On this page
- The Problem With Single-Agent Thinking
- How I Structure the Workflow
- One Agent, One Job
- Context Is a Resource — Spend It Carefully
- The Orchestration Layer
- The Real Claude Code Workflow, Step by Step
- 1. Define the Work Unit
- 2. Load the Right Context
- 3. Run the Session
- 4. Review at the Boundary
- 5. Log and Move
- Where It Breaks
- What This Actually Produces
- The Bigger Picture
My Claude Code Workflow for Running Multiple Agents
Most people use Claude Code the way they used Stack Overflow — paste the problem, wait for the answer, move on. That's fine. It's also leaving most of the leverage on the table.
What I run is different. Seven products, one operator, a system where AI handles research, content, monitoring, deployment scaffolding, and large chunks of code. The claude code workflow I've landed on after a lot of trial and failure isn't glamorous. It's structured, it's opinionated, and it's the thing that actually ships.
Here's how it works.
The Problem With Single-Agent Thinking
When you treat Claude Code as a single assistant — one conversation, one task, one back-and-forth — you're using it like a smarter autocomplete. Useful, but bounded.
The bottleneck isn't Claude's capability. It's the architecture you've built around it. Single-agent thinking means:
- Context windows that bloat and drift
- One failure cascades into the whole session
- You're the bottleneck between every task
- Work can't happen in parallel
The shift that changed how my studio operates was treating agents as workers in a system, not assistants in a conversation. That reframe changes everything about how you structure prompts, sessions, and outputs.
How I Structure the Workflow
One Agent, One Job
Every agent in my system has a defined scope. Not "help me build this feature" — something tighter: generate the data access layer, write the test suite for this module, produce a first draft of the API documentation. The job is specific enough that the agent can succeed or fail clearly, and I can see which without reading five hundred lines of output.
When a task bleeds into adjacent concerns, I split it. Two smaller agents with clear handoffs beat one large agent trying to hold the whole context.
Context Is a Resource — Spend It Carefully
Context windows fill. When they do, quality degrades. This isn't speculation; I've watched it happen enough times to build around it.
My approach: each agent session starts with a tight system prompt that defines the role, the constraint, and the output format. The system prompt doesn't change mid-session. If the work requires a different frame, I open a new session.
For longer tasks — anything that might run across multiple sessions — I use handoff documents. A structured markdown file that captures: what was done, what decisions were made, what assumptions are active, and where the next agent should start. Claude Code can produce these on request. I've standardized the template so any agent in the system can read in a handoff and resume without re-deriving context.
The Orchestration Layer
I built a lightweight orchestration system I call VERA. It's not magic — it's a task queue, a session manager, and a logging layer with some custom tooling on top. The point isn't automation for its own sake. The point is removing me as the bottleneck between sequential tasks.
VERA handles: kicking off agent sessions with the right context, routing outputs to the right place, flagging failures for human review, and logging what ran and when. I'm not babysitting each session. I'm reviewing outputs, making decisions, and queuing the next task.
You don't need VERA to implement this pattern. You need the discipline to define clear inputs, expected outputs, and a place to log what happened. A structured folder and a few markdown templates will get you most of the way there before you need custom infrastructure.
