Do your agentic workflows reliably coordinate tools, agents, and humans without breaking under real-world complexity?
Agentic routing is becoming the backbone of GenAI automation, but without clear patterns for state, memory, and escalation, even promising prototypes stay brittle and hard to scale.
To win, your GenAI solutions need to run on observable, well-governed agentic routing that keeps state, memory, and escalation under control.
The Challenge
Without a strong approach to agentic routing, teams struggle to:
- Unstructured agent designs — Jump into agents without a clear mental model for routing, state, and escalation across workflows.
- Unmanaged state and memory — Rely on fragmented state and opaque memory handling that make behavior hard to explain or debug.
- Ad hoc escalation — Patch in human overrides late, leading to inconsistent handoffs, governance gaps, and fragile runbooks.
Agentic routing gaps will drive reliability issues, governance risk, and frustrating, hallucination-prone user experiences.
Our Solution
In this hands-on workshop, your team designs, implements, and validates LangGraph-powered agent workflows using curated notebooks, graphs, and sample scenarios. Areas of focus include:
- Building LangGraph Agents — Design agents and graphs that coordinate tools, services, and humans across multi-step workflows.
- State & Memory Management — Manage state and memory across agent steps so workflows stay consistent, explainable, and recoverable.
- Escalation & Human Involvement — Design human-in-the-loop patterns that bring people in at the right time with the right context.
- Interactive Labs & Graph Visualizations — Explore agent behavior live in notebooks and graph views to understand routing choices.
- Capstone & Live Coaching — Assemble an end-to-end agentic routing flow and refine it with expert feedback and guardrails.
Areas of Focus
Not in template
Skills You'll Gain
- Reliable Agentic Workflows — Design multi-agent flows that are predictable, debuggable, and resilient to failure.
- Operationally Aware Designs — Treat state, memory, and escalation as first-class design concerns instead of afterthoughts.
- Production-Ready Patterns — Apply repeatable blueprints, guardrails, and governance models for deployable agent systems.
- Better Human–Agent Collaboration — Coordinate agents with humans and existing systems through clear, auditable handoffs.
- Faster Path to Scale — Reuse templates and routing patterns to extend agentic workflows across new use cases and domains.
Who Should Attend:
Solution Essentials
Format
Virtual or in-person
Duration
8 Hours
Skill Level
Intermediate Python and basic GenAI familiarity recommended
Tools
LangGraph, Jupyter notebooks, and preconfigured agent components
Explore the Remaining GenAI Routing Certification Workshops
Help your teams build high-quality, extensible GenAI Solutions. Click below to explore the remaining workshops in the GenAI Routing certification series—and build the applied expertise your teams need to master GenAI Routing.
Logical Routing
Semantic Routing
Evaluating Routing Solutions
Routing Controls & Security