AI is rapidly changing the way we work.
Job seekers are using AI to assess new employers, while AI literacy is quickly becoming a standard job requirement — especially for engineers.
According to Wired, three in four coders use AI at least once a week, with 17 percent using it “most of the time.” While there are plenty of mixed feelings about AI among professionals across industries, many engineers see AI as a tool that can bring their projects to life faster than ever before.
DJ Taylor, a lead software engineer at Inspira Financial, has seen how AI can speed up a project firsthand.
He and his team recently used an AI coding assistant to build an AI agent at warp speed.
“The pace was unreal,” said Taylor. “Someone would throw out an idea and within hours, we’d have a working version ready to test.”
While AI doesn’t replace good engineering fundamentals, Taylor said it builds on them.
“It helps strong engineers move faster, learn faster and create more value for the people we serve,” he explained.
Inspira Financial provides health, wealth, retirement and benefits solutions for over 7 million accountholders.
What types of products or services does your engineering team create? What problem are you solving for customers?
First Dollar, acquired by Inspira Financial in 2024, sits right at the intersection of fintech and healthcare. We’re building a modern platform that helps third-party administrators and banks manage and customize health spending benefits. That includes powerful public APIs that make integration easy, plus two applications, one built for administrators and another that helps consumers access and use their benefits with confidence.
I get to work with an incredible group of engineers, product strategists and designers focused on employer servicing. Together, we take complex systems that touch payroll, financial accounts and data privacy and make them simpler for partners to use. Our goal is to give companies the flexibility to create benefits that work for their employees without all the friction that usually comes with legacy systems.
Tell us about a recent project where your team used AI as a tool. What was it meant to accomplish? How did you use AI to assist?
We recently started using an AI coding assistant and decided to test its potential with a three-day hackathon. My team built a Model Context Protocol server for our public APIs, which gives AI the context it needs to interact intelligently with our systems. We also developed “chunky tools,” or predefined workflows that help AI perform tasks more efficiently.
Time was tight, so we let the AI coding assistant handle a lot of the planning and implementation while we focused on direction, testing and quality. The results were incredible. In just a few days, we had a fully functional MCP server and an interactive app that lets users prompt an AI agent to explore our API ecosystem. It was one of those moments where you can see how fast technology is changing the way we build.
What would that project have looked like if you didn’t have AI as a tool to use?
Without AI, this project probably would have been a slimmed-down proof of concept. Instead, we built fifteen MCP tools and a working chatbot in just a few days. The pace was unreal. Someone would throw out an idea and within hours, we’d have a working version ready to test.
AI has completely changed the way I approach engineering. With AI tools that integrate directly into our codebase, I can use them to draft code, run tests and suggest reviews while I focus on higher-level problem solving. Every change is still reviewed and validated by an engineer before it moves forward, which keeps our development and security standards strong. AI doesn’t replace good engineering fundamentals; it builds on them. It helps strong engineers move faster, learn faster and create more value for the people we serve.
