3:18
LLMOps → Agentic AIOps: Start Here (Playlist Intro)
AI WITH Rithesh
5:58
Prompt Management as Code: Versioning, Injection & DSPy
5:41
How to Evaluate LLM Apps: LLM-as-a-Judge & RAGAS (Without the Bias)
LLM Observability: Traces, Spans & OpenTelemetry for AI Apps
6:01
Production RAG (RAGOps): Hybrid Search, Rerankers & HNSW
5:56
LLM Guardrails: Stop Injection, Leaks & Hallucination (NeMo Guardrails)
5:55
Cut LLM Cost & Latency: KV Cache, Batching, Quantization, vLLM
6:14
How AI Agents Actually Work: ReAct, Tools & Reflexion
6:07
Multi-Agent Systems with LangGraph: The Klarna & Uber Lessons
Agent Memory Explained: MemGPT, Mem0 & Zep (Beyond the Context Window)
6:09
MCP vs A2A: How AI Agents Connect — and How to Govern Them
