Content by heather poulsen (3)

Heather Poulsen shares an optimization playbook for running agentic AI workloads in production on Azure, focusing on keeping multi-agent orchestration reliable while controlling token costs and latency. It highlights practical techniques like inference routing, prompt compression, RAG tuning, caching, and FinOps-style capacity planning.

Heather Poulsen outlines a governance-first blueprint for building scalable agentic AI systems, focusing on how to embed consistent controls and quality checks across user interactions, agent orchestration, integrations, data, and models so systems can scale without losing trust and oversight.

Heather Poulsen shares an event session overview on designing Azure AI Landing Zones as a production-ready foundation for deploying AI applications and AI agents at scale, with guardrails for networking, identity, security, governance, and cost control using Microsoft’s recommended architecture frameworks.