Plan before you build: Deterministic planning patterns for AI agents

Can your agents scale without bankrupting your API quota or your compute budget? Join this session to explore a production-ready architecture that uses the LLM Council pattern, Google’s Agent Development Kit (ADK) for Java and Spring AI, all deployed on Cloud Run. And discover how replacing probabilistic reason-and-act (ReAct) loops with LLM Council enable goal-oriented action planning (GOAP) creates agents that are not only smarter but also significantly lighter and faster – making them the perfect workload for serverless execution.

About the venue
Free Times Cafe has bistro-style seating and a full food and drink menu. Please consider helping to support the venue by planning to have supper during the talk.

Speaker Bio
Dan Dobrin is an App Architect in Google Cloud, helping customer teams adopt modern AI technologies, cloud-native patterns, practices and technologies in GCP.

Dan focuses on building GenAI applications, adopting AI coding assistance tooling with Gemini, Native Java Images, Spring AI, event-driven architectures, production-readiness and performance optimization.

Prior to joining Google Cloud, he has built highly scalable, low-latency, frameworks for technology, security and financial services organizations.