πŸš€ We just built our first real-time implementation of Graph Engineering, inspired by our experience building graph tooling used by 4,000+ developers.

Reddit r/ArtificialInteligence Tools

Summary

GraphArc is a new open-source tool that transforms AI agent workflows into interactive, real-time graphs, enabling developers to visualize, inspect, debug, and control agent execution before approving actions.

πŸ”— Repo: https://github.com/CodeGraphContext/grapharc Have you ever been frustrated because your AI agent: ❌ Takes actions you never intended? ❌ Creates, modifies, or even pushes changes you never asked for? ❌ Feels like a complete black box, making it impossible to understand what's happening until it's too late? What if, before execution, you could visualize the entire orchestration graph - every agent, every dependency, every decision, and inspect it from anywhere, even your phone, before granting approval? That's exactly what GraphArc is built for. Instead of treating agent execution as hidden traces buried in logs, GraphArc transforms workflows into interactive, real-time graphs that you can visualize, inspect, debug, and control. Because the future of AI isn't just autonomous. It's observable. Debuggable. Engineerable. This is our first real-world implementation of Graph Engineering, and we're excited to explore where this paradigm can go with the open-source community. πŸ’‘ We'd love your feedback, ideas, and contributions. ⭐ If this vision resonates with you, please consider starring the repository - it genuinely helps us grow and validates this direction. Let's make AI workflows understandable, not mysterious. #GraphEngineering #GraphArc #AIAgents #AgenticAI #LLM #OpenSource #DeveloperTools #AIEngineering #SoftwareEngineering
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Graph engineering ? Or we can say agents on steroids....

Reddit r/artificial

Introduces GraphARC, an MIT-licensed open-source tool that lets a model author agent graph topologies at runtime, with a deterministic admission gate for auditable execution, built on LangGraph and running locally via ollama or against cloud APIs.

@akshay_pachaar: https://x.com/akshay_pachaar/status/2081089131808243999

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Graph engineering is a new term for coordinating multiple AI agent loops using graphs of nodes (work units) and edges (control flow). The article explains the concept, its historical context (LangGraph, AutoGen, etc.), and the real challenges of designing such graphs.