Graph Engineering: The Next Step After Prompts and Loops

Graph engineering is presented as the evolution beyond prompt and loop engineering for AI, focusing on the coordination of multiple agents to manage complex tasks. It introduces a system where nodes perform work, edges dictate workflow, and state management ensures continuity, moving towards autonomous operations.

• Prompt engineering instructs AI, loop engineering enables repetitive tasks, and graph engineering manages the overall workflow and coordination.
• Graph engineering involves defining nodes (agents, scripts, APIs) that perform work and edges that manage data flow, dependencies, and failure routes.
• This system allows for more complex tasks like launches requiring research, copy, code, legal review, and approval by orchestrating multiple agents.
• Key components include state management, gates for decision-making, cycles for error handling, and terminal states for task completion or human intervention.
• Graph engineering aims to create a visible system for coordination, moving beyond the limitations of single-agent loops for complex operations.
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