I think developers should always learn to code, because some things can be much better described with programming languages than with natural language.

they use a lot of tech in surgeries but the people who perform those surgeries are highly qualified and actually understand both what needs to be done and how. they guide the machines they operate.

i reckon that's what we'll see with devs/engs

The most valuable skills will be critical thinking, domain knowledge, and the ability to refine AI-generated outputs. Experienced engineers and new devs alike should focus on adaptability—leveraging AI while mastering the principles that drive scalable, efficient, and secure software.

It's the time to prepare for single owner service business so as to ensure personal brand building for better future financially that can be scalable with right clients acquisitions and sustainability in recent and upcoming corporate employment reconstruction plans.

Doing research, processing lots of data fast, know how regarding cherrypicking which path to go. Knowing when to do more research. utlizing your brains capacity, and understanding its limits. Esp on time and focus. I wrote a bit about it here: https://eoncodes.substack.com/p/how-i-built-an-ai-wrapper-saas-in TL;DR. Its not coding anymore, its cherry-picking snippets w/ deluxe LLMs. 🍒 Then you have vibe-coding, which can serve as a start of a journey, or a quick one off.

Look at AutoGPT—it can already build and execute simple programs. The future of coding might be about guiding AI rather than writing lines of code ourselves.

As a business guy that started coding with AI, on my experience having code knowledge is crucial to understand the AI outputs and help solve/prevent errors on the code. When things start to grow, if you have no idea of what the AI is doing it tends to not end up well. The good aspect of it, is you can learn by doing much faster than just watching tutorials as the AI helps you to ship thinks faster.

In the end of the day the capacity to solve problems is the most important one. Being able to understand the challenge and break it into smaller pieces to get it done is the key, in my POV.

I think having a sense of product will always help. for example -- product hunt's "mvp" was a newsletter! If you have a keen sense of what to build, how to iterate to find a fit and how to talk to your users, I think you will have a lot of leverage.

I also think as soon as you start building things that are non-trivial you need expertise. AI is really great on the happy path where you are doing what has been done many times before. Over time it will probably continue to get better at the novel, but ultimately i believe at the top of the "skill band" there will always be room for people who can do what others cannot.

maybe that means working in a niche that isn't served with crud apps and simple business logic, or maybe that means being a really powerful "orchestrator" of AI. I think if you empower yourself to have skills that are better than average, you will probably be able to find jobs / projects without too much worry.

If you don't understand how code works, you can't fix anything that AI cannot fix on it's own.

It's important to understand the low level concepts and learn how to prompt AI to create those solutions.

Then if AI doesn't output the correct result, you can go in and fix it.

It's similar to how we use high level languages or abstracted libraries to solve problems. We don't need to necessarily understand the underlying implementation, but we need to understand how to use the higher level tools to solve the problem.

It’s necessary. We can't trust AI 100% because it only facilitates faster communication of ideas. Errors and issues that occur need to be addressed by humans who can recognize and fix them. Humans should have a clearer understanding of what AI is doing than the AI itself.