About modern AI and DX
It’s that time of the quarter I need to quickly (yet consciously) ship results, and gosh if my landscape of projects and libraries is fragmented these days … this story is about me unleashing the power of AI while wondering what is it that we are doing wrong, if anything!
The Pre-AI Era
We’ve all been there, and too many of us (developers) still are, the time where search engines’ answers mattered the most; the time where seniors would dig into every single detail they could through any project that had an easy to reason about or surf, to learn or use, documentation or APIs related pages, a time where “learning-before-using” was the norm, not the after-math.
During this time, choosing the best projects with the most satisfying websites, and with the best documentation out there, has been proven to be a successful strategy for both developers and AI training: caveats, edge cases, examples, the more the better to indirectly shape what came next!
During those days though, side projects or projects with not enough developers behind such documentation effort became, out of the blue, irrelevant … not because their ideas or solutions wouldn’t be the best out there for that specific project/idea, simply because SEO and/or training data wouldn’t include those projects/solutions in.
The AI Era
Please keep “this is my experience so far” as a constrain around anything I am going to tell you, but today I had a choice around a topic:
- learn how to do it the best way, ask reviews, improve my knowledge around that topic and everything else … or …
- ask AI to port one PL related thing to another PL related thing …
Due time constraints, I went for the second approach: I’ve asked AI to help me bringing something strictly JS and NodeJS related, to something strictly Python and Python only related, and it was “a few minutes in the making“: success 🥳
The Questionable
- have I learned anything new in that process? NO
- have I reviewed and tested everything produced worked at least as seamlessly as the NodeJS counter-part I’ve asked to migrate? YES
- am I satisfied about the outcome? Also YES
After all, without learning much around a topic I actually know a lot about in one PL I’m familiar with, I’ve managed to publish something for another environment and programming language I can surely read and write, but it’d take much longer for me to migrate as a whole.
The Elephant in the Room
In my quick, easy, tested and working, migration I’ve never needed to question any of this:
- what do those dependencies do?
- do I need the entirety of those dependencies for this purpose?
- is that the best way I can use such module API?
- how many things that API offers anyway?
- is it that easy to publish this module on another ecosystem?
Now, please bear with me, I am not that naive to publish something that couldn’t make sense out there, no matter the target platform or programming language, but in this whole process I’ve never needed to look at a single “beautifully documentation API related page” because AI had it all covered … and I started wondering …
- are beautiful and styled, modern, fast or efficient, documentation sites around any technology relevant in these days? AI doesn’t care about latest CSS hack to make the Web beautiful, all it cares is about API and documentation content: that’s literally it!
- as modern developers use more and more AI, does anything more complicated than a Markdown page makes sense to both show them eventually some extra content or tell AI how to fix/solve/work around a specific issue?
- is the Web, beside being the best target platform for everything out there, as it’s almost always surely available as a view for consumers, still relevant for developers, where all they need is more like an AGENT.md file, as opposite of something beautiful to read and learn from?
My Current Thoughts
The learning curve is moving from “which library would you use to solve this problem” to “which AI is best at helping you solve this problem” these days, and the answer is not trivial, the pattern is: nobody cares about beautiful documentation out there, everyone and everything cares about the availability of such documentation at least in its most valuable form, which is Markdown format, not HTML, and I wonder if we’re shifting from an “impress developers with such docs” era to an “impress AI with easy to grasp knowledge and solutions” one, where content becomes again “the King” over aestetic or “playfulness” of solutions: AI playing with that has no value, rather wasted tokens, developers using AI don’t read, surf or learn anything anymore, at least nothing they wouldn’t care about when the topic is outside their scope and already solved elsewhere with ease thanks to better AI related documentation.
Is this inevitable?
Yes, I think we’re facing times where nobody will learn anytihing extra or unnecessary and the details, caveats, edge cases, will be covered only by the most updateed AI out there, yet that knowledge and experience is (not so) slowly getting lost or irrelevant.
Nowadays it feels like a good-looking documentation site is an excercise that doesn’t bring value anymore, if not for developers coming from the pre-AI era, ’cause anyone else won’t ever even look at that website.
To me DX means helping developers, and if developers won’t look at anything online anymore, we gotta change the way we ship software: AI first or it never happened in the modern ecosystem 👋
P.S.
I am not trying to tell anyone documentation sites don’t matter, quite the opposite … I am trying to tell that the more playful is the documentation site for humans these days, the least AI in every human writing code these days would matter.
We need to understand old days are gone by all means, we should make some effort to make modern days more appealing for the new eyes of these times: AI eyes, not human anymore, I am afraid.
