Graph Engineering in the Era of LLM Agents: From Individual Intelligence to System Intelligence
- Published
- Source
- arXiv
- Paper number
- 982
- Field
- Information Retrieval
- arXiv ID
- 2608.21156
Key points
- From the perspective of 'the limits of individual intelligence → system intelligence,' it presented the next step after prompt, context, harness, and loop engineering.
- It organized graph-based design along four axes: task organization (what to do), agent coordination (who does it), runtime state management (how it runs), and system evolution.
- It provided a framework for approaching practical challenges in long-running systems, such as failure localization and recovery and structural improvement based on execution histories, through graph-based state management.
- A separate chapter covers scientific-discovery and lab-automation applications, making it directly useful for designing autonomous-lab agents.
- It published lists of related papers, datasets, and projects on GitHub for use as practical references.
Paper links
External research summaries. These are not HDATF publications or measured product results.