Nothing about using an LLM removes skills and abilities you already had before it.
And yes, the goal might be to only use it for boilerplate or first draft. But that's today, people are lazy, just wait for the you of tomorrow
Just because you state it, it doesn't make it true. I could tell you that taking buses or robotaxis doesn't change a bit your ability to drive.
Taking a bus sometimes is fine, but that is missing literally the entire point that I made.
Now, maybe that is the future (no more/extremely little human-written code). Maybe that's a good thing in the same way that "x technological advancement means y skill is no longer necessary" - like how the advent of readily-accessible live maps means you don't need to memorize street intersections and directions or whatever. But it is true.
There was research about vibe coding that had similar conclusion. Feels productive but can take longer to review.
the moment you generate code you don't instantly understand you are better off reading the docs and writing it yourself
Funny story: The widespread of Knorr soup stock already made people unable to cook their own stock soup, or even worse, the skill to season their soup from just basic, fresh ingredients.
Source: my mom.
And just as with cooking: most people won't care - and the same goes with LLMs. It can be good enough... Less efficient? Meh - cloud. AI slop image? Meh - cheaper than paying an artist. LLMs to get kids through school? Meh - something something school-of-life.
I look around and see many poorly educated people leaning hard into LLMs. These people are confusing parroting their prompt output as knowledge, especially in the education realm. And while LLMs may not "remove skills and abilities you already had before it" - you damn sure will lose any edge you had over time. It's a slippery slope of trading a honed skill for convenience. And in some cases that may be a worthwhile trade. In others that is a disaster waiting to happen.
It will change. There will be FOSS models, once it no longer takes hundreds of millions of dollars to train them.
just three possible examples
But indeed it always struck me that some developpers decided to become Apple developpers and sacrifice 30% of everything they ever produce to Apple.
I would argue that it might a bit different though, because when doing iOS development it's possible that you don't lose you core skill, which is building software, and that you can switch to another platform with relative ease. What I think might happen with LLM is that people will lose the core skill (maybe not for the generation who did do LLM-less development, but some devs might eventually not ever know other ways to work, and will become digital vassals of whatever service managed to kill all others)
In exchange for 500% more paid users
Apple largely makes paying users exist that otherwise wouldn’t be there.
Apple is your business partner, doing marketing and distribution for you, and shares its user base. Bloomberg terminals provide real time data and UI to non-technical finance people. Github provides you Git hosting service so you don't need to setup and maintain servers. MATLAB (although there are Octave, Python and open alternatives) sells numerical computation environment to non-CS engineers. Xilinx is sells its hardware and dev tools. Game devs use Unity because they want to focus on gameplay and not game engine development.
These are all the examples of Division of Labor. This time, however, you have to pay for your core competency, because you cannot compete with a good AI coder in the long run. The value you provide diminishes to almost nothing. Yes you can write prompts, but anyone, even a mediocre LLM can write prompts these days. If you need some software, you don't need to hire SW engineers anymore. A handful of vendors dominate the SW development market. Yes, you can switch. But only between the 3 or 4 tech giants. It's an Oligopoly.
If we have FOSS alternatives, at least we can build new services around them and can move on to this new era. We can adapt. Otherwise, we become a human frontend between the client and the AI giants.
Sure, devs can still work without AI.
But if the developer who uses AI has more output than the one that doesn't, it naturally incentives everyone to leverage AI more and more.
And note that I objected online services, local LLM don't have the same issues.
Think of driving a car. If the shortest path (in term to time of travel) is through traffic jam, and there is a longer path where you can drive must faster, it's very likely that most people will have the feeling to be more efficient with the longer path.
Also the slow down of using LLM might be more subtle and harder to measure. They might happen at code review time, handling more bugs and incident, harder maintainance, recovering your deleted DB ;)...
I can see the impact on my own input both in quantity and quality (LLMs can come up with ideas I would not come up to, and are very useful for tinkering and quickly testing different solutions).
As any tool it is up to the user to make the best out of it and understand the limits.
At this point it is clear that naysayers:
1) either don't understand our job
2) or haven't given AI tools the proper stress testing in different conditions
3) or are luddites being defensive about the "old" world
```
The fundamental requirement for the LLM to be used is: don’t use agents or things like editor with integrated coding agents. You want to:
* Always show things to the most able model, the frontier LLM itself.
* Avoid any RAG that will show only part of the code / context to the LLM. This destroys LLMs performance. You must be in control of what the LLM can see when providing a reply.
* Always be part of the loop by moving code by hand from your terminal to the LLM web interface: this guarantees that you follow every process. You are still the coder, but augmented.
```
Not sure about you, but I think this process, which your source seems to present as a prerequisites to use LLM efficiently (and seems good advice to me too, and actually very similar of how I use LLM myself) must be followed by less than 1% of LLM users.
The deciding factor is not speed. It is knowledge. Will I be able to dish out a great compiler in a week? Probably not. But an especially knowledgeable compiler engineer might just do it, for a simple language. Situations like this are the only 10x we have in our profession, if we don't count completely incapable people. The use of AI doesn't make you 1000x. It might make you output an infinite factor of AI slop more, but then you are just pushing the maintenance burden to a later point in time. In total it might make your output completely useless in the long run, making you a 0x dev in the worst case.
So far almost no code I got from LLMs was acceptable to stay as suggested. I found it useful in cases, when I myself didn't know what a typical (!) way is to do things with some framework, but even then often opted for another way, depending on my project's goals and design. Sometimes useful to get you unstuck, but oh boy I wouldn't let it code for me. Then I would have to review so much bad code, it would be very frustrating.
If you meant goes down for good, then I'm sure it would be annoying for a few weeks for the FOSS ecosystem, just the time to migrate elsewhere, but there is not much GitHub specific we would really miss.
The 'take me from A to N' is a pretty broad problem that can have many different solutions. Is that comparable?
We can all see this end up in a oligopoly, no?