designing-genai-patterns

From sumik

32 production-grade GenAI design patterns covering content control (Logits Masking, Grammar, Style Transfer), RAG architecture, model capabilities (Chain of Thought, Adapter Tuning), reliability (LLM-as-Judge, Reflection, Prompt Optimization), agentic systems (Tool Calling, Multiagent Collaboration), deployment optimization (SLM, Prompt Caching, Inference Optimization), safety guardrails (Self-Check, Guardrails), RAG implementation (11 source types, chunking, vector stores), and LLMOps/AgentOps (maturity L0–2, Tool/Agent Registry, Memory Governance, LLM metrics, LLMSecOps). Also covers AI performance (GPU/CUDA, LLM inference) via PERF- references. Use when designing GenAI applications, choosing RAG strategies, implementing agent architectures, optimizing LLM reliability, or operating AI systems in production. For web AI (Vercel AI SDK, LangChain.js), use integrating-ai-web-apps. For GCP-specific ML (BigQuery ML, Vertex AI), use developing-google-cloud.