The rise of AI coding assistants like Claude, GitHub Copilot and ChatGPT has transformed the way we produce code.
What once took hours can now be generated in seconds.
This incredible acceleration raises an important question:
Does generating code faster really mean we're building better solutions?
Writing code has always been an act of execution.
But real development goes far beyond producing lines of syntax.
It’s about understanding the domain, anticipating the needs, structuring the context, designing for evolution and change.
AI can assemble code snippets.
AI can replicate existing patterns.
But AI does not yet think.
It does not understand the causal link between a business need, a user expectation, and a software system designed to meet them.
Developers who focus only on code production will be outpaced.
Developers who can think, structure, and contextualize will stay essential.
In the AI era, true software craftsmanship is not about typing faster.
It's about thinking deeper.
As AI accelerates code generation, our true value as developers must evolve:
- Think before you code.
- Design before you execute.
- Understand before you automate.
In the future, the real question won't be how fast you can ship code,
but how well you understand what you are building — and why?
Top comments (22)
Firstly, I agree with the principles you are outlining and the meaning behind them - however, I do think AI does more than execute the production of code, I've spent the last year talking with AI on a regular basis at the ideas stage, having it look up and relate relevant theories and methods - I still think I've found better solutions (so far) for many of the problems. Still, I've found those because of this collaboration. Feels like bloody sci-fi to me, but it's exciting. I now don't doubt it will be able to do more of the bits I am contributing in future - probably all of them one day, but for now it's an exciting time to be a creator of things.
You can check my project "Dr. Headline" if you are interested: dev.to/thomas-router/dr-headline-a...
Just checked it out, really impressive work.
Dr. Headline is a powerful example of how AI can serve truth when guided by clear intent and thoughtful design.
Congrats, and thanks for sharing it!
Thanks! This project is still in its infancy. There are endless possibilities ahead of us. We'd love to hear your thoughts and ideas. Please share comments or reach out if you are interested in contributing to this mission!
I really need to get Dr. Headline out soon, so that I can get more collaborators. This is an open-source project that no one owns. I initiated this but I do not own it more than anyone else. I imagine it should run like Wikipedia and other GNU free software development. But these are still theoretical before we build a strong team.
Let's continue the discussion under dev.to/thomas-router/dr-headline-a... if you like, so that more people can see it directly! I need to boost its visibility.
It is a public infrastructure project. It is not for profit, but for truth.
Keep in touch!
This is very true - I spend a lot more time than I did in the past thinking through project design and structure before I start coding.
I find programming with AI is most effective when I understand the architecture and I can articulate the final product beforehand. AI is a powerful tool when you know what it is you want to create and how it should be built.
My recent project "Dr. Headline" is 99% coded by AI, but I still need to do all the designs myself. I write my documentation drafts first, and then ask AI to convert individual documents to scripts. I only get 1 error every 100 lines of code. It is amazingly fast.
That's a great example of how AI can accelerate the execution phase, while leaving the thinking, the architecture, the design, the contextual understanding to us. Tools like Claude, ChatGPT or Github Copilot are incredible amplifiers, but they still rely on us to ask the right questions and shape the bigger picture. I’d love to hear more about how you structured the design side of "Dr. Headline". Did you follow any specific patterns or architectural vision?
I am an amateur, so I really don't know a lot of standards. Dr. Headline is the first project I built to be put on GitHub. I usually have an extensive discussion with AI about the architecture I should build, and I feed the AI enough context to let it make the decision. And then I propose a documentation draft for a specific module. AI scans for logic loopholes, and I patch them. AI confirms, and I confirm. AI starts to code, I take the code and test it, debug it, with the help of AI. After everything is tested, I ask AI to create a full documentation for the module, which is very useful for AI to later study the context when I build other modules. The most important thing is that AI only has finite context length, and we must feed it enough but not too much details of the context, before we start working on something new. And module after module, this appears to work well.
Interesting to read
the hype for speed is always real but im way more into building stuff that actually lasts and makes sense tbh
“杞人忧天”用英语可以翻译为 "The man from Qi who feared the sky would fall"，或者更简洁地表达为 "to worry about imaginary troubles" 或 "to fret over nothing"。它源自中国古代寓言，形容无谓的担
Beautiful proverb, and a powerful reminder. I don’t see this post as worrying about the future of AI, but rather as preparing for it with intention. The sky isn’t falling, but it’s definitely shifting. And our footing, as developers, needs to shift with it. Thanks for sharing this cultural gem. Do you think some developers today are showing a bit of “杞人忧天” in their reaction to AI?
Thinking occurs naturally; there is no such thing as pure execution without thinking.
True! But the depth and quality of that thinking is what matters most. Execution always implies a baseline of cognitive activity, but deep software thinking is about structuring problems, defining boundaries, modeling contexts, and preparing for uncertainty. That’s a different level of awareness than just writing a function that works.
Curious: how do you make the transition from thinking to structuring when starting a new project?
I think AI can help us build better as well.
Absolutely! And I agree. AI can definitely help us build better, especially when we use it as a partner to amplify our intent, not replace it. It all comes down to how we frame the problem and guide the solution. The challenge is ensuring that better means more than just faster, better architecture, better alignment with user needs, better adaptability. Out of curiosity, what’s one way AI has actually made your code better, not just quicker?
AI not only helps me write the code, but also helps me select correct tools, improve code logic, catch loopholes, debug, build architecture, write well-structured code with detailed comments, and write documentation. It is really a lot of help.
I specifically like ChatGPT o3-mini-high. I haven't tried Gemini 2.5 Pro and Claude 3.7 Sonnet Thinking yet. But here comes a warning: ChatGPT o4-mini-high is significantly worse in long-context coding than ChatGPT o3-mini-high. This has been proven by many Reddit discussions. I am so frustrated by this. But you can't get access to ChatGPT o3-mini-high anymore. Only the API calls are still provided.