Stop copy-pasting prompts one at a time. chAIrman lets you hire, assign, and orchestrate autonomous Claude Code agents that work in parallel — with dependency chains, shared memory, and a live dashboard.
AI agent orchestration is the practice of coordinating multiple autonomous AI agents to accomplish complex, multi-step tasks. Instead of feeding prompts to a single model one at a time, an orchestration platform distributes work across specialized agents, manages their dependencies, and assembles the results.
Think of it like hiring a team. A single developer can only write one file at a time. But a team of five, each owning different parts of the codebase, can ship a feature in a fraction of the time — as long as someone coordinates them. That coordinator is the orchestration layer.
Without orchestration, scaling AI-assisted development hits a wall fast. Manual prompting is sequential. You wait for one response, interpret the output, craft the next prompt, and repeat. For a 10-step task, that is 10 rounds of back-and-forth. Agent orchestration collapses those 10 steps into parallel streams of autonomous work, with the platform handling handoffs, retries, and state.
chAIrman gives you a simple three-step orchestration model that maps to how real teams operate.
Create specialized agents with focused roles and job descriptions. Each agent is a full Claude Code process with its own context, memory, and file access. Hire a frontend lead, a QA engineer, a database specialist — whatever your project needs. Use templates for common roles or write custom job descriptions. Agents inherit project context files (like CLAUDE.md) and relevant skills automatically.
Give each agent a single, well-defined task through the backlog and ticket system. Every ticket includes a description, the files it should touch, files that are off-limits, and clear success criteria. The orchestrator enforces that no two agents edit the same file simultaneously, preventing merge conflicts and clobbered work. Tasks queue automatically if an agent is already busy.
Connect tasks with dependency chains using the depends_on parameter. When you tell a QA agent to wait for the backend agent, the orchestrator holds the QA task in a waiting state and auto-launches it the moment the backend finishes. Cycle detection prevents deadlocks. The critical path is calculated so you know the minimum time to completion. Pipelines can span dozens of agents across multiple milestones.
Most tools give you a chatbot. chAIrman gives you a workforce.
| Capability | Manual Prompting | Wrapper Tools | chAIrman |
|---|---|---|---|
| Parallel execution | No — one prompt at a time | Limited — some support batching | Unlimited parallel agents with dependency chains |
| Agent memory | Copy-paste context manually | Basic session history | Structured handoffs, alumni archive, shared message board |
| Pipeline dependencies | You manage order manually | Not supported | Automatic dependency resolution with cycle detection |
| Cost tracking | Check your API dashboard | Aggregate only | Per-agent, per-task, per-project with budget enforcement |
| Failure recovery | Start over | Manual retry | Auto-retry up to N times with handoff inheritance |
| Real-time monitoring | Stare at the terminal | Logs after completion | Live dashboard with WebSocket updates and terminal streaming |
Agent orchestration is not limited to code generation. Any multi-step workflow that benefits from parallelism and specialization becomes faster and more reliable with an orchestration layer. Here are the patterns developers use most with chAIrman.
An agent in chAIrman is a full Claude Code process running autonomously in your project directory. Each agent has its own role, job description, memory (handoff documents), file access, and task queue. Agents are spawned as child processes with structured output parsing, cost tracking, and automatic git commits. They are not simple API calls — they are persistent workers that use tools, read and write files, run commands, and produce structured results.
Running multiple Claude Code sessions manually means you are the orchestrator. You manage context, dependencies, file conflicts, retries, and progress tracking in your head. chAIrman automates all of that. It enforces file ownership so agents don't clobber each other's work. It manages dependency chains so tasks execute in the right order. It tracks costs per agent, auto-retries failures, saves handoff documents for continuity, and provides a real-time dashboard. It is the difference between managing a team on sticky notes versus using a project management tool.
Agents communicate through a shared message board. They can broadcast messages to the entire team or send direct messages to specific agents using output tags. Messages are injected into an agent's prompt when a new task is assigned. Agents also share context through structured handoff documents, which are saved every 60 seconds and passed to replacement agents or successors. The CEO (you, in Claude Desktop) reads the message board and coordinates high-level decisions.
chAIrman has a multi-layered failure recovery system. First, it auto-detects eight common error patterns (auth failure, rate limit, context exceeded, etc.) and provides actionable diagnostics. Second, failed agents are automatically retried up to a configurable number of times (default: 3). The replacement agent inherits the original's handoff notes, so it does not start from scratch. Third, idle agents are flagged with warnings after 10 minutes and zombie-detected after 30 minutes. Fourth, the health monitoring system tracks error rates per project and raises warnings when failure rates exceed 50%.
Yes. chAIrman tracks costs at three levels: per-task, per-agent, and per-project. You set a budget on any project, and the orchestrator will refuse to spawn new tasks if the budget is exceeded. The scheduler module recommends cheaper models (Sonnet) for routine tasks and reserves expensive models (Opus) for complex work like architecture decisions. Desktop notifications fire at 80% budget utilization. The metrics system shows cost trends over time so you can spot runaway spending before it becomes a problem.
LangChain and CrewAI are Python frameworks for building agent applications. They require you to write code to define agents, tools, and workflows. chAIrman is not a framework — it is a turnkey orchestration platform that runs as an MCP server inside Claude Desktop. You do not write agent code. You describe roles and tasks in natural language, and chAIrman spawns real Claude Code processes that read files, write code, run tests, and commit to git. It is closer to a project manager than a library. The agents themselves use the full Claude Code toolset, not a limited set of predefined tools.
Join developers who ship faster with chAIrman. From $19.99/mo.