Your Job as a Developer is Changing Faster than You Can Imagine
You're aware that we are on the cusp of a radical tectonic shift. The transformation is obvious. It feels almost magical, definitely weird, and fundamentally wonderful all at the same time.
Also terrifying.
Change is inevitable, but the rate of change is accelerating and there are moments in every smart devs days lately where we have to stop and consider "Will I be doing this in 5 years?"
The good news is that the answer is "yes" for most of us, particularly if you want to keep doing this work.
"Yes, but..."
There's so much hype around Generative AI that it's easy for the signal to get lost in the noise. Do we all need to buckle down and learn linear algebra and start training base models in our home labs?
Definitely not.
That layer of expertise is often interesting and absolutely valuable, but for most working developers we are going to be using these tools much closer to the customer and further away from the lab.
The Essential Skills of an AI Engineer
There's a new job title in town and it's AI Engineer. The AI Engineer is building applications and using GenAI tools to deliver value to their team and their customers.
The AI Engineer delivers consistent results with an often inconsistent tool. GenAI is by it's very nature inconsistent, but business demands deterministic results. The professional AI Engineer understands this need and works with the state of the art tools, patterns, and practices that get the job done.
Skills like prompt engineering and running evals are essential to the AI Engineer, and absolutely critical to the success of projects that want to leverage the power of generative AI inside of real business processes.
It's not easy. In fact, it's incredibly challenging which is why the default seems to be simple chat bots that more often than not piss off customers and cause more hassle than they are worth.
To make it even more complicated, the frontier of AI is moving so fast that it is a part-time job to keep up with the releases, techniques, and best practices required to do real work.
But, once you wade through the hype, there is a very real core of truly radical tools that are at our disposal and expert knowledge in their use and application is what is going to set you apart in the coming decade.
How to Get There
Curiosity is essential. You are fascinated by technology and want to understand how it works and how you can apply it in your work. If you're not interested in learning and exploring new things, the path of the AI Engineer is going to be long and hard.
Guidance is key. You need a trusted guide to filter out the nonsense, hype, and FOMO and help you find your way.
You'll need to build and practice what you learn, starting small, and understanding how the skills of the AI Engineer fit into the work you are doing today.
AI Engineering is the practical application of AI tools and techniques to solve real boring old business problems in new and interesting ways to deliver immense value to your team, the business, and your customers.
It's not easy, the effort is heroic, but the rewards are immense.
