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AI · January 26, 2026

WT

Was tired of drowning in HN comments, so I built an AI Chief of Staff

I've been lurking on HN for years. You know the drill: interesting headline, 200+ comments, you dive in thinking "I'll just skim for 5 minutes"... and an hour later you're 36 chambers deep in a thread about memory allocation patterns in Postgres and you've completely forgotten what the original article was about. I don't just want a "summary" (which usually just shortens the noise). I want the meta-consensus: "What is the actual trade-off being debated? Who is winning the argument? Why does this matter?" So I built HNSignals. Think of it less like a "summarizer" and more like a Chief of…

What it does

In the maker’s words, at launch

I've been lurking on HN for years. You know the drill: interesting headline, 200+ comments, you dive in thinking "I'll just skim for 5 minutes"... and an hour later you're 36 chambers deep in a thread about memory allocation patterns in Postgres and you've completely forgotten what the original article was about. I don't just want a "summary" (which usually just shortens the noise). I want the meta-consensus: "What is the actual trade-off being debated? Who is winning the argument? Why does this matter?" So I built HNSignals. Think of it less like a "summarizer" and more like a Chief of Staff who reads the entire thread for you and hands you a one-page executive brief. How it works: 1. Filters: Shows trending stories (50+ comments) where the discussion has heated up. 2. Extracts: An AI (Qwen 3 via Venice.ai) reads the top comments. 3. Structures: Instead of a wall of text, you get 4 specific signals: - The Hook: Why you should care. - The Gist: The core technical facts. - The Debate: The actual friction point (e.g., "Rust vs. C++ safety"). - The Verdict: The community consensus. Why I'm showing this (Beta): Most AI tools just shorten the text. I'm trying to extract the signal. It's a work in progress - the AI sometimes gets too clever, and I'm still tuning the cache strategy. I'd love feedback on whether this structured approach is actually better than a standard "TL;DR." Bonus meta-game: If this Show HN gets 50+ comments and makes it onto HNSignals itself, I'll read the AI's analysis of people analyzing my analyzer. (P.S. Please go easy on the intentional stress testing - my Lambda inference budget is finite!) Try it: https://hnsignals.com Example output The Heartbleed Bug (2014): https://hnsignals.com/signal/7548991 Ask HN: What is the most unethical thing you've done as a programmer? (2018): https://hnsignals.com/signal/17692005 Comparing the Same Project in Rust, Haskell, C++, Python, Scala and OCaml (2019): https://hnsignals.com/signal/20192645 OpenAI's GPT-3 may be the biggest thing since Bitcoin (2020): https://hnsignals.com/signal/23885684 Apple, What Have You Done? (2026): https://hnsignals.com/signal/46763592

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