I built an external context layer for AI agents - most of it already exists, here's what doesn't
Ritvika Mishra developed an external context layer for AI agents called Meniscus during a hackathon. The tool aims to capture user activity across various platforms and provide a structured context for AI interactions. However, upon further review, Mishra discovered that many of the features already exist in other tools.
- ▪Meniscus is designed to hold knowledge externally for AI agents, allowing users to switch between tools without losing context.
- ▪The architecture of Meniscus includes events, entities, and threads to organize user activity and relevant information.
- ▪Mishra found that most of the functionalities he created were already available in existing solutions like Zep and Rewind.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3880227) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Ritvika Mishra Posted on May 20 I built an external context layer for AI agents - most of it already exists, here's what doesn't #ai #architecture #systems Imagine you're deep into a brainstorming session with an AI, going back and forth for an hour - and then the free tier rate limit hits. Now you have to switch to another AI and re-explain everything from scratch. The context, the problem, what you've tried, where you're stuck. All of it.
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