Post #2537615

There are lots of misconceptions of what software engineering is, in the field trying to automate it. There are some things I want to make clear here. The purpose of software engineering is not to write code. Code is a liability, which will require maintenance for as long as it is used. Less code is better than more code. No code is the best. The purpose isn't even to solve tickets. Tickets are a representation of work to be done, yes, but this is from the time when the same people working in the same team, drinking the same coffee wrote and read the tickets, and discussed them freely without any boundaries. This representation of work leans on a mountain of shared silent knowledge. When the shared knowledge isn't shared, the text will be understood differently from how it was written. AI agents cannot know about your business unless someone takes time to bring them up to speed, chatting with them interactively. If they know this internally without interrogation, your business is redundant and has been done a thousand times before in the AI agent training materials. Removing the experience, the taste, the mentality from the picture will make systems regress to the mean. One of the most important processes in software engineering is the flow of knowledge into coded machine usable abstractions. This is not very different from how AIs are trained in general, garbage-in-garbage-out existed before AI models. So, the flow of knowledge needs to be not only of good volume, but also of high fidelity and quality. It is not all the same who you ask for how the cake is baked; it determines the outcome. Aggregating high volume, high quality knowledge in pragmatic forms will determine the business and technology topology of the near term future. We should not try to optimize for wrong things like numbers of tickets closed. In many things slow is smooth, smooth is fast. Especially in infrastructure and in production databases, changes should not be fast. Doing the correct things is way more important than the speed of doing things. If you try to hurry the process of interrogating the domain experts and the software engineers, you're just exhausting them and getting low quality as a result. You'll fail in mining and capturing what truly matters. Why not regress to the mean? The point is not only that we can observe the mean in our lives, and then focus on those things to make the next generation of systems better. Additionally, our distinctive tastes and ideas, ways of seeing things in themselves are a kind of a seed if nothing else, which allows us to not design the same restaurant with the same menu over and over, but to actually create true, informed variation, trying out different things by different approaches. If you plan a city using a single architect, you get those things where everything looks the same. There is value in tapping the uniqueness of vision, and add it on top of the dynamic power of agentic engineering. #AI #AgenticEngineering