This is a submission for the Google AI Agents Writing Challenge [Learning Reflections]
5-Day AI Agents Intensive Course with Google and Kaggle
Learning Reflections
When I joined the 5-Day AI Agents Intensive Course with Google and Kaggle, I was excited to explore AI agents and understand how intelligent, autonomous systems are designed in practice. My goal was to gain hands-on experience with the Gemini API and the Agent Development Kit (ADK), specifically building agents that can use external tools and retain context across interactions. I saw this practical, project-based curriculum as an opportunity to bridge the gap between theoretical knowledge and real-world implementation.
As a BSCS student with a strong interest in AI, this intensive felt like an opportunity to move beyond concepts and observe how real agent architectures are structured and deployed.
Experience During the Intensive
This course introduced me to core ideas behind agentic AI, including how agents are structured, how they interact with tools, orchestration, memory, evaluation, and how multi-agent systems coordinate through routing and decision logic. These core concepts helped me see how large language models can move beyond simple chat interfaces and behave more like goal-driven and production-ready systems.
Challenges
One of the biggest challenges I faced was the pace of the intensive. The sessions were information-dense, and while I followed the lectures and labs, I realized that watching and completing content is very different from deeply understanding it. I was keeping up, but I wasn't fully digesting everything in real-time.
Then, reality hit. At the same time, my academic exams were ongoing, which limited the time I could dedicate to hands-on experimentation and completing the capstone project. It’s not about the completion certificate; it’s about the competence.
Key Realizations
This experience led to an important realization for me: meaningful learning in AI requires time, repetition, and deliberate practice. Exposure is valuable, but real understanding comes from slowing down, revisiting concepts, and rebuilding systems step by step. Even though I wasn’t able to complete the capstone during the intensive period, the course gave me clarity on what I need to focus on next.
What’s Next
Moving forward, I plan to revisit the Kaggle Learn Guide to reinforce foundational concepts and rebuild a simple AI agent from scratch before progressing to more complex multi-agent systems. This approach aligns better with my learning style and long-term goal of developing reliable, well-understood AI solutions.
Overall, the AI Agents Intensive helped me understand not only what agentic AI is, but also how I learn best. I’m grateful for the exposure, the structured resources, and the direction this course has given me for continuing my AI journey with intention and depth. I’m taking this AI journey seriously, and this course was the spark I needed. A sincere thank you to the instructors and the community for the resources, the challenge, and the inspiration.
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