In software development, the real challenge often isn’t coding—it’s solving the right problems. In this episode of Building Better Developers with AI, hosts Rob Broadhead and Michael Meloche tackle one of the most overlooked but costly traps in tech: solving problems in software projects that don’t need solving, while missing the ones that do.
With the help of AI, they explore why teams often get stuck fixing symptoms instead of addressing root causes, launching features that don’t matter, or optimizing performance before users even exist. Through candid examples and sharp insights, they demonstrate how developers can shift their mindset to deliver meaningful and lasting solutions.
Solving Problems in Software Projects with AI
This episode begins with a lighthearted intro: No, AI won’t send killer robots to your house—but it can help you become a better developer. Rob and Michael let AI help set the topic: solving problems in software projects without actually solving the problem.
They explain how developers often confuse motion with progress. Writing code doesn’t mean you’re building value. Launching a feature doesn’t mean it’s needed. These illusions create technical debt and user frustration.
Michael compares this to marketing tricks, such as offering gift cards to attract users instead of improving the site to keep them engaged.
Solving the Right Problem in Software Projects
A quote from Einstein sets the tone: “If I had an hour to solve a problem, I’d spend 55 minutes thinking about the problem.” Rob and Michael emphasize the importance of understanding before acting. Too many developers rush to fix bugs without asking: What’s broken? What does the user expect?
Michael draws on insights from Dan Heath’s “Upstream“ to emphasize the importance of preventing issues, rather than just reacting to them. Effective developers think ahead and solve problems at the source—not just in the code, but in the system design and user flow.
Avoid Quick Fixes When Solving Problems in Software Projects
Rob warns against “band-aid fixes”—temporary solutions, such as increasing timeouts or adding unnecessary features. These surface-level patches don’t address the core issue and often exacerbate the problem.
Michael provides examples from the gaming world and enterprise software, highlighting instances where shipping buggy systems is done solely to meet a deadline, only to spend months patching them. Instead, they advocate for delivering a Minimum Viable Product (MVP) that truly addresses user needs.
Why Listening Solves More Than Writing Code
Michael shares a powerful technique: shut up and let your customer talk. Developers often assume they understand the problem after hearing a few words. But real insights come from listening deeply and asking open-ended questions.
Rob adds that great discovery comes from dialogue. Clients often reveal critical needs casually—things you’d never hear if you rushed through the requirements checklist.
Strategic Planning vs Feature Bloat
Planning is vital, but discipline is equally important. Michael recommends an early brainstorm to throw every idea on the table. Then, trim down ruthlessly to only what’s needed for your MVP.
Rob warns against premature optimization: spending hours adjusting colors and layout before functionality is in place. Significant development is about timing—doing the right work at the right stage.
Final Thoughts on Solving Problems in Software Projects
The episode concludes with a call to action: focus on outcomes, not output. Don’t measure your value by lines of code or number of features. Measure it by the clarity, stability, and usefulness of the solution you deliver.
Sometimes, the best move is to slow down, ask more questions, and think more deeply. Rushing to implement can lead to rework and frustration. Thoughtful, deliberate problem-solving builds better developers and better software.
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