#LLM

Large Language Models (LLMs) power the reasoning layer in these multi-agent systems. Posts cover LLM reliability engineering, token budget management, provider abstraction patterns, and the operational challenges of running LLM-backed services in production with predictable cost and latency.

1 post tagged with llm. ← All posts

A2A (5)ADK (8)AG-UI (7)AI Agents (232)AI Governance (5)Agent Skills (3)Agentic AI (13)Agents (4)Architecture (15)Azure (9)Azure AI Foundry (10)BigQuery (6)Checkpointing (5)Compliance (8)Concurrency (4)Context Providers (3)Conversation State (3)Cost Optimisation (3)Distributed Systems (3)Evaluation (4)FREE-AI (8)FinOps (5)FinTech (6)Function Tools (6)GCP (5)Go (168)Google ADK (26)Governance (5)Guardrails (3)HIPAA (3)Harness Engineering (8)Human-in-the-Loop (7)KYC (3)Kubernetes (6)LLM (1)LangGraph (11)Microsoft Agent Framework (21)MCP (5)Memory (5)Microsoft Agent Framework (188)Middleware (9)Multi-Agent (8)Multi-Agent AI (13)Multimodal (4)Observability (12)Open Source (6)OpenTelemetry (5)Opinion (6)Orchestration (15)Payments (4)Privacy Engineering (3)Providers (3)Python (126)RAG (6)RBI (3)Retrieval (3)SRE (3)Security (9)Sessions (4)Spanner (4)Streaming (4)Structured Output (4)Workflows (14)

All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.