine, it is also fine to inquire which exact features they are looking for.

Yet https://openrouter.ai/rankings still shows exponential growth at every scale. So demand isn't slowing down.

It's showing exponential growth but mostly towards the value models (DeepSeek Flash, GLM 5.3 Flash, etc). Which might be an indication that these models are "good enough". At this intelligence level perhaps it's more about cost optimisations.

I cannot speak for everyone else but for us (20 people company) AI spending has definitely peaked and is trending downwards. We're consolidating providers and heavily experimenting with "good enough" models.

I can only imagine it's a small slice of users that are skipping the first party API's of the big labs to use openrouter instead.

Turns out selling one dollar bills for a dime does lead to growth, but not much else.

It goes way back, I work in AI/Ml (taken over by transformers/LLMs) space since early days of this "AI Summer". We get some nice grad school students interning from top universities. I met one during a trip to the office, from top notch school, introduced me to Triton programming when it first came out. It was early days of LLaMA just coming, when The Bloke was regularly dropping finetunes, I was joking asking him what the hacker stack was for "AI waifus" that the cool kids were using. Lo and behold he drops the name of the SillyTavern project. Which later was really educational in setting up local inference servers and in other ways, may have had to, ahem, delete some browser history.

I wonder if any doctors feel depressed about losing "creativity", or are instead yeah I can help diagnose and cure more people.

AI is going to be both a boon and a bane for doctors. Its "good enough" behavior will lead to complacency like it does any place where the automated system is "good enough" but the system still wants human validation. This will without a doubt result in some preventable tragedies that will end with more work and check lists (and probably not enough accountability). But there are other places where it will absolutely free up mental energy to focus more on the patient.

I was talking to my own doctor and their experience with a new note taking / transcription AI app they've been using, having worked on medical software before. One of the problems I noticed when designing software then was that software likes its categorized fields, with data entered just the right way and in just the right order. But medical work is almost never that neat and tidy. Patients and other medical professionals give you information in whatever order things come to their mind in, or in whatever order their own system and paperwork displays it. A simple prescription consisting of a patient's name, DOB, medication, medication form, dispensing quantity, refills and dosing instructions might be given to a provider in any order of those fields and no matter what order your software chooses, it won't be the same order as someone else giving it to you. Most providers that used the software I worked on resorted to hand writing everything down and filling it all in later, or having to ask for repetition over and over as they clicked through various fields trying to remember everything before it flicked out of their short term memory or the other person moved on. And as more and more systems and regulations require everything to be entered into electronic records, this has become more of a problem. To the point where you go to some appointments and you often don't even see your doctor's face because they're stuck behind a terminal nodding along as they try to capture everything you say into the specific fields in the system. AI tooling has the potential (and at least from my own doctor's experience, is already showing that potential) to free up the mental effort spent on getting the right data into the right fields. AI can do a great job of understanding that a free text field that says:

    Fucitol tab 25mg qid
    John Smith 01/01/75
    #30 3 months

and a free text field that says:

    Fucitol 25mg tablet
    30 tabs, 4x per day
    3 refills
    Smith, John 1975-01-01

say the same things, and get those things into the right fields in the record for you. They still need to go back and check it (and see the previous caveat about "good enough" systems) but by freeing the doctor from the mental load of intentionally categorizing all of the data they're hearing while simultaneously trying to reason through what all that data means and enter it at the same time they have more mental room to actually pay attention to the things the patient is saying, the things they're doing and the things the doctor is seeing.

And one thing I hope is that it makes switching doctors if you need to safer and more effective. The sheer volume of information a new patient can bring with them if they have all their medical records is massive and sorting through it all is likely something we'll never give our providers enough time and money to do. Things will get missed, or doctors will defer (consciously or not) to the diagnosis already listed, even if a more thorough review might reveal the diagnosis was wrong. An AI system designed to review an influx of data with an adversarial eye, or at least an eye towards looking for missed possibilities or potential reasons for the patient's dissatisfaction with the previous provider could go a long way towards helping end the sorts of "I went through 10 doctors all of which told me it was all in my head/I should try losing weight/I can't be experiencing this issue at my age, and then finally the last doctor had just finished reading a paper about how XYZ can cause these symptoms and now I'm finally getting treatment" stories anyone with friends or family with chronic health problems probably has heard more than once.

People mentioned it in the article, it used to be "innocent until proven guilty". No need for a third category.

You're presumed innocent unless proven guilty.

At the same time I'd rather an experienced dev with an open weight model vs a junior dev with Claude. I assume the experienced dev has good domain knowledge and can prompt his way out of the "lower intelligence".

I'm fine with DS Flash V4.1 in code bases I have experience in, don't really notice a huge difference other than more steering is needed.

Same, I went from being die hard Terminus fan to this. Been a long time daily driver.

Yep. :waves: to ones on similar path.. Switching off from Terminus was hard, but eventually unavoidable. Switched to Jetbrains Mono when Ghostty came out nearly 2 years ago..

oh man I used Terminus for so long till my finger hurt ... recently I was very happy with Cascadia Mono but now I've migrated to (as I was saying in another thread) Pragmasevka (derivative of Iosevka that mimics Pragmata Pro). It's really great.