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Agentic workflows are not just chat prompts with a loop. Production agents need explicit goals, tools, memory boundaries, evaluation, observability, and integration contracts. Azure AI Foundry and MCP give .NET teams a practical way to build that stack.

CQRS and Saga solve different but related problems: CQRS separates reads from writes inside a service boundary, while Saga coordinates long-running business workflows across service boundaries.

Event-driven architecture decouples services and enables scale, but it moves complexity from runtime coupling to data consistency and operational observability.

CAP is not a menu where you pick two. Partition tolerance is mandatory — the real choice is between consistency and availability when the network fails.

Never trust, always verify — zero trust moves security from the network edge to every request, every service, every identity.

Small review loops keep architecture decisions explicit while teams keep shipping.

RAG is not a single call to a vector database. Production RAG pipelines have five stages, each with tradeoffs that determine whether the system retrieves the right context.

Rate limiting protects services from overload. The algorithm matters less than where you enforce it and whether your counters are consistent across nodes.