I became a software architect after over a decade of experience as a software engineer, developing code in multiple languages ​​and across multiple tech stacks, from embedded to mobile to SaaS. I understand the nuts and bolts of programmatic code, and even though I’m no longer writing the code myself, I rely on my software development background to make high-level decisions and drill down into the details when needed. If we as tech leaders do not ensure that we have equal knowledge and experience in the field of GenAI, we will not be able to lead the architecture of modern systems.

In other words — I realized that I couldn’t be a good software architect without knowing GenAI. Similarly, if I don’t understand topics like algorithms, complexity, scaling, I can’t be a good software architect. architectures such as client-server, SaaS, relational and non-relational databases; and other computer science foundations.

GenAI has become Basic in computer engineering. GenAI is no longer a specialized subdomain that can be abstracted and left to subject matter experts. GenAI means new paradigms and new ways of thinking about software architecture and design. And I don’t think any software architect or tech leader can reliably make decisions without that knowledge.

It may be that the products and projects you lead remain AI-free. GenAI is not a silver bullet, and we need to make sure we don’t replace simple automation with AI when it’s not needed and can be harmful. All the same, we need to be able to at least. Consider this decision carefully.every time we encounter it.

I’m going to end with some positive news for software architects — yes we all have to ramp up and learn AI — but once we do, we need to!

As GenAI-based tools become ever more complex, data science and AI expertise won’t be enough — we need to take all these other factors into account. Keeping in mind the need to architect and design the systems we’ve been focusing on so far—scale, performance, maintainability, good Design and composability — there’s a lot we can contribute to.

But first we need to make sure we learn the new paradigms as GenAI transforms computer engineering – and make sure we’re ready to be the technical decision makers in this new world.