Building @Vennbee | AI Engineer & Tech Lead building performant, full-stack applications. Specializing in RAG systems,

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Nidheesh Vakharia • Peerlist

Open Source Graphite Alternative. Stacked diffs for GitHub. Work on multiple dependent pull requests as a linear stack of branches, with automatic PR management and conflict-aware rebasing.

Giff

A TypeScript library for explicit error handling. Instead of functions that throw or return null, you get a Result&lt;T, E&gt; type that makes the failure case part of the signature — the compiler tells you when you haven't handled it.Built while working on Vennbee's backend, where async tool chains kept eating errors silently. The flatMapAsync combinator chains calls that can fail, short-circuiting on the first error without a try/catch tower. partition handles fan-out patterns where some requests failing is okay and you want to keep going with what succeeded.Zero dependencies, JSON-serializable results, fully tree-shakeable.npm: @vennbee/result-type

Typescript Result Types

Vennbee is a revolutionary social media app that redefines how we connect and express ourselves online. Leveraging cutting-edge artificial intelligence, Vennbee offers a platform that celebrates individuality and the multidimensional nature of people. Unlike traditional social networks, Vennbee eliminates bland profiles and strict social graphs, allowing users to express themselves fully. Vennbee is designed for those who refuse to fit into one box and want to express their true selves. Join the new age of social media and experience a platform built for how humans actually exist.

Vennbee — Coming Soon

The Review Radar is a simple web application that allows users to input Amazon product links and find the best review videos on YouTube related to those products. Whether you’re a savvy shopper or a content creator, this tool can help you discover insightful reviews quickly. SIte: https://review-radar.vercel.app/

Review Radar

Trace AI is a smart note-taking application that helps users refine and organize their notes efficiently. The app allows users to input their rough notes in one window, while an AI-based engine works in another window to clean, format, and summarize the content for better readability and organization. This project combines the power of AI with a user-friendly interface to make the note-taking process more streamlined and effective. Why is it important or interesting to you? Note-taking is a crucial skill for students and professionals alike. However, many people struggle to keep their notes organized or formatted in a way that is easy to review. With Trace AI, we aim to make note-taking more efficient by leveraging AI to clean and refine notes automatically, allowing users to focus on the content rather than formatting. The project is particularly interesting because it merges AI technologies with real-world applications in education and productivity. It also provides the team with hands-on experience in working with cutting-edge technologies.