I started learning programming about six months ago after years of being an advanced Excel user. I built increasingly complex macros to automate my work, and later used AI-generated scripts when the problems became more complicated or changed frequently. Eventually, I realized I wanted to understand what the code was actually doing, so I began studying programming more seriously, especially backend development. Frontend work has never interested me as much.
The learning process has been difficult, but I genuinely enjoy it. Most of the time I'm struggling, debugging, and feeling stuck, but understanding a difficult concept gives me an incredible sense of satisfaction. It feels more meaningful than a typical hobby, especially because my current job is repetitive and doesn't provide much mental stimulation.
I'm in my mid-30s and teaching myself without a computer science degree. I've also been a musician for more than 20 years, so I understand the difference between enjoying something and realistically building a career from it. I'm perfectly willing to keep programming as a hobby if that's the sensible choice, but I'd like an honest assessment of whether there is still a realistic path into professional software development, especially with AI changing entry-level work. Are there particular roles or areas where my Excel automation and business experience could help?
5 Answers
Yes, there are still programming jobs, but the entry-level market is competitive and AI has raised the expectations for new developers. That doesn’t mean you should give up. Your experience solving real workplace problems with Excel and macros is useful, especially for backend automation, internal tools, data workflows, integrations, and business software. Build projects that demonstrate practical problem-solving rather than only tutorial exercises, and learn to use AI as a tool while still understanding and testing the code it produces.
A self-taught career is possible, but it requires sustained effort and realistic expectations. Give yourself a defined period of serious study—perhaps a couple of years—and decide whether you would still value the learning even if it didn’t immediately lead to a job. Contributing to open-source projects can help because it teaches collaboration, unfamiliar codebases, version control, and review workflows. Your existing automation experience may also provide a better starting point than someone with no experience solving real business problems.
The industry is not uniformly collapsing. Many experienced developers are employed, but junior hiring is definitely harder than it was during the boom years. Conditions vary heavily by location, company, and specialization, so don’t rely on broad internet predictions. Look at actual job postings in your area, identify the recurring skills, and start applying once you have enough practical work to discuss. Rejection will be part of the process, but it can also show you exactly what to improve.
Anecdotes can be misleading in either direction. Some developers are getting plenty of recruiter attention while others are affected by layoffs, so larger hiring trends and local job data are more useful than either extreme.
AI can make individual developers more productive, but it still struggles with requirements, architecture, debugging unfamiliar systems, security, and deciding whether a solution is actually correct. Those fundamentals remain valuable. The job will change, and fewer people may be needed for some kinds of routine work, but companies still need people who can understand a problem and take responsibility for a reliable solution. Keep learning programming fundamentals, data structures, databases, testing, and system design rather than becoming dependent on generated code.
The concern is still legitimate: AI can let one experienced developer handle much more work, which may reduce the number of junior openings. That makes the transition harder, but it doesn’t make the career impossible.
Don’t assume you have to compete only for generic web-development jobs. Look at automation, operations tooling, data engineering, QA automation, embedded systems, industrial software, technical support, and roles where programming is combined with knowledge of a particular business. Companies outside major technology hubs often need people who understand both the technical side and the practical problems employees face. A degree could improve access to some employers, but it is not the only route; a portfolio showing useful, finished work can open doors too.
The degree-free route hasn’t disappeared completely, but you need something substantial to compensate for the missing credential: useful projects, open-source contributions, relevant work experience, or strong domain knowledge.