Contrary to the general opinion, I feel that AI has IMPROVED my cognitive skills. I find myself discovering solutions to problems I've always struggled with (without asking AI about it, of course). I also find myself becoming much better at thinking on my feet during regular conversations. I believe I'm spending more time deep thinking than ever before because I can leave the boring cognitive stuff to AI, and that's giving my mind tougher workouts and making it stronger; but I could be completely wrong.
> C code admits many assembly interpretations and the assembly you get will vary depending on your compiler and parameters.
There's your own example defining how code is deterministic. Despite being compiled to different assembly interpretations, the code does the same thing.
Natural language is fluid and ambiguous while code is rigid and deterministic. Spec-driven development appears to be the best of both worlds. But really, it is the worst of both. LLMs are language models - their breakthrough capability is handling natural language. Code is meant to be unambiguous and deterministic. A spec is neither fluid nor deterministic.
Wow! I just wrote the article "Stop trivialising AI: it’s not your intern, colleague or compiler" today and shared on HN - https://news.ycombinator.com/item?id=47274213 - but I talk about different dangers though. Enjoyed reading your viewpoint.
Fair enough! Business and user perspectives are meta-data that explain the intent behind the code. I disagree with the point that intent should be the source of truth, though. Intent, like you explained, is high level and lacks the details to be an unambiguous source of truth.
Thanks for the feedback! I agree there needs to be visual indication for the knobs' min and max points. I'm thinking about how to do this without adding visual clutter.
Thanks for the feedback! Click and scroll up/down to turn the knobs. I will fix this as it isn't an intuitive way to control knobs.
EDIT: Done! Please disregard this comment.
Exactly! LLMs' (or any Gen-AI) lack of lived-experience/emotions is their Achilles heel. The best human creators understand how to inspire emotions mainly because they can feel it themselves. Most other humans, despite innately understanding emotions, can't really create things that inspire emotions in others. So, Gen-AI as we know it today can't really reach a point where it deeply, personally understands and inspires emotions. Vibe discovery bridges this gap, I think.
There was a very specific purpose here - to build a web-based accelerometer game. If I were to compare this with playing, I would say this is more akin to playing with a special kind of clay that shape-shifts itself based on your instructions.
As for the LLM-generated writing - I've updated the blog post with a 'meta' section explaining how LLMs generated the post itself. I've shared the link to the specific section as a response to other comments with the same criticism - I don't want to link to the blog again here and risk looking like a spam bot.
The blog post was written by Claude Code, reviewed by Gemini Pro, ChatGPT 5.2 Thinking, Kimi K2 Thinking, Deepseek Deep Thinking and me. Naturally, all the LLMs failed to judge that AI-generated writing is a turn-off for most readers. I failed to judge that too.
I misjudged the amount of dislike HN users have for AI generated writing. I have added a "meta" section explaining how the post itself was written by AI, directed by my own taste. Here's the meta - https://www.kikkupico.com/posts/vibe-discovery/#the-meta
To be frank, I don't think AI-generated writing is inherently bad. Since there appears to be a strong bias against it, I will stick to writing blog posts by hand.