This is a submission for the Google AI Agents Writing Challenge: Learning Reflections

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I didn’t wake up one day wanting to build AI agents.

My journey into AI started by accident, when I read the first chapter of Rebooting AI by Gary Marcus and Ernest Davis just out of pure curiosity (Book lover over here) . Instead of feeling overwhelmed by AI, I felt… curious and as an engineer I felt a little behind (Where did I have my head stuck while this was being developed?). That chapter made me question what AI really is and more importantly, it made me want to understand it for myself.

Before the Crash Course: Learning in Small Steps

Before attending the AI DEV event that changed everything, I had already started building my foundation.

I completed:

• A Reinforcement Learning course by Hugging Face
• The Google Machine Learning Engineer course

I am a beginner and that’s okay. What mattered was that I was slowly starting to think in systems, models, rewards, and feedback loops instead of just using ChatGPT.

Then came the turning point.

I attended an AI DEV event in San Francisco, and it changed how I saw myself.

For the first time, I was surrounded by people who were actively building models, deploying systems, and solving real problems. I met incredible professionals who were generous with their knowledge and honest about their learning curves. I realized something very important that day:

Everyone is learning. Even the experts.

After that event, I joined the Google Developers Program, where I found hands-on cloud labs that helped me move from theory to real projects. While exploring these labs, I found the Google & Kaggle 5-Day AI Agents Intensive Course and here we are reflecting on it.

What I Actually Learned in the 5-Day AI Agents Intensive

This wasn’t just watching videos. It was thinking, experimenting, breaking things, and rebuilding.

I learned the difference between a simple model and an intelligent agent. Agents can perceive context, make decisions, take actions, and learn from results. It made me realize how collaborative AI systems can become. I learned that memory is not just storage. It’s part of intelligence.

This completely shifted how I think about designing AI systems. Also how important is to build honest and responsible AI, as well as avoiding bias.

It taught me that good agents aren’t just powerful, they are careful.

The final sessions focused on the gap between a working demo and a real-world system. I learned about deployment, scaling, monitoring, and iteration.

Am I an Expert Now?

Honestly? Definitely not.

And I’m okay with that.

I can now see the architecture behind agents, understand the language professionals use, and feel less lost when reading research papers or system designs.

I’m slowly understanding more every day, and that feels even more powerful than pretending to be an expert.

Why I’m Sharing This

I’m sharing this for anyone who feels like they’re “late” or “behind.”

You don’t need to be an expert to belong in AI. You just need curiosity, discipline, and the courage to start (fighting imposter syndrome).