While AI coding assistants accelerate individual developers, engineering an autonomous multi-agent factory across an entire team's delivery workflow uncovers severe architectural friction. Moving past basic prompt generation requires robust state management, reliable cross-agent handoffs, and deterministic validation layers built on top of resilient cloud infrastructure.
In this highly technical session, we dissect the implementation of a 7-phase agentic software orchestrator engineered for safety-critical corporate environments. We look at the universal architectural patterns required to handle complex multi-agent state coordination, manage context window depletion, and balance lightweight local small language models (Phi via Ollama) with cloud engines (Azure OpenAI). Developers and architects will walk away with a practical architectural blueprint for utilizing deterministic validation gates to safely contain non-deterministic LLM behavior within production pipelines.
What you will learn:

- Orchestration Patterns: Designing resilient cloud backend layers to coordinate state and token handoffs between specialized AI agents.
- Deterministic Validation: Implementing schema-driven validation gates to securely intercept and verify non-deterministic AI outputs.
- Hybrid AI Infrastructure: Trade-offs and routing mechanics of splitting execution boundaries between local hardware and cloud APIs.