Prompt engineering research for AI agent understanding
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SuperPrompt is an open-source project aiming to enhance AI agent understanding through a novel prompting technique. It's designed for users interacting with large language models, particularly Claude, to elicit deeper, more "outside-the-box" reasoning and generate novel ideas. The core benefit is its potential to uncover unexplored areas of LLM capabilities, acting as a "soft jailbreak" for more creative and profound outputs.
How It Works
SuperPrompt utilizes a "canonical holographic metadata" approach, employing custom XML tags like <think>
to guide LLM reasoning. This method aims to force models into a "tree-of-thought" process, adapting its internal meta-prompt based on provided metadata to better suit the task. The prompt's structure, often appearing as "gibberish" to humans, is optimized for the LLM's internal processing, enabling it to explore conceptual evolution and self-adaptation.
Quick Start & Requirements
Highlighted Details
<think>
tag, claimed to outperform standard Chain-of-Thought (CoT) prompting.Maintenance & Community
Licensing & Compatibility
Limitations & Caveats
8 months ago
1 day