Orchestrating Multi-Step Workflows
You'll learn to
- -Understand orchestration patterns for multi-step agent workflows
- -Recognize when to hand off between specialized agents
- -See how every concept in this tier composes into one platform
A company hosting two hundred different agents across fifty enterprise clients cannot run each one as its own bespoke, hand-wired system. Each agent needs its own tools, its own memory, its own model configuration, and every client needs strict isolation from every other client's agents. This closing chapter is where every piece from this entire tier, tools, ReAct, planning, memory, multi-agent collaboration, sandboxing, approval gates, error handling, and evaluation, composes into one coherent platform.
Four Layers
An agent orchestration platform, request to response.
- -Gateway: authenticates the request, rate-limits it per tenant, and routes it to the right agent, the same gateway concerns Tier 10 covers in full depth for LLM traffic generally.
- -Execution: the agent loop itself, tool registry, and whichever LLM that specific agent is configured to use.
- -State: each agent's working and long-term memory, isolated per tenant so one client's agent state is never visible to another's.
- -Observability: full tracing, metrics, and cost tracking across every agent, which is exactly what makes fifty clients' worth of agents auditable and debuggable from one place.
Multi-Tenant Isolation Is Not Optional
Each client's agents run in a genuinely separate context: scoped tool access, isolated memory, and per-tenant rate limits and cost tracking for billing. A bug or a runaway loop in one client's agent must never be able to affect another client's agent, consume their rate limit budget, or leak their memory. This is the same tenant-isolation instinct that shows up anywhere a platform serves multiple independent customers on shared infrastructure.
Design this the way a container orchestration platform works: declarative per-agent configuration, health checks, resource limits, and the ability to roll out an update to one agent without touching the other one hundred ninety-nine. The platform manages lifecycle and isolation. Each individual agent just focuses on its own task, using every pattern this tier has built up: tools, ReAct, planning, memory, collaboration, sandboxing, approval gates, and error handling.
Everything in This Tier, Composed
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Build the Error Handler, Agent Evaluator, and Orchestrator levels in the GenAI Lab.