Everyone’s Quitting Software Dev. I Just Rebuilt My Entire Product Line.

A post hit the front page of Reddit this week: “I think I’m done with software development.” Over 1,400 upvotes, 600+ comments. The thread was full of developers who feel burned out, replaced by AI, and questioning whether the career they chose still has a future. I read the whole thing. I understand the feeling. And I could not disagree more with the conclusion.

While that thread was happening, I was in the middle of the most productive stretch of my career. Over the past few months, our agency has discarded nearly every legacy addon in our product catalog and rebuilt them from scratch. New architecture, new UI, new features that would have taken us a year each to ship. We did it in weeks. Not because we hired more people. Because AI changed how fast we can move.

This is not a motivational post. This is what actually happened, why it happened, and what it means for anyone building software products right now.

Why I Discarded the Old Product Line

We had over a dozen WordPress plugins and addons built over several years. Some were selling well. Some were on life support. All of them shared a common problem: they were built for a version of WordPress that no longer exists. Classic editor assumptions baked into the UI. jQuery dependencies that should have been removed years ago. Architecture decisions that made sense in 2021 but created maintenance nightmares in 2026.

The honest truth is that maintaining old code was consuming more time than building new features. Every WordPress core update required compatibility patches. Every customer support ticket required re-understanding code that nobody on the team had touched in two years. We were spending 70% of our development time on maintenance and 30% on anything that moved the business forward.

The math stopped working. Patching old products to keep them alive was costing more than rebuilding them correctly. So we made the decision: stop maintaining, start rebuilding.

What AI Actually Changed

Let me be specific about what AI tools changed in our workflow, because vague claims about AI productivity are everywhere and most of them are useless.

Architecture decisions happen faster. Before starting any rebuild, I load the entire old plugin codebase into Claude and ask it to identify every hook, every database table, every API endpoint, every user-facing feature. What used to take a week of reading code takes an afternoon. I get a complete map of what the old plugin does, which parts customers actually use (based on support tickets and feature requests), and what can be dropped.

Boilerplate disappears. Plugin scaffolding, settings pages, REST API endpoints, block registration, AJAX handlers with proper nonce verification, all the repetitive infrastructure code that used to take days now takes hours. The AI generates it correctly, I review it, and I move on to the parts that actually require creative thinking.

Testing coverage that we never had. Our old plugins had minimal test coverage because writing tests felt like a luxury when we were already behind on features. Now AI writes the test scaffolding while I define the test cases. We ship every rebuilt plugin with PHPUnit tests covering the critical paths. This alone has cut our post-release bug rate by more than half.

Documentation gets written. This was always the thing that got skipped. Now every rebuilt plugin ships with complete developer documentation, hook references, and user guides. The AI generates first drafts from the codebase, I review and refine, and we publish. Documentation that used to take a dedicated week now happens alongside development.

The Rebuild Results

Here is what the numbers actually look like after rebuilding our product line:

Average codebase size dropped by 40%. Not because the plugins do less, they do more. The old code had layers of compatibility shims, deprecated function wrappers, and dead code paths that accumulated over years. Starting fresh with modern WordPress APIs and block editor integration produces cleaner, smaller code that does more with less.

Support tickets dropped by 60% in the first month after each rebuild launch. Cleaner architecture means fewer edge-case bugs. Better documentation means customers solve their own problems. Modern UI means fewer confusion-based tickets.

Development velocity for new features roughly tripled. When your codebase is clean, well-tested, and well-documented, adding a new feature is a matter of days, not weeks. The compounding benefit of a clean architecture is real and dramatic.

Customer satisfaction, measured by review scores and renewal rates, went up. People notice when a product gets genuinely better, not just patched.

Why “I’m Done” Is the Wrong Conclusion

I understand the burnout. I have felt it. The industry has gone through layoffs, AI anxiety, and a job market that felt hostile for a while. But quitting software development because AI exists is like quitting photography because digital cameras replaced film. The tools changed. The opportunity got bigger.

The developers who are burning out are often the ones doing work that AI is now doing faster. If your job was writing boilerplate CRUD endpoints, building basic WordPress themes from purchased designs, or converting Figma mockups to HTML pixel-by-pixel, yes, that work is being automated. It should be. It was never the interesting part of the job.

What AI cannot do is decide what to build. It cannot understand your customers’ actual problems. It cannot make the strategic decision to kill a product line and rebuild from scratch. It cannot evaluate whether a feature request is worth implementing or whether it represents a vocal minority. It cannot build relationships with the people who use your software.

The developers who are thriving right now, and I count myself among them, are the ones who use AI as a multiplier for the judgment and experience they already have. We are not being replaced. We are moving faster than we ever have.

The New Product Series

Every rebuilt plugin in our new line follows principles that the old products never consistently achieved: block editor native from day one, no jQuery dependency, REST API for every feature, proper capability checks and nonce verification on every endpoint, automated test coverage, and documentation that ships with the code.

But beyond the technical improvements, the strategic shift is what matters. We are not rebuilding the same products we had before. We are building the products we wished we had built the first time, informed by years of customer feedback, support tickets, and market observation. The old product line was a collection of things we could build. The new line is a collection of things people actually need.

AI made this possible not by writing the code for us, but by compressing the time between deciding what to build and shipping it. When the cycle time drops from months to weeks, you can afford to be more ambitious. You can afford to throw away something that is working okay and replace it with something that works great.

What I Would Tell That Reddit Thread

If I could reply to every developer in that “I’m done” thread, I would say this: the feeling of being overwhelmed by AI is real, but it is temporary. The developers who push through this transition period and learn to work with AI tools will be more productive, more valuable, and more creative than they have ever been.

The ones who quit are leaving right before the most interesting part. The hard, boring, repetitive work is getting automated. What is left is the thinking, the strategy, the creativity, the customer understanding, and the decision-making. That is the good stuff. That is why most of us got into this field in the first place.

I did not quit. I rebuilt everything. And I have never been more excited about what comes next.