Doc Ligot

The Turning Point That Made AI Coding Mainstream

The Month Developers Stopped Laughing at Vibe Coding

For years, developers argued about AI coding tools. Some loved them. Some hated them. Many were curious but cautious.

Then October 2025 changed the conversation. A new generation of coding models arrived. They were faster, smarter, and much more useful than earlier versions.

The result was simple. Developers started saving real time. AI could write routine code, create tests, and produce documentation much faster than before.

That did not mean developers suddenly trusted AI. Far from it. Most developers used AI every day, yet many still doubted the quality of AI-generated code. But they kept using it anyway.

Why? Because usefulness matters more than perfection. Think about spell check. It makes mistakes. People still use it.

For me, AI coding tools reached that point in 2025. Developers no longer saw them as toys. They saw them as tools. The smartest teams learned something important. AI works best when humans stay involved.

The AI writes a first draft. The human reviews it. The AI saves time. The human provides judgment. That balance is why vibe coding survived.

October 2025 was not when AI became perfect. It was when AI became useful enough that many developers could not ignore it anymore.

And that is usually how real technology shifts begin.

Read more in my latest Substack: https://docligot.substack.com/p/what-finally-made-developers-believe

We're Forgetting One Group in the AI Skills Race

Everyone says we need AI upskilling. Workers need new skills. Students need new skills. Entire industries need new skills.

I agree. But there is one problem. Who will teach them?

Sirang plaka nako on this issue. But I still discussed this with Jing Castaneda recently. The conversation around AI often assumes that learning will somehow happen on its own. It won't. Every training program needs instructors. Every classroom needs teachers. Every workshop needs facilitators.

That is why we should be asking: Where is the upskilling of the upskillers?

If we want people to learn AI, we first need teachers who understand AI. We also need to be clear about what kind of education we need.

There are two tracks. The first is specialist education. These are the engineers and researchers who build AI systems.

The second is AI literacy. This is for everyone. Most people do not need to become AI experts. They need enough knowledge to use AI tools wisely and responsibly.

That is why AI literacy should become a national priority. Just as basic computer skills became important during the internet age, AI literacy is becoming important today. But literacy programs require teachers.

Without trained educators, AI education cannot reach enough people. Instead of focusing only on workers, governments and schools should focus on educators as well.

How many teachers need training? What skills should they learn? How do we support them? Those questions may not sound exciting, but they are essential.

The truth is simple. Before we can upskill a nation, we must upskill the people responsible for teaching that nation.

Teachers are not a side issue in AI transformation.

They are the foundation.

Read more in my latest Substack: 👇
https://docligot.substack.com/p/no-teachers-no-ai-upskilling