Revenue up. Cash down. And nobody sees it coming because profit looks fine on paper.

This is the resilience gap. And it's worth understanding.

We're just getting better at automating the easy parts while the hard problems remain unsolved.

The companies winning this space will be those that augment developer thinking, not just developer typing.

The real question isn't which AI coding tool wins. It's whether we're creating better programmers or just faster code generators.

Every "revolutionary" coding AI release proves we're nowhere near replacing human developers.

The Cursor vs Copilot vs GPT-5 Codex battle misses the point entirely. None of these tools understand what they're building. They pattern-match from training data without comprehending software architecture, business logic, or long-term maintainability.

Meanwhile, developers are getting dependent on tools that can't actually replace deep programming knowledge. We're training a generation of programmers who can't code without AI assistance.

The reality is that current coding assistants are glorified autocomplete with better marketing. They help with boilerplate code and simple functions, but struggle with complex architecture decisions or debugging intricate systems.

Think about it - if these tools were actually good, why would we need constant "improved versions" every few months? Real breakthroughs don't need quarterly updates.

The technical specs matter: improved code generation, better debugging capabilities, and enhanced context understanding across entire repositories.

But here's the controversial take: this move proves that coding AI is still primitive.

The difference is intentional design. Companies that substitute tasks see hiring shrink. Companies that augment workers keep hiring.

The entry-level crisis is real but fixable. The question is whether your company builds the next generation or accidentally eliminates them.

Some companies are fixing this. Instead of deleting entry-level roles, they're redesigning them.

Smart managers pair new hires with seniors for AI output reviews. They measure junior impact on outcomes, not volume. They use AI to augment work, not replace learning opportunities.