Building a Technical Debt Factory with AI Agents

Are you looking for a job that lasts for a lifetime? Tired of projects that actually get finished and clients who are satisfied? Well, I have good news for you: there is nothing more sustainable than being a software engineer paid to maintain a mountain of technical debt.

And here’s the secret nobody is talking about: you can create your own technical debt factory using AI agents.

The Recipe for Success

The process is surprisingly simple. All you have to do is follow these proven steps:

Step 1: Run the AI agent with inadequate context. Why waste time explaining your codebase architecture, design patterns, or business requirements? Just jump right in with vague prompts like “make it better” or “add a feature.” The AI doesn’t need to understand the big picture—that would make the code too maintainable.

Step 2: Put no thought or attention into what you tell the AI agent to do. Thinking is hard work. Instead, just stream-of-consciousness your way through prompts. Contradictory requirements? Perfect! Vague objectives? Even better! The confusion will compound into beautiful complexity.

Step 3: Do not review its output. The AI generated 500 lines of code in 30 seconds? Ship it! Reading code is for people who don’t trust technology. Besides, you’ve got more features to generate.

Step 4: Accept huge volumes of code with no review. Why review when you can just accept? The AI is probably smarter than you anyway, right? Just merge those pull requests. All of them. At once.

Step 5: Do not test, lint, or format any of the code. Tests slow down development. Linting is just the computer being picky. Consistent formatting is a waste of time. Real developers ship fast and fix in production.

Step 6: When the AI agent makes mistakes, let it! Does the app technically work, riddled with errors and abundant extra code that seems to do nothing at all? Great! This massive mound of technical debt is going to cause the client endless frustration, so they will have no choice but to continue to hire you to clean it up—forever!

All you have to do is run the latest AI agent tools on your codebase with zero discipline.

Advanced Techniques: The Force Multiplier

However, if you really want to increase the amount of technical debt exponentially, here’s the secret weapon: give AI coding tools to a junior developer and tell them to just trust the AI.

Think about it: a junior developer doesn’t yet have the experience to recognize when AI-generated code is subtly wrong, violates best practices, or introduces security vulnerabilities. They haven’t built the intuition to spot the difference between “works right now” and “will work in production for years.”

Combine inexperience with blind trust in AI output, and you’ve created a technical debt multiplication machine. The junior developer will happily accept every suggestion, merge every change, and generate code at a rate that would take a team of seniors months to untangle.

You will have your own mountain of technical debt in no time, ensuring the entire team has long-term employment!

The Alternative Nobody Wants to Talk About

Or… you could actually review the code.

You could use AI agents as powerful tools that augment your capabilities rather than replace your judgment. You could provide proper context, review every line of output, test thoroughly, and maintain the same quality standards you’d apply to human-written code.

You could use AI to move faster while thinking harder—generating boilerplate quickly so you can focus your mental energy on architecture, edge cases, and maintainability. You could treat AI suggestions as first drafts that need your expertise to refine into production-quality code.

But where’s the job security in that?

The Reality

Here’s the truth: AI agents are incredibly powerful tools. They can generate code faster than any human, suggest solutions you might not have considered, and dramatically accelerate development. I use them daily, and they’ve made me significantly more productive.

But they’re tools, not replacements for thinking.

Every line of AI-generated code needs review. Every suggestion needs evaluation. Every output needs testing. The AI doesn’t understand your architecture, your constraints, or your users. You do.

The real value of AI coding tools isn’t in generating mountains of unreviewed code. It’s in generating good code faster, with a human expert in the loop ensuring quality at every step.

Use AI agents to move faster. Use them to explore solutions. Use them to handle tedious boilerplate. But never, ever turn off your brain and trust them blindly.

Unless you’re building a technical debt factory. In that case, carry on.