I Talked to a CTO About AI, Here’s What Everyone Gets Wrong

Talking with fellow CTO Raven Duran taught me interesting things about AI building. It reminded me that even though AI feels new and powerful, the rules of building good products have not really changed. What has changed is the speed.

A lot of developers today want to move away from doing daily operational work. They want to build products instead. I feel the same way. AI makes that shift feel more possible because you can build things faster than ever before. But speed alone does not guarantee success.

One big thing I learned is that most AI products do not start in a complex way. They start simple. Many early AI products are just APIs connected to other tools. You send data in, get a result out, and show it to the user. Behind the scenes, it often looks like a set of workflows instead of a big system. That may sound boring, but it works.

Some people look down on this approach. They say, “You’re not really building AI. You’re just calling an API.” I don’t agree with that at all. In the early stages, the goal is not to prove how smart you are. The goal is to find out if your idea matters to anyone. If users don’t care, the product fails no matter how advanced the technology is.

We talked about how many AI products begin as simple generators. From the outside, they may look basic. But when people actually use them, something important happens. The product earns the right to grow. Over time, you improve accuracy. You add smarter logic. You find ways to lower costs. Under the hood, the system becomes more mature, even if the user experience stays simple.

That growth only happens if users show up. This is why the biggest challenge in AI today is not building. Building is fast now. Tools are everywhere. You can create a working prototype in days or even hours. The hard part is choosing the right use case.

Too many people are building AI products that no one wants. They build something cool. They share it online. People say “wow.” Then no one uses it. This problem has nothing to do with AI. It’s the same old product problem: solving the wrong thing.

AI has made early product development easier, especially for small teams. Prototyping is faster. Testing ideas is simpler. Tools that existed before are now easier to use and more visible. More people can experiment, and that’s a good thing. It lowers the barrier to entry and gives more builders a chance to try.

Cost still matters, of course. AI services can be expensive. But in the early stages, many teams accept that cost in exchange for speed. Learning fast is often more valuable than saving money at the beginning. You can always optimize later, but only if the product is worth keeping.

The biggest lesson I took away from that conversation is simple. Start small. Use what already exists. Focus on real problems. Don’t worry about building the perfect system on day one. Let users guide you.

AI gives us new power, but it doesn’t change the basics. Products still succeed for the same reason they always have: they help people do something they care about. Everything else is just noise.

 

 

About Me:

Dominic “Doc” Ligot is one of the leading voices in AI in the Philippines. Doc has been extensively cited in local and global media outlets including The Economist, South China Morning Post, Washington Post, and Agence France Presse. His award-winning work has been recognized and published by prestigious organizations such as NASA, Data.org, Digital Public Goods Alliance, the Group on Earth Observations (GEO), the United Nations Development Programme (UNDP), the World Health Organization (WHO), and UNICEF.

If you need guidance or training in maximizing AI for your career or business, reach out to Doc via https://docligot.com.

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