Ralph Workflow vs Conductor Teams: Local-First Coordination vs Reviewable Finish
Conductor Teams is a markdown-native local-first orchestration tool for coding teams. Ralph Workflow is a free open-source composable loop framework for autonomous coding. Here is how they compare.
Ralph Workflow vs Conductor Teams: Local-First Coordination vs Reviewable Finish
Conductor Teams is a markdown-native local-first orchestration tool for coding teams. Ralph Workflow is a free open-source composable loop framework for autonomous coding runs that aims to end in finished, tested code you can review.
They overlap on orchestration, but they emphasize different outcomes.
At a Glance
| Ralph Workflow | Conductor Teams | |
|---|---|---|
| What it is | Operating system for autonomous coding: free open-source composable loop framework and AI orchestrator | Markdown-native local-first orchestration for coding teams |
| License | AGPL (source) / CC0 (outputs) | Free / Open source |
| Setup | TOML config files, no cloud required | Varies |
| Vendor lock-in | None — own your config | Varies |
| Primary use case | Unattended coding runs with a reviewable finish | Local-first coordination across coding teammates and agents |
Key Differences
Conductor Teams leans into markdown-native coordination, local-first operation, and branch/worktree-oriented team flows. Ralph Workflow is more opinionated about the software task lifecycle: plan, build, verify, and come back to a clear finish state.
Ralph Workflow is the better choice when you want:
- A strong default workflow for writing software
- A simple loop core composed into bigger workflow stages
- Cost control via model routing across phases
- A workflow you can use today, then extend later without replacing the core
Conductor Teams is the better choice when you want:
- Markdown-native local-first orchestration
- Branch/worktree-oriented modes
- Parallel execution with a team coordination flavor
Feature Comparison
| Feature | Ralph Workflow | Conductor Teams |
|---|---|---|
| Multi-agent orchestration | ✅ | ⚠️ |
| Claude Code integration | ✅ | ❌ |
| OpenCode / Codex integration | ✅ | ❌ |
| Cost model routing | ✅ | ❌ |
| Unattended execution | ✅ (built for it) | ⚠️ |
| Policy-defined config (TOML) | ✅ | ❌ |
| Checkpoint / resume | ✅ | ⚠️ |
| MCP support | ✅ | ⚠️ |
| Parallel work units | ✅ | ✅ |
| Open source | ✅ | ✅ |
| Self-hosted | ✅ | ✅ |
Why the Finish State Changes the Evaluation
A lot of orchestration tools look similar if you only compare how they start work. The more useful comparison is how they finish.
Ralph Workflow is built around the idea that autonomous coding should end with something explicit: what changed, what checks passed, what failed, and what still needs a human call.
That makes it a stronger fit for teams whose real pain is not coordination alone, but trust in the result when nobody was watching the session.
Try Ralph Workflow
pipx install ralph-workflow
cd /path/to/your/project
ralph --init
$EDITOR PROMPT.md # write your task
ralph # walk away
Ralph Workflow runs on your own machine. It works with Claude Code, Codex, and OpenCode. The default workflow handles planning, development, verification, and follow-up — or you can compose your own.
Install guide → · Quick start → · Primary Codeberg repo → · GitHub mirror: github.com/Ralph-Workflow/Ralph-Workflow