LangGraph vs Attune AI
LangGraph brings graph-based agent orchestration to the LangChain ecosystem — powerful for complex, cyclical workflows. Attune AI takes a workflow-first approach that's easier to get started with and purpose-built for Claude Code developers.
Feature Comparison
| Feature | Attune AI | LangGraph |
|---|---|---|
| Claude-native integration | ✅ First-class | ⚠️ Via LangChain adapter |
| Orchestration model | Workflow-first (linear + parallel) | Graph-based (nodes + edges) |
| Prompt caching (90% cost savings) | ✅ Built-in | ❌ Manual setup |
| Code wizards | ✅ 10 built-in | ❌ None |
| Claude Code CLI integration | ✅ Plugin-native | ❌ None |
| Learning curve | Low (workflow DSL) | Steep (graph theory required) |
| Agent state persistence | ✅ Built-in | ✅ Checkpointing built-in |
| Human-in-the-loop | ⚠️ Via Socratic prompts | ✅ First-class |
| Open source license | ✅ Apache 2.0 | ✅ MIT |
| Installation | pip install attune-ai | pip install langgraph |
Choose Attune AI if...
- • You use Claude Code and want seamless CLI integration
- • You want linear workflows without graph theory overhead
- • Cost optimization (prompt caching) is important
- • You need built-in code wizards for everyday developer tasks
Choose LangGraph if...
- • You need cyclical, graph-based agent flows
- • Human-in-the-loop interrupts are a core requirement
- • You're already in the LangChain ecosystem
- • You need time-travel debugging and state branching
Try Attune AI for Claude Code
Free, open source, and installed in seconds.
pip install attune-ai