“langgraph”
Multi-Turn Evals: Scoring Long Conversations End-to-End
Learn how to evaluate multi-turn agent conversations with trajectory scoring, context tracking, and end-to-end metrics that go beyond single-turn accuracy.
Routing Tasks Across a Fleet of Worker Agents
Learn how to efficiently route tasks across multiple worker agents using LangGraph, parallel execution patterns, and intelligent load balancing.
Fan-Out/Fan-In: Parallel Execution in Multi-Agent Systems
Master the Fan-Out/Fan-In orchestration pattern in LangGraph to run concurrent worker agents in parallel and aggregate multi-agent insights.
Connecting MCP Tools to LangGraph Agents
Integrate Model Context Protocol (MCP) tool servers dynamically into stateful LangGraph agent workflows using langchain-mcp adapters.
Retry Policies and Fallbacks for Invalid Model Responses
Build resilient LangGraph multi-agent workflows with stateful retries, exponential backoffs, and model fallback chains when LLM outputs fail validation.
Checkpointing LangGraph State: Snapshots, Restores, and Forks
Deep dive into LangGraph checkpointing. Create snapshots of agent state, restore from any point, and fork executions to explore alternative paths.
Queue-Driven Agents: Feeding Workloads from Kafka into a LangGraph Fleet
Build queue-driven agent systems with Kafka and LangGraph. Process agent workloads at scale with guaranteed delivery, ordering, and fault tolerance.
LangGraph for Production: State Machines, Checkpointing, and Subgraphs
Take LangGraph to production with state machines, checkpointing, and subgraphs. Build reliable, observable, and scalable agent workflows.
Approval Gates: Pausing Agent Workflows for Human Sign-Off
Implement approval gates in agent workflows. Pause execution before critical actions, route to human reviewers, and resume with approval or rejection.
The Supervisor Pattern: Coordinating Specialist Agents in LangGraph
Implement the supervisor pattern in LangGraph to coordinate specialist agents. Build a routing system that delegates tasks to expert sub-agents and aggregates results.
Checkpointing Agent State with LangGraph: Threads, Checkpointers, and Resume
Master LangGraph checkpointing to persist agent state, resume interrupted workflows, and build fault-tolerant multi-step agent systems with threads and checkpointers.
Graph-Based Orchestration: Sequential, Parallel, and Handoff Patterns
Master graph-based orchestration patterns for multi-agent systems with LangGraph, including sequential processing, parallel execution, and agent handoff mechanisms.
The Agent SDK Landscape Deep Dive: LangGraph, CrewAI, MAF, ADK
A comprehensive comparison of the leading AI agent frameworks in 2026: LangGraph, CrewAI, Microsoft Agent Framework, and Google ADK, with practical guidance on choosing the right one.
Deep Agents: Long-Horizon Task Execution with Durable Threads
Build agents that run for hours, pause for approval, and survive crashes. Learn durable execution, delta channels, and human-in-the-loop with LangChain Deep Agents.
The Agent SDK Landscape: PydanticAI vs. LangGraph vs. CrewAI
Stop choosing an agent framework at random. Compare PydanticAI, LangGraph, and CrewAI on statefulness, multi-agent design, type safety, and operational control — then pick the right tool per job.
LangGraph: Stateful, Graph-Based Agent Orchestration
LangGraph turns an agent into an explicit graph of nodes with durable state. Learn StateGraph, checkpointers, thread_id, and crash-resilient execution.
Top AI Agent Frameworks for 2026: A Practical Comparison
A practical, evidence-based comparison of the leading AI agent frameworks in 2026 — LangGraph, CrewAI, OpenAI Agents SDK, AutoGen/AG2, Google ADK, and more — with guidance on how to choose.