Gl

Glider with code (again)

Hacker News

Glider with code (again)

http://glider5.com/ is kind of like an open search engine where all the code is open, forkable and votable. Kind of like Quora but with code instead of text. Since I posted this last time[1] the site actually now works, with a bunch of updates: * Location support ("where am I") and city database data * Synonym support ("where am I" == "where I am") * Query exposure (recent queries, broken queries, top queries, top users....) * API[2] so you can query from other sites/apps There are still a lot of bugs, the site only works well in chrome, things like that. There's also a blog[3]. Network access for snippets is coming so they can call out to other APIs. [1] - https://news.ycombinator.com/item?id=13805212 [2] - https://glider5.com/help-glider-api [3] - http://blog.glider5.com/

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, user, new · Missing: mac, agents, macos
80%80% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
77%77% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: apps, users · Missing: mobile apps, ios, personal
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
29%29% 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
19%19% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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