Tutorials Prompt Engineering Tutorial
Agent Orchestration — Complete Guide
Agent Orchestration — Complete Guide: free step-by-step lesson with examples, common mistakes, and interview tips — part of Prompt Engineering Tutorial on Toolliyo Academy.
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Prompt Engineering Tutorial · Lesson 58 of 100
Agent Orchestration
Prompts ✓ → Apps
Apps · 2 — RAG & agents · ~10 min · Module 6: AI Agents
What is this?
Orchestration coordinates multiple agents, routes events, handles parallelism, and enforces global policies across runs.
Why should you care?
PromptVerse Orchestrator runs map-reduce over ticket batches with per-tenant concurrency caps.
See it live — copy this example
Copy the prompt into ChatGPT, Claude, or your LLM API playground and compare outputs.
orchestrator.run({
pattern: "map_reduce",
map: { agent: "classifier", input: tickets, concurrency: 20 },
reduce: { agent: "summarizer", input: "map_outputs" },
policy: { max_cost_usd: 5.0 }
});What happened?
- Map classifies in parallel with cap 20.
- Reduce summarizes batch.
- policy.max_cost_usd aborts run if spend spikes.
Practice next
- Sketch map step on 5 items.
- Add reduce aggregation prompt.
- Set concurrency 2 for test.
- DAG instead of linear map-reduce.
- Schedule orchestration on cron.
Remember
Orchestrator owns concurrency and cost. Map-reduce for batch AI. Policies apply globally.
Nightly ticket batch
10k tickets classify by morning.
Outcome: Orchestrator finishes under $5 cap with 20-wide map.
Interview prep for this lesson
Practice these questions aloud after reading—each links to a full structured answer.
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