The Short Answer
Some workflows need more than a single agent handling a single task. They need multiple agents, or multiple steps within an agent, coordinating together: one agent qualifying a lead, another routing it, a third triggering a follow-up sequence. This coordination is orchestration, and getting it right determines whether a multi-step agent workflow is reliable or fragile.
Why This Topic Matters
A single, well-designed agent handling one task is relatively straightforward to build reliably. Orchestrating multiple agents or steps introduces new failure points: a handoff that loses context, a step that fails silently, or a sequence that gets stuck waiting on a condition that never resolves.
Approaching orchestration deliberately, with clear handoff protocols and failure recovery built in, prevents these issues from surfacing only after the workflow is already in production.
Common Mistakes and Risks
- Losing context during handoffs.Passing incomplete information between agents or steps, forcing the next step to work with insufficient context.
- No failure recovery plan.Designing orchestration that assumes every step will succeed, with no defined behavior when one doesn't.
- Overcomplicating simple sequences.Building elaborate orchestration for a workflow that could be handled by a single agent with straightforward logic.
- Ignoring latency accumulation.Chaining multiple steps without considering how their combined latency affects the overall user or customer experience.
- No visibility into the orchestration's current state.Building a multi-step workflow without the ability to see where a specific instance currently stands in the sequence.
BetterBoost Practical Framework
BetterBoost applies its Analyze, Conceptualize, Build, Measure methodology to agent orchestration design.
During Analyze, the full workflow sequence is mapped, including every handoff point and the information that needs to transfer at each one. During Conceptualize, the orchestration logic is designed, including failure recovery behavior and human-in-the-loop checkpoints where needed. Build implements the orchestration with monitoring for each step's status. Measure tracks completion rates, failure recovery effectiveness, and end-to-end latency after deployment.
Step-By-Step Guidance
- Step 1: Map the full workflow sequence.Document every step and handoff point in the orchestration, including which agent or system handles each one.
- Step 2: Define what information transfers at each handoff.Specify exactly what context needs to pass from one step to the next.
- Step 3: Design failure recovery for each step.Determine what happens if a specific step fails, retry, escalate, or fall back to a default path.
- Step 4: Place human-in-the-loop checkpoints.Identify where human review belongs given the consequences of an incorrect outcome at that stage.
- Step 5: Account for latency accumulation.Evaluate whether the combined time across all steps meets your workflow's acceptable response time.
- Step 6: Build monitoring for orchestration state.Ensure you can see where any given instance of the workflow currently stands, not just its final outcome.
Examples and Use Cases
A team building a multi-step lead qualification and routing workflow initially designed each step independently, only to discover during testing that a qualification agent's output format didn't match what the routing step expected, causing silent failures. Explicitly defining the handoff format between steps, as covered in Step 2, resolved the issue before it reached production.
How to Apply This Inside Your Organization
Start by mapping your full workflow sequence using Step 1, paying particular attention to every handoff point. Define exactly what information transfers at each handoff using Step 2, since this is one of the most common sources of orchestration failure.
If your organization wants support designing and implementing multi-step agent orchestration, BetterBoost's AI Agent Development service applies this framework directly.