Agent Team Composition: 5 Patterns That Actually Work

March 2026 • 11 min read

Not every task needs five agents. Not every task needs one. The art of multi-agent development is matching the right team structure to the right problem. After working with dozens of agent team configurations across production codebases, five patterns have emerged as consistently effective. Each one solves a different class of problem with a different trade-off between speed, quality, and cost.

Here are the five patterns, when to use each, and how to set them up.

Pattern 1: Pair Programming

The simplest multi-agent pattern. Two agents: one codes, one reviews. The coder generates the implementation, and the reviewer analyzes it for bugs, edge cases, and adherence to project standards. The reviewer's feedback goes back to the coder for iteration.

Team size: 2 agents. Models: Both Sonnet 4.6. Best for: Bug fixes, quality-sensitive changes, and any task where a second pair of eyes catches issues the first agent misses.

This pattern catches 30-40% more bugs than a single agent. The reviewer sees the code with fresh context, without the biases that come from having written it. Set up the reviewer in a separate Beam tab with instructions to act as a senior code reviewer who focuses on correctness, edge cases, and maintainability.

Pattern 2: Specialist Trio

Three agents, each owning a layer of the stack: frontend, backend, and testing. Each works in its own git worktree, building its portion of the feature simultaneously. The testing agent writes tests based on interface definitions before the other two finish implementing.

Team size: 3 agents. Models: All Sonnet 4.6. Best for: Full-stack features with clear separation between frontend and backend. A new dashboard page with an API endpoint and corresponding tests is the canonical use case.

The Specialist Trio is the most cost-effective multi-agent pattern. Three Sonnet agents cost less than a single Opus agent while producing more total output. The parallelism typically cuts implementation time by 40-50% compared to a single agent working sequentially.

Pattern 3: Full Squad

The full development team: an architect, two or three implementers, and a QA agent. The architect (Opus 4.6) plans the work breakdown, defines interfaces, and reviews the final integration. Implementers (Sonnet 4.6) build their assigned components. The QA agent (Sonnet or Haiku) writes and runs tests continuously.

Team size: 4-5 agents. Models: Opus for architect, Sonnet for implementers, Haiku for simple QA. Best for: Large features, new microservices, or major refactoring efforts that span many files and components.

Pattern 4: Research and Execute

A two-phase pattern where an explorer agent investigates the problem space before a builder agent implements the solution. The explorer reads documentation, analyzes existing code, evaluates libraries, and produces a research brief. The builder takes that brief and implements the solution.

Team size: 2 agents (sequential, not parallel). Models: Opus for explorer, Sonnet for builder. Best for: Unfamiliar domains, library evaluations, migration planning, and any task where you need to understand the landscape before committing to an approach.

The Research and Execute pattern prevents the common failure mode where an agent starts building immediately and picks the wrong approach. By separating research from execution, you ensure the builder starts with the right context and the right plan. The explorer can evaluate multiple options, identify trade-offs, and recommend the best path forward.

Pattern 5: Red Team / Blue Team

An adversarial pattern borrowed from security. The Blue Team (builder agent) writes code. The Red Team (auditor agent) tries to break it. The Red Team looks for security vulnerabilities, injection points, authentication bypasses, and data leakage. Every issue the Red Team finds goes back to the Blue Team for fixing.

Team size: 2 agents (iterative loop). Models: Sonnet for Blue Team, Opus for Red Team. Best for: Authentication systems, payment processing, API security, data handling, and any code that handles sensitive information.

The Red Team should run Opus because security analysis requires deep reasoning about edge cases, attack vectors, and subtle logic flaws. Sonnet can miss nuanced security issues that Opus catches. One round of Red Team review typically surfaces 3-5 security improvements that a single agent would miss entirely.

Choosing the Right Pattern

Match the pattern to the task, not the other way around. A simple bug fix does not need a Full Squad. A security-critical authentication rewrite does not need a simple Pair.

• Default to Pair Programming for any task where quality matters more than speed. It is the lowest overhead multi-agent pattern and catches the most bugs per dollar spent.
• Scale to Specialist Trio when you have a full-stack feature with clean layer boundaries. If the frontend and backend can be built independently, parallelize them.
• Use Full Squad only for genuinely large efforts -- new services, major migrations, or features that touch 20+ files. The coordination overhead is not worth it for smaller tasks.
• Deploy Research and Execute when you are working in unfamiliar territory. The upfront research investment prevents costly rework.
• Activate Red/Blue for anything security-sensitive. The cost of Opus for the Red Team is trivial compared to the cost of a security breach.

Running Patterns in Beam

Each pattern maps naturally to Beam's workspace model. Create one workspace per active pattern, with each agent in its own tab. For the Pair Programming pattern, two tabs suffice. For the Full Squad, you need four or five tabs with clear labels.

Use ⌘N to create the workspace, ⌘T for each agent tab, and ⌘1-5 to switch between them. Save your workspace layout with ⌘S so you can quickly spin up the same pattern for future tasks.