100kb – an opinionated feed of personal blogs

Hacker News

Hi HN! This is a personal project I finally got round to completing and shipping. It’s a simple feed of articles written by real people with interesting things to say. I wanted to explore some new technologies I haven't had a chance to try before, mostly rust and LLMs. As I browse HN each day I find myself most drawn to the content on personal blogs: people who have interesting things to say, from their own point-of-view, on a whole range of topics. Rather than being interested in particular topics, I’m more interested in reading from interesting people. This isn't a particularly new idea, there's been plenty of similar projects shared on HN and on the internet (Kagi Search, Marginalia, Bearblog etc). But, I don't think personal projects need to be revolutionary to be useful (to me at least). It's open source here https://github.com/danhilltech/100kb.golang

Visit product View on Hacker NewsAug 22, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, open · Missing: mac, agents, macos

69%69% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released

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

nativeThis product was originally launched on this platform.

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

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs

34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

33%33% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: real people · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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