How much of Hacker News is about AI?

Hacker News

This website counts titles containing the standalone word "AI", case-sensitive and word-bounded. "OpenAI" doesn't count. "AI-powered" does. There's a toggle for a wider vocabulary: artificial intelligence spelled out, LLM, GPT, and model and vendor names. Some quick stats: - 14.4% of new HN titles this year, against 10.9% in 2025. On the wider vocabulary, 21.9% and 16.1%. - First month above 1% was Oct 2016. Above 5%, Feb 2023. Above 10%, May 2025. - Over the last five years the quietest month was Jan 2022 at 0.8%. The peak was Feb 2026 at 15.9%. - 13.6% on weekdays against 12.4% at weekends. - Show HN runs highest of any category at 19.8% this year, which makes this post part of the number. As of this post, today is at 15% for the standard filter and 19% for the extended.

Visit product View on Hacker NewsAug 26, 2026

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74points

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Made the leaderboard

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TrustMRRFits verified-revenue profile · Strong signals: month · Missing: mobile apps, ios, personal

57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: hacker news, ide · Missing: https docs, excited, just released

35%35% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: model, new, openai · Missing: mac, agents, macos

31%31% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

19%19% predicted probability of success on AppSumo, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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