With the rise of AI, everyone thinks the rules of software engineering don't hold anymore

They are wrong. A lot.

What I found is that old laws are here to stay, and even a few of them are even stronger than before.

Take an example of an Conway's Law. The system is shaped by how its builders communicate. Now, we build with agents, and the same thing happens just one layer down. Boundaries between agents, the handoffs, and where it breaks trace back to how you split the work. If your agents don't talk to each other, you will get architecture that doesn't either. The law is now on the orchestration level.

Goodhart's Law is maybe even more visible. It says that the moment a measure becomes a target, it stops telling the real truth. We see this in many companies now with tokenmaxxing: people optimize their work to be at the top of token usage benchmarks because companies have started measuring it, but the real impact is missing.

Don't forget Hyrum's Law too. Given the system has enough users, every observable behavior becomes something someone depends on. AI models make this worse, because they are non-deterministic. A pipeline parses the output once, but the next time you depend on that pipeline, that could be changed.

None of these laws are new; some of them are a few decades old. AI didn't change them; it just raised the price of ignoring them.

I wrote about these and more than 60 others in my book Laws of Software Engineering: lawsofsoftwareengineeri…