Nice overview of how broad AI's impact actually is across the SDLC, it's easy to think of AI as "just faster coding." Still, the maintenance and project management angles you mentioned often get overlooked.

On the coding and testing side specifically, this is exactly what we've built our delivery model around at Ailoitte. As a custom development company doing AI custom software development, we've found the biggest gains aren't just in code generation, it's pairing that with automated testing and review so AI-generated output is actually production-ready, not just fast to produce.

Your point about AI reshaping traditional practices like agile development is playing out in pricing too, in our experience. If implementation gets meaningfully faster, hourly billing stops making sense, it's part of why we moved to fixed-price, outcome-based delivery instead. It's also becoming a real differentiator when clients are evaluating who's the best custom software development company for their build, since anyone can claim "we use AI" but fewer teams have actually rebuilt their process around it.

Good primer for anyone just starting to think about where AI fits into their dev workflow.