AI has spread like wildfire. In software development especially, it’s changing how we learn and solve problems. Instead of digging through documentation or reading long-form blog posts, many engineers now turn to AI for direct, tailored answers. It’s faster. It’s contextual. And if you know how to prompt well, it can even feel like having a senior engineer on demand.
But it makes me wonder:
Do people still genuinely care about technical articles?
Are long-form developer posts becoming obsolete, or are they evolving into something AI can’t replace?
Is there a kind of depth, perspective, or storytelling that only comes from reading someone’s full thought process?
Are we optimizing for speed over understanding?
AI gives answers, and articles often give context.
Maybe the real question is :
Are we building engineers who can ship fast or engineers who deeply understand what they’re shipping?
Curious to hear your thoughts, hmmm.
Top comments (49)
AI is powerful. I use it. We all do.
But here’s my perspective as someone building real infrastructure in Web3:
AI gives answers.
Articles give responsibility.
When I write, I’m not rewriting documentation.
I’m documenting a problem that actually exists — one I’ve faced while building a product that’s already live and tested.
Every article I publish is tied to something real:
• A friction point users encounter
• A limitation in existing tooling
• A deployment constraint
• A UX bottleneck
• A cost inefficiency
And more importantly — a solution that is already implemented inside my product.
That’s something AI can’t replicate.
AI can summarize patterns.
It can generate explanations.
But it cannot replace lived engineering decisions, trade-offs, failed iterations, gas optimizations, architecture pivots, and real production constraints.
When you read a long-form technical article written by someone actively building, you’re not just consuming information.
You’re seeing:
• Why a decision was made
• What alternatives were rejected
• What broke in staging
• What failed in testnet
• What scaled — and what didn’t
AI optimizes for answers.
Engineering optimizes for accountability.
If we only optimize for speed, we produce engineers who can prompt.
If we value deep technical writing, we produce engineers who can reason.
The future isn’t AI vs articles.
It’s:
AI for acceleration.
Long-form writing for depth, judgment, and engineering maturity.
And if your articles are grounded in real, deployed products — they don’t become obsolete.
They become proof.
Curious if this was written with AI. No shame if so
To be honest, No.
You can rest assured that the thought is real.
But as I mentioned (I use it) and I whispered in her ear to structure the thought.
Thanks@alejandro_steiner , this is golden.
Articles carry accountability, experience, I always refer to articles (but sometimes to AI also).. for a lot of problems, AI hallucinates, creates code that does not compile. AI has speed, but articles have depth. The fact is that some times, neither the articles, not AI have the full solution we want, only a part of it and we need to figure out things ourselves. And when we do, then we should share that knowledge :-) (my preference - article)
Thanks @shitij_bhatnagar_b6d1be72 for the comment. Indeed, finding balance is important in how we learn, either by depending on AI or reading an article.
Honestly speaking i only care about technical articles that are in my field of interest. For example, anytime i see any article about the cloud or infrastructure in code, because i am getting into that field i immediately open it to read it, just to learn something new. Because I have read some interesting technical articles that have taught me stuff i wouldn't learn in a textbook or a tutorial vide. I sometimes read technical articles out of curiosity too, if it is an interesting niche. So i would say on a personal level, it depends on the technical topic being shared in general, if i have an interest in it, i would definitely give it a read. If not, i just don't bother to read it at all
Safe to say people care about what really matters to them. But I would love to ask if you use AI for your day-to-day activity. Do you just randomly go to Hasnode, dev blogs, to see articles? curious on how often you use AI.
I usually just use google, and most of the time i get redirected to relevant articles. I barely use AI to find technical articles. I mainly use AIto simplify my lecture notes most of the time
Thanks @maame-codes, i get your point now.
welcome
I think articles are more important now than before, weirdly enough. Here's why — when I ask an AI something, I get an answer that works for the generic case. But the best technical articles I've read weren't about generic answers. They were about someone hitting a weird edge case at 2am, trying 4 different approaches, and then explaining why option 3 was the right call for their specific situation. That kind of battle-tested context just doesn't exist in AI training data yet. What I've noticed changing though is the format. Nobody wants a 3000 word tutorial anymore when the docs + AI can handle that. But a focused post about a specific problem, decision, or tradeoff? That's gold. Shorter, opinionated, experience-driven posts seem to be what actually gets engagement now.
I think this is a valid point; articles that are born out of real engineering experience tend to be the best, and sadly AI is too direct when it comes to giving solutions.
However, an engineer might have tried a different approach just to solve a problem; during this period, he documents his experience with all approaches and gives you the best possible case scenario. Context is everything!
I put a lot of value on human-written technical articles, now more than ever. LLMs are not capable of understanding the information they spit out, nor are they capable of fact-checking it. A technical article written by a person who has tested the code they're sharing is priceless now that the internet is so full of unverified slop
I care. I read. I write. Ironically, at the same time that AI gets a little better at faking human expertise ("thinking" ... "could" ... "often" ... "may" ... "Why this works!") another AI gets much better at detecting AI slop even without penalizing em dashes and missing perplexity. Humans get better at detecting slop, too, no matter if AI-generated or generic marketing spam.
I would argue that there is even more value for honest, thoughtful technical articles these days. The demand for skilled writers is still high because authentic voices are increasingly appreciated amongst the AI slop. It is not just about the content but also the form, the story behind.
On another more existential point: AI is trained on existing data, so we need to keep pushing our unique voices out there to keep innovation and original thoughts going strong.
Yes, but selectively.
Deep technical articles = gold for the 10% solving hard problems.
Tutorials serve the 90% building CRUD.
Engagement follows value.
I feel: We read what makes us better engineers, not what goes viral. Keep shipping! 🚀
I'm gonna have to disagree with this one, or the implications of it. Deep technical articles are gold for the people who are far enough on their learning journey to understand them (and/or far enough that the tutorials don't help anymore). Tutorials serve anyone who's still learning how to engineer, anyone who's still learning how to code, and anyone who's learning a new ecosystem. They're all deeply valuable to creating and maintaining a tech industry with skilled engineers, because everyone in said industry is at a different skill level in different fields. We're all learning, and the vast majority of human-written technical articles have valuable information to teach us--perhaps not you specifically, but someone else whose education needs are just as important as yours.
@mergerg Totally agree—all technical content has its place and helps someone learn.
My angle: Tutorials master the 90% (shipping CRUD fast). Articles unlock the 10% career multiplier (tradeoffs mastery).
Both scale different needs in the ecosystem. Tutorials = velocity for teams. Articles = maturity for architects.
Appreciate you pushing back—sharpens the point! 🚀
Fair point...
Neat dissection @charanpool ! Agreed!
What they are important for is changing in ways that you need to think about the audience and expectations in different ways then the old days, but people definitely care.
Honestly I think articles matter more now than before AI, not less. Here's why - when I'm building stuff and I ask Claude or ChatGPT for help, it gives me an answer that works. But I have no idea if it's the right approach or if I'm walking into a trap. Last month I was shipping a side project and the AI-generated auth flow looked perfect. Then I read someone's article about common auth mistakes in vibe-coded apps and realized I had like three of them. The AI never flagged those because it technically "worked." Articles give you the war stories and the why-this-will-bite-you-later context that AI just can't. AI optimizes for "does it compile" and articles optimize for "will you regret this in 6 months." Different jobs entirely.
Indeed, articles provide in-depth paths to success when solving a problem; it's great to know people still care.
Right? And the cool thing is when you write about solving a problem, you end up understanding it way better yourself. I've caught bugs in my own approach just from writing up what I did. Double win honestly.
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