Production-Ready AI Agents: 5 Lessons from Refactoring a Monolith- Google Developers Blog

This post details the refactoring of a monolithic AI agent ('Titanium') into a production-ready system using Google's Agent Development Kit (ADK). Key technical contributions include: 1. Replacing a monolithic script with a 'SequentialAgent' pipeline composed of specialized sub-agents for improved reliability and separation of concerns. 2. Forcing structured outputs using Pydantic objects instead of prompt-based JSON formatting, leveraging ADK's dynamic structured output capabilities. 3. Implementing a dynamic RAG pipeline by replacing hardcoded case studies with an autonomous data intake system using Playwright for scraping and Google Cloud Vector Search for hybrid search. 4. Integrating OpenTelemetry for observability by using ADK's built-in support for distributed tracing and a tailored SSE streaming app for live telemetry. 5. Implementing cost optimization through ADK's native orchestration features like exponential backoffs and timeout boundaries, effectively installing circuit breakers.