AI has spread like wildfire. In software development especially, it’s changing how we learn and solve problems. Instead of digging through document...
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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.
As I read somewhere "I'm not going to waste my time reading something that nobody takes time to write". So I try to read articles written from humans. If the article has some AI smell I close it immediately.
I think it is important in order to preserve a good quality of content but also to provide real knowledge and innovation. AI content leads to rotten knowledge, words that statistically looks good together but that doesn't provide real value.
Writing genuine articles are also important but what scares me is AI bots stealing this real content. Is there any way to block AI bots to consume this content? Ideas, thoughts, experiences, knowledge should be only for people, because people are the only one that can understand, can be inspired, can get real value from.
So yes, I think we should take care of genuine content by reading and writing it. If not what we are promoting is the death of innovation, the death of thinking by ourselves, the end of judgement. How can we solve new problems and challenges using AI that has been trained with obsolete content and data?
How can we avoid the AI slop that is flooding the whole internet?
I genuinely love reading technical articles , bcoz articles show the why behind the answer - the trade offs, the mistakes, the thinking process. That human layer , lived experince, judgement, is something prompts can’t fully replicate as of now.
I still love reading articles because they showcase a journey:
Someone walking through the mess, what they tried, what actually worked, and why.
You get the shape of their thinking, not just the final answer. With AI, you're often reverse-engineering understanding through a bunch of back-and-forth, and even then you don't know what you don't know. A good article surfaces things you'd never think to ask. AI is great for quick wins and execution.
Indeed, AI is built for accelerating development. Reading in-depth long-form articles offers more.
Honest take?
I still read technical articles — but my behavior has changed.
Earlier: I'd read entire blogs to understand a concept.
Now: I use AI to solve a problem, then read articles to deep dive.
AI gives me answers. Articles give me context, best practices, and the 'why' behind the code.
So yeah — articles aren't dead. They've just shifted from being my first stop to my second stop.
Quality over quantity matters now more than ever. 🔥
The question now would be how often you create time to deep-dive. I want to assume you use LLM in your day-to-day activities.
Your question really resonated with me.
I’ve been asking myself the same thing lately — who we’re actually writing for now that quick answers are everywhere.
I ended up writing a piece as both a response and an extension of that reflection: Who Are We Still Writing Technical Articles For?.
I think we need to shape a better idea of what tools we have at our disposal. I use AI for direct answers yes, because that is the tool I need in the case of work items. As far as deeper dives, I love reading through articles, to learn from the writer’s perspective, and two to learn the perspectives of others that comment. I use articles like this one as the tool of diversity, because growing my base or perspective helps develop my skills for my work
Please share your thoughts…
If nobody writes anything anymore, then what is there for AI to "harvest" (apart from official docs)? That says it all, in my opinion ...
I don’t think long-form is dead, it just has to earn attention now.
AI gives you the answer, but good articles give you the why. That depth, trade-offs, and thought process still matter.
Fast shipping is great… but without understanding, you’re just moving quicker toward bigger bugs 😅
I regularly check tech articles from blog platforms, newsletters, and developers I follow. For me, the main value is getting a unique perspective, discovering new trends, staying up to date with technology updates.
That said, I have the impression that the number and maybe the impact of tutorial articles is decreasing. I probably wouldn’t read or write an article about how to build a simple component in Next.js anymore. It’s often faster to ask an AI tool to generate and explain it.
So I think people still care about technical articles, but the focus may be shifting more toward insights, opinions, real-world experience and deeper analysis :)
I’m using this opportunity to put myself out there for roles in Developer Relations and Technical Writing.
I was laid off in January on the first workday of the year. It wasn’t how I imagined starting 2026, but it gave me something unexpected: time to reflect.
I spent the rest of January thinking deeply about my career, my strengths, and the kind of impact I want to make moving forward. That period of reflection brought clarity—about the value I bring and the direction I’m excited to pursue next.
I shared the full story of what happened, my past experience, and what came next here:
dev.to/miracool/laid-off-on-the-fi...
AI can provide useful guidance in successful scenarios. For example, if you're looking to learn how to work with X, AI can instruct you by saying, "Do X and Y, and you'll achieve Z." But what happens if you don’t achieve Z for some reason? In that case, technical articles can be extremely helpful. These articles often describe the challenges faced by others and how they resolved them, offering insights that AI cannot provide.
Tbh, even before AI I wasn't "deeply understanding" what I was building. It was basically just posting errors in google and hoping Stack Overflow or GitHub Discussions posted a clear solution. AI just sped that process up.
I think if you are someone who used Stack Overflow to gain deep understanding of issues, then you're doing the same with AI. It's more of a behavior amplifier than some new threat.
Also, fundamentally.. I think engineering IS more about try and iterate as opposed to understand deeply then nail it first try. This is supported by the pioneers of electrical/computer engineering as well as the cultlure of the biggest tech companies in the world. It just works better.
Yes 🤚🤚🤚🤚🤚🤚🤚