Coffee Hop – Find work-friendly coffee shops by walking time

Hacker News

For those that like to work in coffee shops... I built this over the holidays to get myself out of the house more in 2026. Coffee Hop helps remote workers find cafés (and pubs) nearby, rated by the community for WiFi speed, plug availability, coffee quality, and ambiance. Pick how far you want to walk (5 mins to an hour), work for a couple hours, then hop to your next spot. The idea: $10-15/day in coffee vs $50 for a desk in a co-working space, plus you get some movement between sessions. Built entirely with AI (Cursor and Opus 4.5) - I didn't write any code myself. Not many ratings yet, but I'm using it myself to build up the initial data.

Visit product View on Hacker NewsDec 30, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: cursor, using, code · Missing: mac, agents, macos

75%75% 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.

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

59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

57%57% predicted probability of success on Indie Hackers, 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

52%52% 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 · Strong signals: plus, friendly · Missing: platform, intuitive, reviews

42%42% 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

26%26% 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.

Incorrect prediction on native model

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