Loop Interviewer
The Intelligent AI Voice Interviewer for LeetCode
What it does
Traditional coding practice is silent. Real interviews are not. Loop introduces an interactive voice layer that probes your reasoning, challenges your edge cases, and guides your progress—exactly like a senior software engineer from a top-tier tech firm.
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I've long had a dislike for leetcode interviews on both sides of the coin. Project-based interviews can also be challenging because it can end up filtering out folks who don't want to spend several hours building something in their free time. I met up with a friend last year -- a very senior dev -- who had taken some time off to study leetcode exercises while preparing for FAANG interviews. It struck me that one of the key measures of whether a candidate is a fit for a team is rather synthetic. CodeRev.app is a simple, lightweight tool that helps teams evaluate candidates using code reviews.…
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Hey HN! I’m Andrew, and I built Code Coach with my good friends, Akshay and Chetan. Code Coach is an AI-powered interview coach that you talk to. It plugs right into Leetcode and turns any problem into a mock interview – it grills you the same way a real interviewer would and provides in-depth feedback on where you can improve. I built Code Coach to solve some of my own problems when practicing for technical interviews. I knew I had to practice communicating my reasoning while coding, but found it intimidating to schedule mock interviews with friends. More often than not, I ended up talking…
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Parallel agents, diff reviewer, and multi-model comparisons
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Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
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