The article discusses how modern architectures create precise, cost‑efficient context for enterprise AI agents, moving beyond Retrieval‑Augmented Generation (RAG). It presents six advanced architectural patterns that serve as a practical guide for practitioners. The focus is on engineering context layers that improve the performance and efficiency of AI systems in enterprise settings.
By Partha Sarkar
The article "Agentic Systems: A Practitioner's Guide to 6 Advanced Architectural Patterns" discusses six production-oriented architectures designed to build autonomous, reliable, and scalable large language model (LLM) agents, moving beyond basic ReAct loops. It provides a practitioner-focused guide to implementing these advanced patterns in real-world systems.
By Partha Sarkar
A practical enterprise AI architecture with data agents, AI-powered QA, and AI governance. The post Many Companies Use AI.
By Jiayan Yin
Beyond basic graph retrieval: six production-oriented architectures for combining semantic search, knowledge graphs, and LLM reasoning.
The post GraphRAG: A Practitioner's Guide to 6 Advanced Architec...
By Partha Sarkar
The article "How to Design Architectural Guardrails Around AI Agents" discusses essential agent design patterns that data engineers should understand. It emphasizes the importance of establishing clear architectural boundaries to ensure AI agents operate safely and effectively within larger systems. The post was originally published on Towards Data Science.
By Thuwarakesh Murallie
Giving an AI agent access to a data warehouse doesn't automatically make it agent-ready. The real challenge lies in teaching the agent what the data means and when it's reliable enough to use.
By Shafeeq Ur Rahaman