It is now clear that AI agents have started to change development work in very concrete ways. They speed up codebase exploration, make writing, review, testing, and documentation easier, and shift part of the work toward steering and arbitration.
The new trend, multi-agent orchestration, can be summed up like this: instead of making a single agent, or a few manually piloted agents, handle everything, you distribute work across several specialized agents coordinated with one another. Very quickly, the idea is no longer to have “a better copilot,” but rather a coordinated team: a security agent, an architecture agent, a testing agent, a documentation agent, each brought in at the right time.
The goal is no longer simply to use Claude Code as a conversational assistant, but to build a small working system where several agents cooperate, split tasks, hand work off to one another, and sometimes move in parallel.
To understand what this looks like in practice, it is worth looking at three projects that embody three fairly different visions of orchestration: wshobson/agents, Oh My Claude Code (OMC), and Gas Town.
Why multi-agent orchestration is becoming a real topic
Claude Code already makes it possible to run several sessions around task lists, Git branches, and shared files. As long as you are piloting a few agents by hand, that remains manageable.
But as soon as needs diversify — code, security, infrastructure, data, documentation, product — the real questions begin:
- Which agent should do what?
- How do you avoid collisions in the codebase?
- Where do you keep state, decisions, and instructions without having to reload all context at every interaction?
- How do you parallelize without losing coherence?
- How do you keep a trace of what has been done?
This is where multi-agent orchestration architectures come in. They add an organizational layer on top of Claude Code: roles, workflows, communication conventions, and sometimes external artifacts such as Git, config files, issues, or databases to structure collaboration.
In other words, you move from an intelligent assistant to a coordinated work system.
wshobson/agents: a toolbox of specialized agents
The first approach looks like a well-equipped workshop.
With wshobson/agents, the idea is not to impose a single orchestration model, but to provide an ecosystem of plugins, skills, and specialized agents that can be attached to Claude Code as needed.
You will find agents focused on security, SQL, testing, performance, documentation, full-stack work, infrastructure, ML, or even business. Rather than a large monolithic framework, the project relies on composability: you pick the bricks you need and assemble your own environment.
That is exactly where its strength lies.
You do not install “multi-agent orchestration” as an opaque block. You progressively compose a workflow adapted to your stack. For example, an orchestrator can launch a code review by bringing in:
- a security agent,
- a performance agent,
- an architecture agent,
- and then a documentation agent.
Each agent works on a clearly bounded aspect of the problem, instead of forcing everything through a single generalist session.
This approach will immediately resonate with teams that like building their development environment à la carte, just as they would with dotfiles, internal scripts, or homegrown pipelines. wshobson/agents is above all a logic of modularity and control.
Oh My Claude Code: orchestration designed for DX
Oh My Claude Code (OMC) starts from a different observation: multi-agent orchestration is powerful, but it can quickly become painful to configure and operate on a daily basis.
Where wshobson/agents feels like a toolbox, OMC positions itself more as an automation layer oriented toward developer experience. The ambition is not only to add agents, but to make them easy, fast, and pleasant to use.
Concretely, OMC emphasizes:
- guided configuration,
- project profiles,
- multiple execution modes,
- real-time monitoring,
- and integrations with team communication tools.
The key idea is to reduce the cognitive cost of orchestration.
You state an objective, launch a run, and OMC takes care of part of the mechanics: which agents to call, how to split the work, what can be parallelized, and how to report progress back to channels the team already uses — for example Discord or Telegram.
Another interesting point is the care given to onboarding. OMC does not just run agents: it helps generate or update project configuration files, define execution modes such as sequential, parallel, or swarm, and install a kind of HUD or status tracking layer.
The result is that you can move fairly quickly from “I use Claude Code alone” to “I am piloting a small team of agents” without having to understand all the internal plumbing right away.
For teams that want to benefit from multi-agent workflows without turning their dev environment into an architecture project, OMC offers a particularly pragmatic approach.
Gas Town: an industrial vision of orchestration
With Gas Town, the scale changes again.
Here the goal is no longer just to distribute a few tasks across specialized agents, but to design a real multi-agent production environment around Claude Code.
The project introduces a more ambitious structure, with concepts such as:
- the Town, which centralizes global configuration;
- rigs, which correspond to repositories or projects;
- fleets of agents able to work in parallel on branches, tasks, or code patrols.
This time, agents are not defined only as personas or specialized assistants, but as actual operational roles in an organization:
- a Mayor to coordinate, break down, and supervise work;
- Polecats to execute bounded tasks quickly;
- and other roles for auditing, monitoring, or system maintenance.
The major difference is that the state of the system is not carried only by conversational context. It also lives in external artifacts: Git, issues, beads, and tracking elements. That persistence enables parallelization, human supervision, and traceability.
Gas Town pushes the idea further: agents do not simply assist a developer; they become part of an organized production chain with conventions, responsibilities, controls, and proof of work.
This is a very infrastructure-minded, almost ops-like view of multi-agent systems. You are no longer adding a few assistants to an existing flow; you are building an agent factory.
Three complementary visions of orchestration
If you put implementation details aside, these three projects actually sketch out three ways of thinking about orchestration around Claude Code.
- The modular logic: with wshobson/agents, you assemble your own ecosystem of agents and orchestrators. This is the path of control, customization, and composability.
- The experience-oriented logic: with OMC, orchestration becomes a service that absorbs part of the technical complexity. This is the path of ease of use, rapid adoption, and operational comfort.
- The infrastructure logic: with Gas Town, agents become a structuring layer of the development process itself. This is the path of persistence, traceability, massive parallelism, and industrialization.
These approaches do not exclude one another. On the contrary, they can complement each other.
For example, you could combine:
- the composability of wshobson/agents,
- the DX choices of OMC,
- and the persistence and role concepts of Gas Town,
to design an orchestration model adapted to your own stack, monorepo, or team constraints.
How to transpose these ideas into your own stack
The real question is not only “which tool should I choose?” but where to begin.
A realistic path might look like this:
Start simple. Build an initial toolbox of specialized agents in Claude Code to cover the most recurring needs: code review, security, testing, and documentation.
Add a light orchestration layer. Then introduce an OMC-like logic to parallelize some tasks, standardize a few execution modes, and share progress more clearly with the team.
Test a more structured model. Finally, on a pilot project, experiment with something closer to Gas Town: role-based agents, dedicated branches, tracking artifacts, human supervision, and a more industrialized workflow.
The right level of orchestration will always depend on your context: team size, code criticality, frequency of refactors, traceability needs, and infrastructure maturity.
But one thing is becoming clear: as these practices stabilize, multi-agent orchestration stops being an impressive gimmick and becomes a new way to organize development work around Claude Code.
What to remember
The point of multi-agent systems is not to add “more AI” for its own sake. It is to distribute work better, preserve context, parallelize what can be parallelized, and make contributions easier to read, more specialized, and more traceable.
- wshobson/agents shows the value of a modular approach.
- OMC shows how to make orchestration accessible and comfortable.
- Gas Town shows how far an industrialized approach can go.
Between those three visions, there is already plenty to think seriously about when it comes to evolving your own environment around Claude Code.