A couple of months ago in Miami, I sat down and dumped my brains

AI engineer Miami shares hot takes on the future of software development, arguing that while anyone can now generate code using AI tools, true software engineering requires deeper skills. He warns that developers who fail to understand coding agents or lack curiosity are replaceable, and predicts an explosion in the number of developers as AI makes software creation nearly free.

A couple of months ago in Miami, I sat down and dumped my brains. Here's the interview... Some personal hot takes from AI: Engineer Miami follows... 1. Software development is a dead-end profession because anyone can be a software developer now. 2. Anyone can use Cursor or any other tool and generate code. Being a coder and being a software engineer are different. 3. Computers used to be gated; now everyone has the power to make computers malleable. Everyone is a software developer now, but that does not mean they are software engineers 4. If you cannot demonstrate how a coding agent works, you are just a consumer and have imposed an artificial glass ceiling on your career as a software engineer. 5. If you are curious, you will have a job. If you have not been curious in the last two years, you are replaceable. 6. SaaS per-seat economics may become unstable as customers need fewer people to achieve results, prompting founders to think about new unit economics 7. Most companies will take two or three years or more to figure out AI transformation. 8. Some companies are already building AI native teams of five to ten people who can build with the grain of AI 9. There will be an explosion in the number of software developers. Software development is now essentially free, and tokens are cheaper than humans 10. Not enough engineers know what it means to be a product engineer 11. JIRA ticket monkeys are cooked 12. If your company has banned AI, you should quit that company 13. AI is more like a musical instrument than just a tool. Play with it, make discoveries, build intuition, learn where AI is good and where it fails