Graph Engineering: Revolutionizing AI Agent Coordination
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The Evolution of AI Agents Towards an Integrated Approach
The development of artificial intelligence agents has gone through several successive phases, each bringing its own set of innovations. Among these phases, we find prompt engineering, context engineering, tool usage, autonomous loops, memory systems, and multi-agent coordination. Today, a new approach is emerging: graph engineering.
A New Vision for AI Applications
Graph engineering proposes to view AI applications not as isolated entities, but as explicitly designed workflows. This method emphasizes coordination among agents, tools, deterministic functions, validators, data sources, and humans. The goal is to create a system where each component interacts smoothly and efficiently with the others.
Towards Optimized Coordination
With this approach, AI agents can be integrated into larger systems, allowing for optimized resource use and improved coordination. Graph engineering thus offers a new way to design AI systems, focusing on interaction and collaboration among different elements, rather than the autonomy of a single agent.
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