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

The Hidden Data Economy Powering AI

People think AI suddenly became smart. But that is not really what happened. Humans trained it first.

On the recent CNA Insider documentary (check it out here: https://www.youtube.com/watch?v=7MVfAVnUF9Y) I heard this line: “I helped improve the work of AI and now the AI replaced my job.”

That sentence hit me hard. Because it explains the hidden story behind automation. Before AI can do human work, it needs data.

Lots of it. Real examples. Real conversations. Real human decisions.

Take customer service. For years, human agents answered calls, solved problems, and handled complaints. Now many of those same calls are used to train AI systems. The AI studies how humans respond. It learns patterns.

Then eventually, machine learning becomes machine doing.

Even those Captcha image tests, the ones asking you to identify traffic lights or crosswalks, helped train AI systems for self-driving cars. Humans labeled the world first. Machines learned later. That is the part many people miss.

Automation is not magic. It is built from human behavior turned into data. This does not mean every job disappears tomorrow. Many jobs are still too complicated and emotional for AI to fully replace.

But workers should understand something important. Today, people are not only doing work. They are also teaching machines how humans work.

And that may become one of the biggest economic stories of our time.

AI Is Not A National Priority

I joined Mimi Ong of Market Edge today for a conversation about AI and the future of work.

Honestly, one thing worries me: Many people still think AI is far away. It is not. It is already changing jobs today.

We talked about the BPO industry and how companies abroad are automating more work using AI. Customer support, reports, scheduling, and many routine tasks can now be done by software. That does not mean all jobs disappear overnight. But it does mean workers need to prepare now. Upskilling is no longer optional.

We also talked about government readiness. The DICT has a big role to play because infrastructure matters. Internet stability, cybersecurity, and reliable systems, like the eGov app, are important if we want to compete in the AI age.

But infrastructure alone is not enough. We also need to invest in scientists, researchers, and education. We cannot say we want innovation while refusing to fund it properly.

Near the end of the interview, I was asked what keeps me awake at night about AI. My answer surprised even me.

It is the children. Gen Z grew up with the internet. Now Gen Z are becoming parents. Their children: Gen Alpha and Gen Beta, may never know a world without AI.

That changes everything. We need to guide the next generation carefully. We need to teach wisdom, ethics, creativity, and critical thinking while helping them adapt to new technology.

If you want to continue the conversation, please visit https://www.resetph.com and join the webinar on May 20.

The mission remains. Need more coffee.

Check out more on my recent substack (link in comments).