It may sound weird, but it's based on my 20y observations in the industry (including teaching noobs).

Given the goal, you don't want to bee strategic about learning technical skills.

It is a botomless pit - the more you dig for the sake of improving a skill - the more there is to dig. And the worse you feel about yourself, the more unrealistic your goal seems.

The best thing I would do in your place is stay focused on the business goal - i would try a couple of courses, books that is think would get me to shipping some specific product in mind ASAP. You don't have (and even better not) to be a good coder to launch a product.

You only need to be good enough to launch and get your first client. Then the users/market would hint you specific directions and highlight your gaps pretty well.

If your product is complex - I would dumb it down to some school class grade prototype and attack it first.

When you just want to play a cool song on a guitar — you learn the song. You don't spend years of your life becoming a decent guitarist, unless this (or procrastination) is you real goal.

Specific piece of advice: Ruby on Rails is your friend.

All batteries included, noobs friendly, time saving framework designed for one-man shows / quick prototyping. Yet mature enough to scale with you out of your prototyping phase.

Countless of startups has been started (and most continued) as Ruby on Rails web app.

I would not waste time with today's prompt engineering. The results are iffy, and the tech is evolving. I'd focus more on understanding how complex apps are structured. When AI hits its next big inflection point, it will be able to handle everything shy of the actual architecture of your app. I'd focus skills on being able to lead a team of coders, and then you can do so whether they are digital or human, expanding your capabilities in tandem with AIs improvements.

I'd also focus on determining the right use cases for AI. Right now, people are throwing it at everything, including processes and problems that need deterministic answers. LLMs are non-deterministic, so some people are not using them correctly yet. They are trying to pound in nails with screwdrivers.

All that to say that if I were you, I'd get good at understanding the current AI capabilities (and not limited to LLMs), applying it to the correct product and dev features, and being able to lead both AI and humans through the gaps, selecting the correct team member to solve the problems which cater to their strengths.

I'm lucky in the sense that what got me back into coding was a very specific set of personal needs that drove me mad in the best way with passion. I'm not a technical wizard, but coding and growing over the last few years has to count for something.

As you grow in skill and familiarity you will add features and configure more pieces to work together.

After all of this (in years) you will hate everything you’ve done and have had to do to get things working (and they have.) You will dream of a day when you can scrap it all for a new from scratch exhibition of all that you have learned.

Someday you will.

Until then, just hobble things together so they work in the environment you are most confident in, like everybody else.

Even fewer make a net profit. You're probably going to lose money here unless you want to work for a corp.

I'd go with Python or JavaScript. It depends on your first project. Python is basically very good with data science and okay at everything else. JavaScript is almost the only way to build a website and okay with other things.

Write something simple. Like a sales tax calculator with Python. Then slowly build yourself up to other more challengingly things.