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Comprehensive guide to evaluating LLM performance in production using offline metrics, online evaluation, human sampling, pairwise comparisons, and continuous monitoring pipelines.
Comprehensive guide to versioning LLM deployments including semantic versioning, model registries, canary deployment, A/B testing, and automated rollback strategies.
Build multi-agent systems using supervisor-worker patterns, agent specialization, shared state management, and result aggregation with LangGraph.
Build secure multi-tenant AI systems with tenant isolation, per-tenant prompts, cost tracking, and prevent cross-tenant data leakage in production.
Validate LLM outputs against schemas, business rules, and semantic constraints with automated retry and fallback mechanisms.