This is a submission for the Google AI Agents Writing Challenge: Learning Reflections
I recently completed the 5-Day AI Agents Intensive Course with Google and Kaggle, and it was a positive and practical learning experience that strengthened my understanding of AI agents.
The course clearly explained what makes AI agents different from regular LLM applications—especially their ability to take actions and use external tools. Learning about the Model Context Protocol (MCP) helped me understand how agents can easily connect with APIs and external systems.
I also found the sessions on memory and context engineering very useful. The hands-on labs made it easy to see how short-term and long-term memory help agents handle multi-step tasks more effectively.
The module on agent quality, logging, and evaluation gave me a better idea of how to build reliable and production-ready agents. Understanding tracing, metrics, and observability was a big plus.
On the final day, learning how to move from prototype to production and how agents communicate through the A2A (Agent2Agent) protocol helped me see how multi-agent systems can work together in real scenarios.
Overall, the course was clear, well-structured, and very practical. It improved my confidence in designing and deploying agentic systems, and I’m grateful to Google and Kaggle for offering such a valuable program.
I’m grateful to Google and Kaggle for offering such a valuable program.
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