AI Resistance: Why Your Codebase Pushes Back

AI is changing how software gets built, but it’s also revealing why some systems can’t keep up.

In this episode, Annika Packalén sits down with Lou Franco, author of Swimming in Tech Debt, to explore a growing phenomenon: AI resistance.

As teams adopt AI copilots, many expect faster delivery and better outcomes. But in reality, some codebases push back. AI struggles to make meaningful changes, introduces repetition, or even undoes its own fixes. The models aren't broken. The systems they're working in are.

What they’re exposing is something deeper:
architecture that was never designed to support this level of speed.

Together, Annika and Lou unpack what’s really happening beneath the surface:

• Why AI doesn’t create technical debt—but accelerates its consequences
• How “AI resistance” reveals structural weaknesses in your codebase
• Why "fixing technical debt" might be the wrong framing for the real problem
• Why speed without architectural clarity leads to compounding complexity
• What disciplined, AI-assisted engineering actually looks like

The conversation points toward a fundamental realization that AI doesn't reduce the need for architectural clarity. Instead, it raises the bar. The organizations getting real value from AI tools are the ones that invested in their foundation before adopting the tools. And for everyone else, the episode makes the case that it's not too late to start, but the order matters. Foundation first, then speed.

This episode is for engineering leaders and experienced developers navigating the pressure to adopt AI and move faster, while keeping the systems they build maintainable, scalable, and trustworthy.

The episode will air on July 21 - your calendar is packed? Register anyway to receive your video copy by email, the day after the live event.