Redefining My Understanding of AI Agents: A Five-Day Learning Experience

Source: Dev.to

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

Day 1 – Foundations of AI Agents

The first day introduced the core concepts of AI agents and their defining characteristics. I learned about sequential agents, parallel agents, and loop agents, which completely reshaped my view of how AI agents can be orchestrated. This foundation set the stage for exploring more sophisticated agentic architectures.

Day 2 – Custom Tools & Human‑in‑the‑Loop

While built‑in tools simplify many tasks, the real challenge is defining custom tools. I discovered that my existing coding skills remain valuable in the era of “vibe coding.” The hands‑on sessions covered:

• Creating MCP tools
• Managing long‑running operations with HITL (human in the loop)

These experiences reinforced that developers can still drive innovation by extending the platform with bespoke functionality.

Day 3 – Context Engineering & Memory

Prompt engineering is giving way to context engineering. On day three we focused on implementing both short‑term and long‑term memory for agents, enabling them to handle complex, multi‑turn interactions. With memory mechanisms in place, agents can maintain context across conversations, moving beyond toy projects toward mission‑critical LLM‑based solutions.

Day 4 – Reliability, Transparency & Evaluation

A production‑grade system must be reliable. This session taught us how to make AI agents robust and transparent using advanced metrics and evaluation strategies. Although the material felt initially dense, mastering these evaluation techniques is essential for delivering impactful AI agent solutions in business environments.

Day 5 – Prototype Development & Deployment

The final day centered on building a prototype that queries a vendor’s product database. We walked through the entire deployment pipeline, taking the agent from concept to a real‑world, usable service.

Conclusion

My five‑day journey provided a vivid glimpse into the evolving world of AI agents and agentic architecture. With a clearer understanding of foundational concepts, custom tooling, memory management, reliability, and deployment, I feel better equipped to shape my career and contribute to the next generation of AI‑driven applications.