Multi-agent systems outperform single agents for complex tasks that require diverse expertise. But how agents coordinate matters just as much as how many you deploy. The wrong coordination pattern produces chaos; the right one produces results that feel like magic.
Build Agents Store supports six coordination patterns. Each one solves a different kind of problem. Here's when and why to use each.
What it is: Multiple agents work on different subtasks simultaneously. Results are combined at the end.
Best for: Problems that decompose into independent pieces. When subtasks don't depend on each other and speed matters.
Example: Competitive analysis. One agent researches pricing, another analyzes features, a third studies customer reviews, and a fourth maps market positioning. All work at the same time, then results merge into a comprehensive report.
When to avoid: When subtasks are tightly coupled and one agent's output depends on another's.
What it is: Agents process work in a defined order. Each agent builds on the previous agent's output.
Best for: Problems with natural phases where each step needs the previous step's results. Think assembly line.
Example: Content creation pipeline. A Research Agent gathers data, then a Writer Agent drafts copy using that research, then an Editor Agent refines the draft, then a Publisher Agent formats and prepares for distribution.
When to avoid: When subtasks are independent and could run simultaneously — a pipeline adds unnecessary waiting time.
What it is: Work starts with a single agent, splits into parallel branches for specialized processing, then merges back for a unified result.
Best for: Problems that start unified, need parallel deep-dives, then require synthesis. Combines the focus of pipelines with the speed of parallel work.
Example: Market expansion analysis. A Strategy Agent defines the evaluation framework, then forks to Regional Analysts who each assess a different market (EU, APAC, LATAM) in parallel, then joins back to a Synthesis Agent who compares regions and makes a recommendation.
When to avoid: When there's no natural "split and merge" structure to the problem.
What it is: Agents discuss approaches, challenge each other's assumptions, and reach a well-reasoned consensus through structured debate.
Best for: Problems where you need multiple perspectives to avoid blind spots. Decisions with significant consequences where groupthink is dangerous.
Example: Investment analysis. A Bull Agent argues for the opportunity, a Bear Agent argues against, a Risk Agent identifies uncertainties, and a Moderator Agent synthesizes the debate into a balanced recommendation with explicit tradeoffs.
When to avoid: When there's a clear right answer and debate would just waste time. Factual tasks don't benefit from debate.
What it is: A lead agent delegates tasks to specialist agents and synthesizes their findings. The lead agent decides what to investigate and when to go deeper.
Best for: Exploratory problems where you don't know what you'll find. The lead agent adapts the investigation based on early results.
Example: Due diligence investigation. A Lead Analyst identifies areas of concern, dispatches specialists (Financial Scout, Legal Scout, Technical Scout, Market Scout) to investigate specific questions, reviews their findings, asks follow-up questions, and produces a final assessment.
When to avoid: When the problem structure is well-defined upfront — Subagent Scout adds overhead for problems that are already decomposed.
What it is: Combines multiple coordination patterns for complex, multi-phase challenges. Different phases use different patterns.
Best for: Large, complex problems that have distinct phases with different coordination needs.
Example: Product launch. Phase 1 uses Parallel Workers for market research, competitive analysis, and audience segmentation simultaneously. Phase 2 uses a Sequential Pipeline for strategy development, messaging, then channel planning. Phase 3 uses Advisory Debate to stress-test the launch plan before execution.
When to avoid: When the problem is simple enough for a single pattern. Don't add complexity where it's not needed.
Ask yourself these questions:
Or skip the analysis entirely — describe your business problem on Build Agents Store and let AI pick the best pattern for you. You'll get three different team designs using three different patterns, so you can compare approaches and choose the one that fits.
Regardless of pattern, effective agent teams share these traits:
Build Agents Store generates all of this automatically. Describe your challenge, pick a team, and get a copy-paste-ready prompt with roles, deliverables, handoffs, and synthesis built in.
Ready to build your first agent team? Try Build Agents Store — your first generation is free.