The reality today is that AI tools are everywhere and constantly being pushed in our faces. Initially, like most people, I was skeptical of AI, partly out of fear of job displacement, so I dismissed it as nothing more than a glorified text autocomplete tool. But as these models continue to improve, seemingly every day, it’s become harder to hold onto that view.
This got me thinking about some fundamental questions: What actually is AI, and how do I maintain my value as an engineer? I believe a core skill that separates great engineers is the ability to be opinionated, but opinionated with evidence. It’s about extracting solutions while understanding both the problem and the underlying business needs. Sure, you can build something for one person or even a small group, but once you factor in enterprise requirements and the actual use cases that generate revenue, a simple black and white approach won’t work.
The problem I’m seeing today is that the definition of what AI does, and what AI actually is, varies wildly depending on who you talk to. In this time of uncertainty, it’s important to define what AI means to you. For me, as an engineer thinking about my own value, AI acts as a companion. I still feel weird personifying a chatbot, but reframing it in my mind as less of a persona and more of a sounding board really changed my perspective. This framing works for me because it puts AI in my toolbox. With it acting as a sounding board, I can run POCs and work through ideas. Ideas that I want to emphasize are my own.
The glaring issue I’m seeing is that a lot of folks are using AI and ending up not being opinionated. They’re not understanding the root problem, or why we’re solving a particular business case, or why we’re doing something a certain way. What non-code dependencies are we dealing with? What operational issues might we see coming down the road? These questions are extremely important, both to maintain your own value and to preserve the core engineering skill of solving problems. And to solve problems, you need to be opinionated.
Especially for new engineers entering the industry, it’s crucial to use AI as a tool to enhance learning and accelerate upskilling. But the key is learning to form your own opinions. Don’t just let the chatbot take you down its path. Being opinionated is what makes us creative.
To enable this, it’s important when using tools like Copilot to set context through prompting. I mean prompting in the sense of how you keep your value as an engineer. For me, the most important thing is to establish that I’m using AI as a sounding board. I’m not looking for it to give me a solution. I’m not asking it to solve anything. I want it to be a fast Google search and help me structure my own thoughts. Starting with something along these lines before presenting any problem I’m working on has given me great success. I’m still using my brain to understand the problem and why I’m doing what I’m doing. This gets my mind working, and I become a bigger asset to any organization I work for because code isn’t just written, it’s understood. For example, “Why do we have this if statement? Why don’t we use a different approach here?”
Prompting and context setting is super important. For early career engineers, it enables growth. For experienced engineers, it ensures they don’t lose the thing that makes them special.