Loop

Loop Your prep, on loop. Loop turns your own notes and code into a role-specific preparation plan for interview, then helps you practice, receive feedback, and improve, all in one workspace. The problem I wanted to solve While preparing for interviews, I had no shortage of material. I had personal notes in OneNote, bookmarked tutorials, coding problems, and resources scattered across websites. What I lacked was direction. Which material mattered for the role I was targeting? What should I practice today? And after practicing, what should I improve? I built Loop to connect those pieces into a repeatable preparation cycle. How Loop works Start by bringing your notes, documents, and code into Loop and selecting your target role. From there, you can: Build a preparation plan: Generate relevant topics, drills, and a five-day schedule from your material. Explore your knowledge: Turn notes into an interactive mindmap, explore connections, and launch a drill from a concept. Practice with feedback: Answer technical, behavioral, or leadership questions and receive scores, actionable feedback, a model answer, and follow-up questions. Rehearse an interview: Run an adaptive mock interview that responds to your answers and ends with a structured assessment. Reason through code: Explore AI-generated execution simulations with step-by-step variable states and potential gotchas. Fill knowledge gaps: Request suggested resources, save useful ones, and track your reading. How Meta powers Loop Meta Muse Spark is Loop’s intelligence layer. Every AI feature makes a live call through Meta Model API: planning, question generation, answer feedback, adaptive interviewing, interview assessment, mindmap generation, resource suggestions, and code simulation. These calls run behind two Supabase Edge Functions, with the API key held server-side. React and TypeScript provide the interface, while Supabase handles authentication, saved data, and access controls. I also used Muse Code during development. What makes it personal Loop builds on my existing interview-preparation foundation. This entry focuses on the connected, Meta-powered workflow: turning my own material into a plan, making that plan actionable through practice, and using feedback to guide the next attempt. The goal is to make every preparation session lead to a clear next step. Try Loop: https://divya0702.github.io/loop/# Your material in. Interview readiness out.