Realistic learning paths? Technical SEO & AI learning. Data Analysis, Web Scraping, SEO Consulting, LLM use cases.

I’m 29 and have only about 4 experience into my SEO career. I started off in with a year in content for B2B industrial. Not much anything but something to put on my resume to get somewhere better. Moved to Local SEO for about 3.5 years and was client facing. In this role I consulted small to mid size businesses. There were few opportunities to manage accounts with technical challenges, and my company did not have any formal structure to addressing them. I was mostly let on my own to teach myself about things like developing recommendations for faceted navigations and stuff, and figuring out the language I needed to communicate the changes to developers. Now I’m 1 year into a role with a huge agency that has a lot of resources as well as processes for communication. I’m working on a huge enterprise account (one of the largest U.S. tech companies) with an amazing team. This feels like my first real opportunity to learn technical SEO on another level. I know from experience and talking to coders that coding isn’t something easily taught without actual projects to work on. What are some prompts I can use in a gen-AI tool which can help guide me down a realistic learning path for Python? Do you think Python will be a necessary skill for SEO in 5-10 years? Or are the basics enough for consulting/communicating with developers? I’ve read things like developing my own crawler or web scraper could be a good project, but this seems like a lot of work for little reward. There is so much material/content on how crawlers and LLMs work, because of this, what purpose could it serve me to learn how to create my own? What are some practical learnings I should take if I want to succeed in the future of SEO amid the exponential growth of AI for work?