AI is an incredible force multiplier, but it’s an assistant, not an architect. It's like having a super-fast copywriter when what you actually need is an investigative journalist.

Exactly! Who is going to own the technical debt? AI won't be there at 3 AM to handle an incident response post-mortem when a weird edge case breaks the system.

The biggest risk right now is junior devs using AI blindly. If you can't debug the 'perfectly written code' when it fails silently in production, you aren't engineering safely.

As the saying goes: 'Programming is telling a computer what to do. Engineering is figuring out what to tell it to do.' AI handles the syntax; we still handle the strategy.

Engineering is fundamentally about empathy and communication—translating vague human desires into working systems. AI doesn't understand human nuance; it just predicts the next token.

I’ve noticed LLMs are great at greenfield projects, but the moment you drop them into a massive, messy 10-year-old codebase, they completely lose the plot.

AI can give you a perfect function to sort an array, but it can't tell you why your microservices architecture is experiencing a bottleneck because of a hidden network lag between AWS regions.

Writing code is just the implementation detail. Engineering is about understanding legacy trade-offs, scaling constraints, team dynamics, and business logic.