How Flint Hills Group Is Utilizing AI to Make Development More Efficient

Artificial intelligence (AI) is now part of our everyday language. It dominates much of the conversation around prominent technology – and for good reason, as it is also transforming the way we work. Just a year ago, as AI was becoming more prevalent, we wrote about when it made sense to apply it, as well as its limitations – at that time – in software development.

There are still limitations, but AI has also advanced to reveal numerous advantages in development. That’s why at Flint Hills Group we’ve made the conscious decision not to shy away from it, but to embrace it as a tool that makes us more efficient, more agile, and better equipped to serve our clients.

AI Is the New Reality

Interest in AI is accelerating. Some developers fear AI will replace their jobs but the truth is more nuanced. Just as the internet, email, and cloud technology redefined the way we worked decades ago, AI is simply the next disruptive leap, but at a much faster pace.

We see AI in that same category: powerful, imperfect, and destined to become something we can’t imagine working without.

Think back to the 1800s, when mechanized looms replaced manual textile work, but someone had to build, operate, and maintain those machines. Henry Ford’s assembly lines replaced custom work but required managers and technicians to run them. Automated phone switchboards replaced operators but created jobs for those who built and maintained the systems. Every disruptive technology in history has shifted the kinds of jobs available, and AI is no different – it will not replace the value of human expertise today, but developers who understand and use AI will outpace those who ignore it.

AI as an Efficiency Booster – Not a Replacement

At FHG we think of AI as a partner, not a competitor. A junior developer may take hours to figure out a task; AI can complete that same work in minutes. But it still requires a developer’s expertise – knowing how to ask the right questions, structure the right prompts, and evaluate the results – or the outcome could be incomplete or even wrong.

We believe it makes sense for our developers to use AI thoughtfully – leveraging it to cut down on tedious tasks, troubleshoot faster, and stay focused on high-value problem-solving. Below are some examples of how we’ve used AI tools:

• Package Installation & API Development: One developer used AI to add the Spring Boot Actuator package—a task that normally takes half a day. AI completed it in under five minutes. It also created four REST (Representational State Transfer) controllers and corresponding test coverage in just 13 minutes, saving an entire day of work.
• Custom Endpoint Creation: Instead of spending days sifting through incomplete documentation, AI guided a developer step-by-step to create a custom endpoint (the address where a client application can interact with a server to perform various operations).
• Automation Scripting: Our team has used AI to build complex automation scripts for tasks like software deployment and driver installation. While syntax occasionally needed adjustment, the AI adapted from corrections and delivered better results over time. Importantly, the human reviewed and refined the outputs to ensure accuracy.
• Tool Strengths: We’ve found that some AI systems are particularly good at generating code from scratch and adapting to our coding style, while others excel at refactoring or handling niche use cases. In all cases, outputs improve fastest when developers provide careful review and iteration.

These AI tools are like having a highly skilled assistant on hand – one that can generate, test, and iterate rapidly – but always under the careful review of experienced developers.

From Caution to Strategic Adoption

In that earlier blog about the risks and limitations of AI app builders we explored the potential downsides of using AI, from inaccurate outputs to privacy concerns. That caution remains valid. Used responsibly, the benefits can outweigh the risks. We have clear rules in place that we outline more clearly below.

The recent wave of tech layoffs at companies like Microsoft, Google, Meta, and Amazon underscores the importance of adaptability. Some jobs are disappearing, but entirely new categories of work are emerging to support, train, and manage AI systems. Those who embrace AI tools now will be better positioned for the future.

Our AI Guidelines

We’ve adopted a set of principles for AI use that help us work faster without sacrificing quality:

1. Use AI for speed, not shortcuts – AI is a helper, not a replacement for critical thinking.
2. Verify everything – AI can be wrong; human review is essential.
3. Protect client confidentiality – No sensitive or proprietary information is entered into AI tools.
4. Choose the right tool for the task – Each AI platform has different strengths.
5. Ask the right questions – Well-structured prompts lead to better results.
6. Iterate and refine – Rarely is the first AI output the final product.
7. Keep learning – AI evolves rapidly; so should we.
8. Use AI to teach yourself – Asking clarifying questions builds long-term skill, not dependency.

The Road Ahead with FHG and AI

Yes, AI will change jobs, just as it has in every other technological revolution. But at Flint Hills Group, we believe that those who embrace the change, learn the tools, and maintain their expertise will be the ones shaping the future of software development. Contact us to learn more about how we can power your app idea into development with our many years of expertise, and working smarter with AI tools.

Disclaimer: AI tools can produce incorrect or incomplete results. Flint Hills Group never uploads private client data to AI systems, and all AI-generated work is reviewed and tested by experienced developers before deployment.