One dev split Claude Code into specialized agents per skill type
A developer shared how they moved away from using a single Claude Code instance for everything, instead routing each type of task to a dedicated agent. Each agent focuses on one skill — like testing, code review, or documentation. The post asks whether others are experimenting with similar setups.
Rather than sending all requests to one AI session, this person built a 'skill routing' layer on top of Claude Code. When a request comes in, the system first identifies what kind of task it is, then hands it off to the agent best suited for that job. For example, a bug fix request goes to a debugging agent, while a docs request goes to a documentation agent.
The benefit is that each agent stays focused and doesn't get its context cluttered with unrelated work, which can improve the quality of responses. For solo developers juggling many types of tasks, this kind of structured setup could reduce errors and make AI assistance more reliable. It's still an experimental, self-built approach, but it shows how power users are pushing Claude Code beyond its default single-session model.
Key points
- Uses multiple focused agents instead of one catch-all Claude Code session
- A routing layer detects the request type and sends it to the right agent
- Each agent handles only one skill area, keeping its context clean
- Particularly useful for solo developers managing many different task types
- The post is a community check-in — the author wants to know if others do this too
Quick term guide
- instance
- One independent run of an AI model, separate from any other run of the same model.
- testing
- The process of checking that software does what it's supposed to do, usually by running it and looking for errors.
- code review
- A check of code before it is shipped, usually to find mistakes or improvements.
- session
- A continuous period of interaction between a user and a computer program.
- skill routing
- A system that reads what kind of task you're asking for and automatically sends it to the agent best suited to handle it.
- context
- The information an AI uses to understand your request, such as files, notes, and past messages.
- responses
- An OpenAI API feature for creating and handling model answers.
- developers
- Developers are people who build software, apps, or websites.