Shifting Focus from Software to Value Creation

Understanding the problem space deeply before implementing solutions is the foundation of creating meaningful value in software development.

We often get excited about building cool tech solutions, but the real magic happens when we truly understand the problems we're trying to solve first. Taking the time to ask good questions, really listen to users, and validate our assumptions might feel slower at first, but it saves us from building things nobody wants or needs. Often, technically perfect solution completely misses the mark because we jumped into coding before fully understanding what would actually help users. The most valuable skill in today's tech world isn't how quickly you can write code - it's how well you can understand problems and find the simplest way to solve them, even if that solution isn't software at all.

The Mom Test

After this fundamental shift from solution-first to problem-first thinking, the next crucial skill is learning how to truly understand our customers through effective questioning. The Mom Test, a proven technique for customer research, teaches us that instead of asking what people want (which often leads to biased answers, just like your mom saying she loves your idea), we should focus on understanding their past behaviors, current problems, and actual experiences to uncover genuine insights.

The Rise of Problem Discovery

Building great software comes down to two things:

1. Understanding what's valuable to people (asking the right questions)
2. Having the skills to build it well (technical execution)

AI tools are making the technical part easier and faster. But they don't help much with understanding what's actually valuable to people. That still requires:

• Talking to users
• Asking good questions
• Understanding their real problems
• Identifying what solutions would actually help them

So while AI will help us build software more efficiently, it won't tell us what to build. That's why the focus needs to shift from "how to build" to "what to build" - because that's the part AI can't solve for us.

The real challenge isn't writing code anymore. It's figuring out what's worth building in the first place.