Analysis
This article offers a fascinating look into the mechanics of 'harness' software, brilliantly explaining how modern AI agents like Cursor and Claude Desktop actually function. By examining the raw inputs and outputs passed to the Large Language Model (LLM), it demystifies the complex orchestration happening behind the scenes. It's an incredibly exciting read for anyone looking to understand how tools like 検索拡張生成 (RAG) and multimodal features are expanding the capabilities of AI.
Key Takeaways
- •Many popular AI applications like Cursor and Devin do not have built-in AI, but act as 'harnesses' that process inputs and outputs for external Large Language Models (LLMs).
- •Harnesses supercharge LLMs by providing critical features like long-term memory, tool usage, and Retrieval-Augmented Generation (RAG).
- •Observing the direct inputs and outputs between the harness and the LLM is a highly effective way to understand how complex AI agents operate.
Reference / Citation
View Original"A harness is software that complements the input and output of the LLM, providing input in a format the LLM can understand, and appropriately processing the output from the LLM to return it to the user."
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