Ask HN: Balancing AI-Assisted Development with Deep Learning as a Founder

1 pointsby dennisyletztes Jahr2 comments

I’m a software developer and repeat founder who’s genuinely excited about what AI can do for our industry. In past projects, I’ve relied on AI coding assistants (e.g., GitHub Copilot, ChatGPT, Claude Code) to help me write boilerplate, generate suggestions, and speed up routine tasks. But every time I lean on these tools, I notice myself understanding concepts less deeply and becoming a bit “lazy” about fundamental problem-solving. To counter that, I’ve habitually limited my AI usage—kind of like how I allow myself only 30 minutes per day on Hacker News.

However, I’m now pulling together a new startup, and the stakes have changed. Speed-to-market isn’t just a fun challenge anymore; it’s a competitive necessity. If I don’t use AI to accelerate development, I risk falling behind. At the same time, I worry that over-reliance on AI will stunt my learning curve and leave me unable to debug tricky issues or refactor in a meaningful way. Has anyone else experienced this tension between “true learning” and “rapid launch”?

I’m not advocating for an “AI doom” mentality far from it. I want to embrace AI’s productivity gains, but I also want to make sure I’m still learning, able to debug, able to build robust architecture and improving as an engineer. If you’ve navigated this trade-off (particularly in a high-stakes startup environment), I’d love to hear: - What concrete strategies or workflows you put in place. - How you measure your own “proficiency” so you know you’re not losing the fundamentals. - Any pitfalls you ran into by either over-relying or under-relying on AI tools.

Thanks in advance for sharing your experiences and advice!

2 comments

elemcontribletztes Jahr

I think you could adjust your mindset on this issue.

AI is a tool.

If you already have the fundamentals neccessary to call yourself a software developer, ie. architecture, algorithms, language coding standards and style guides, UX, maintainability, robustness, correctness etc. then AI is just accelerating that for you, not exempting you from it.

If you need to scratch a learning itch then that's something else, and AI can help there too. Just ask it.

I also think if your product idea is so sensitive to a launch timeline that precludes manual coding not to fail, then you have a bigger problem.

dennisyletztes Jahr

Appreciate the reply, but sadly disagree with all of it.

> If you already have the fundamentals neccessary to call yourself a software developer

Yes, but do you not need to learn more? Do you not need to train what you know to keep it at your fingertips?

I think most would agree our memory has gotten worse since we have access to digital phone books, web search etc. This is because the mind does not need to store these things anymore.

The process here would be the same, your coding ability will degrade over time if not used.

> I also think if your product idea is so sensitive to a launch timeline that precludes manual coding not to fail, then you have a bigger problem.

I think here you just over reached with your point. If I can test and iterate x features / ideas vs 10x in the same month longer period, its fair to say that 10x would be deemed a better velocity with more chance of success. It is not based on my "idea".