The Agent Moat is Memory: Context Engineering, Agentic Workflows, and the Reliability Divide

Tools

DeepLearning.AI: Building Reliable Agentic Workflows with LangGraph

Andrew Ng's team demonstrates practical patterns for adding guardrails and checkpoints to agent workflows. Shows how to handle failure modes and state persistence, which are now table stakes for production.

Research

Anthropic: Contextual Retrieval for Better Agent Performance

Anthropic shares research on improving agent performance by enriching retrieved context with metadata. A direct response to the 'garbage in, garbage out' problem in RAG-based agents, focusing on input quality.

Analysis

Context Engineering for Agents: A LangChain Deep Dive

LangChain outlines the emerging discipline of 'context engineering' for agents, focusing on how to structure prompts, memory, and tools for optimal performance. A practical guide for builders moving beyond simple chains.