Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
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Build intelligent decision points in LangGraph using conditional edges, router functions, and multi-path branching to create agents that dynamically choose their execution path.
Learn how to integrate LLM function calling into LangGraph workflows using ToolNode, tool binding, automatic tool execution, and structured error handling for reliable agent behavior.
Implement human approval gates in LangGraph using interrupt_before, interrupt_after, and resume patterns to build agent workflows that pause for human review before executing sensitive actions.
Implement persistence and time travel in LangGraph using MemorySaver, SqliteSaver, and PostgresSaver to checkpoint agent state, replay past executions, and recover from failures.
Build multi-agent systems in LangGraph using subgraph composition, supervisor routing, and parallel worker execution to create specialized agent teams that collaborate on complex tasks.
Implement real-time streaming in LangGraph with stream modes for node-level updates, token-by-token LLM output, custom event streams, and practical patterns for responsive agent UIs.
Build resilient LangGraph workflows with try/except patterns in nodes, fallback conditional edges, configurable retry logic, and dead-end recovery strategies for production agent systems.
Deploy LangGraph agents to production using LangGraph Cloud with API endpoints, cron triggers, monitoring, scaling strategies, and operational best practices for stateful agent workflows.
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