Want to build an AI app? Of course you do. Everyone does, and it’s changing the way the engineering world works. For a long time, companies needed teams of experts in machine learning to build AI apps. Now, they can hand it off to just a few people. A process that once required custom models developed by sophisticated data science teams has been condensed into an API. Like any advancement in technology, it brings some good and bad to the engineering space. Today’s APIs make it easy for AI engineers to create AI apps with advanced features no matter their level of expertise. But it also means they need a different skill set to stand out in their space.
AI engineers must now consider different challenges, such as how people will interact with AI apps and how to increase the consistency and accuracy of the results their apps produce. But they’re not alone in this. They also need help from the companies that are providing them with tools.
The Evolving Role of the AI Engineer
With an API, anyone can build an AI app. It’s a blessing and a curse. But not everyone can build a good and consistent app. Consistency is a crucial element for apps.
In 2022, an airline chatbot informed a customer they could receive a discount on a flight under the airline’s bereavement policy. The chatbot provided the wrong information, even though a bereavement policy existed. A court later ruled the airline was responsible for the information the bot provided.
From a technical perspective, all of the code for the AI app worked correctly. It sent the request to the appropriate server/database, retrieved the information, and sent the answer back to the user.
Whereas engineers of the past often worked in a more traditional software engineer role, such as a front-end, back-end or database engineer, today’s engineers will need to work more on considering the user experience. Simply put, their roles will be more customer-centric.
AI apps now answer complex questions and, maybe more importantly, they’re more specialized in the problems they solve. Some might be designed to handle customer inquiries. Others might deal with writing, data analysis, image generation, or more.
AI engineers will need to spend more time refining apps to meet the needs of customers and problems more than ensuring they work. But they’ll need to move fast to keep up with the AI space.
How Developer Companies Can Empower AI Engineers
One reason why the AI space is moving so fast is that developers now have access to models and APIs that shorten development time. Now, everyone is developing an AI app. For engineers to keep up, they’ll need easily accessible tools with a low barrier to entry, minimal learning curves, and appeal to engineers with varying levels of experience while being flexible enough to modify.
It will be up to developer companies to collapse the stack for them. Companies should build on sources that make it easier for engineers to use the languages they know. Reliable and stable sources that come with communities and extensions, like PostgreSQL, reduce the complexity of building an app. Extensions can also help engineers solve problems that are specific to their industries and customers.
For companies, it’s all about creating a process that’s as seamless as possible. Remove friction points. Make processes easier. Help engineers feel comfortable and confident with the tools they’re using.
The challenge now shouldn’t be about using the tools but getting them to solve the problems customers want AI to solve.
The Future of AI Engineering: Reducing Complexity, Increasing Impact
As AI engineers take on more responsibilities and companies tailor their solutions to meet their needs, the traditional tech stack needs to collapse. It’s the only way engineers will be able to keep pace with the quickly evolving world of AI.
As I said before, anyone can create an AI app, but not everyone can make it great. At the end of the day, an app is a product, and the best products—the ones that solve problems for customers and provide a great experience—are the ones that succeed.
To create AI apps that deliver a positive impact to customers, AI engineers will see the specialization of their roles shift from specializing in app development to app refinement. The best way for them to do that is for companies to condense the stack—and the process—as much as possible.
