In this video I break down Google ADK (Agent Development Kit) and why it’s a serious shift if you’re thinking in “production agent” terms instead of weekend demos. I walk through how ADK helps you design agents as modular components—tools, memory, and tracing—so you can actually reason about reliability, observability, and scaling. I also compare it against the OpenAI Agents SDK feature-by-feature, because the real question is: what makes an agent framework enterprise-ready beyond just tool calling? Then I go hands-on: I demo an agent that parses PDFs and answers questions using Gemini Flash, and I show how to run agents using ADK’s CLI and Web UI. Finally, I stitch it into a Streamlit app step-by-step so you can see the full “agent to app” pipeline. If you’re building workflows for finance/healthcare/law/research, this is the kind of system-design thinking I want you to copy: clear agent boundaries, structured tool use, memory where it matters, and tracing so you can debug what the model is actually doing.