The 4 Patterns of AI Native Development — Patrick Debois (AI column)

I watched a short but interesting one yesterday. speech Patrick Dubois, a DevOps expert, co-author of the DevOps Handbook, an expert in integrating AI into development. This performance took place. 4 June 2025 AI Engineer World's Fair 2025 San Francisco is the largest industry event dedicated to the practical application of AI in engineering. The conference gathered around 1000 Founders, Vice Presidents and Leading Engineers from Around the World (I watched this conference live with great interest, which was available on YouTube.).

Patrick’s key insights are that we’re now in a transition from conventional development to AI Native. It’s similar to how we’ve all moved towards cloud native, but now we have a new wave of change. As a result, engineers are changing 4 direction

1. From manufacturer to manager. Developers are writing less code themselves, instead managing AI agents that generate code. The time to write code is reduced, but the time to review increases - the cognitive load increases. 2. From implementation to intent n The focus shifts from “how to do” to “what to do.” We describe purpose and requirements, allowing AI to find a solution on its own. There are specification-centric tools. 3. From delivery to discovery The cost of experiments has dropped dramatically. It is now possible to quickly prototype, test multiple variants and explore new ideas before making decisions. 4. From content to knowledge n AI provides motivation to systematize and retain team knowledge. Accumulated expertise is becoming a competitive advantage of the company as product creation becomes more automated.

To sum up, AI is not replacing developers, it is changing the areas where we create value. Understanding these patterns will help engineers effectively position themselves and their teams in the changing development landscape.

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