A Drip of JavaScript

Hacker News

Over the past couple of years, I've been very impressed by Kale Davis's Hacker Newsletter and Peter Cooper's entire newsletter empire. They're clearly meeting people's need to stay caught up on industry news without spending their entire lives watching HN and Twitter. Their success has inspired me to try something similar. So I've just begun publishing a JS newsletter called "A Drip of JavaScript." Rather than focus on the latest JS news (which JavaScript Weekly already does rather well), each issue is just a short article about some aspect of programming in JavaScript. The newsletter is aimed at intermediate JS developers, or beginners at JS who already know another language. Some of you might be wondering why I didn't just start a blog. I've found that there is something terribly compelling about having something just show up in your inbox without having to go looking for it. And I'm hoping that this will end up helping developers who want to improve their skills but don't have a lot of time on their hands. If you have any feedback or suggestions, I'd love to hear them. Thanks! Newsletter: http://designpepper.com/a-drip-of-javascript Issue 1: http://us6.campaign-archive1.com/?u=2cc20705b76fa66ab84a6634f&id=ce9ce7921e&e=36e087d5a5 Issue 2: http://us6.campaign-archive1.com/?u=2cc20705b76fa66ab84a6634f&id=c8f1074cb2&e=36e087d5a5

Visit product View on Hacker NewsJan 27, 2013

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

75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

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

Hacker NewsStrong engagement from HN community · Strong signals: hacker news, io · Missing: https docs, excited, just released

51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

28%28% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

21%21% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

10%10% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · 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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