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Multi-agent workflows • Parallel engineering

Engineering Agent Teams: Architecting Claude Code Agent Teams for Parallel Engineering

A practical masterclass on configuring, managing, and deploying multi-agent workflows to solve complex coding challenges at scale—faster, with better coverage, and less tunnel vision.

Who it’s for

Senior engineers, tech leads, architects, and AI-enabled development teams who want repeatable patterns for parallelizing implementation, review, debugging, and research with Claude Code agent teams.

Outcomes
  • Understand agent team architecture (Lead, teammates, mailbox) and how peer collaboration differs from hierarchical sub-agents.
  • Apply four core benefits in real projects: parallelization, overcoming tunnel vision, competing hypotheses, and context preservation.
  • Enable and configure agent teams (environment variable + settings) and choose display modes (in-process vs split panes).
  • Orchestrate teams effectively using role definition, direct/broadcast messaging, plan approval, and delegate mode for clean separation of concerns.
  • Control cost and reliability with model selection, task sizing, file ownership strategies, and troubleshooting playbooks.
Price / Format
Format
Live (Masterclass)
Price
FREE
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20 Jan 2026

Engineering Agent Teams: Architecting Claude Code Agent Teams for Parallel Engineering - Pacific Time - March 31, 2026

Author: Rod Claar CST  /  Categories: Agent Teams, AI Skills  / 

Event date: 3/31/2026 4:00 PM - 7:00 PM Export event

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Engineering Agent Teams March 31, 2026

Architecting Claude Code Agent Teams for Parallel Engineering — live, hands-on session March 31, 2026.

March 31, 2026 | 2:00 PM – 5:00 PM PST

Course Overview

Engineering Agent Teams is a practical, architecture-focused workshop on designing and orchestrating Claude Code agent teams to enable parallel engineering workflows. Learn how to structure specialized agents, coordinate task execution, and integrate human oversight for scalable AI-assisted development.

This session emphasizes system design patterns, role-based agent decomposition, workflow orchestration, and production considerations for high-leverage engineering teams.

Key Learning Objectives

  • ✅ Design role-based Claude Code agent architectures for parallel development
  • ✅ Decompose complex engineering work into coordinated agent workflows
  • ✅ Implement orchestration strategies for task routing and delegation
  • ✅ Integrate human-in-the-loop controls for quality and governance
  • ✅ Apply production-ready patterns for scaling AI-assisted engineering teams
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What You’ll Learn

Time: 2 Hours

A structured walk-through of agent teams in Claude Code—from concepts to configuration, orchestration patterns, real-world workflows, and cost/troubleshooting practices.

What Are Agent Teams?

Core concepts, architecture, and communication flows.
  • Team Lead, Teammates, and the mailbox system
  • Horizontal collaboration vs. hierarchical sub-agents
  • How task assignment, collaboration, and synthesis work end-to-end

Configuration & Setup

Enable agent teams and choose in-process vs split-pane modes.
  • Prereqs: version, subscription, terminal access
  • Enable via CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS
  • tmux/iTerm2 split panes vs in-process navigation

Managing the Team

Orchestration controls, role design, and safe coordination.
  • User-controlled spawning + inherited permissions
  • Delegate Mode and Plan Approval
  • Direct vs broadcast messaging; navigation & context management

Real-World Workflow Patterns

Debugging, code review, and feature construction with teams.
  • Scientific Debate: adversarial hypothesis testing
  • Parallel Code Review: security/performance/tests specialists
  • Tower Construction: dependencies → parallel build → integration

Best Practices, Costs & Troubleshooting

Token management, task sizing, file ownership, and fixes.
  • Model selection strategy (Haiku/Sonnet/Opus) mapped to task complexity
  • Prevent lead impatience; enforce “wait for teammates” sequencing
  • Avoid file conflicts via exclusive ownership + bounded tasks

Q&A and Final Demo

Live demonstration + interactive questions.
  • Hands-on demo of a multi-agent research workflow
  • How prompts decompose into roles and tasks
  • What “good orchestration” looks like in practice

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