Sampletext.store/ We built a dumb web shop and we cannot look away

Hacker News

So this all started two weeks ago as a stupid inside joke with friends in a group chat where we got a chatgpt powered bot to write plugins for itself and told it to build one that would make it fetch a random image from Wikipedia and then place words from the same article onto it. Often times it would just return mangled garbage or be completely incoherent but every now and then something astoundingly funny or profound would break through (if you have that certain 2005 idiotic internet humor that we/I certainly suffer from). And well a sleepless weekend and two maxed out copilot subscriptions later, what I can only describe as antipattern for the pure sake of having dumb fun actually went live. For an added bonus, some banger keygen chiptunes are highly reccomended for browsing. Might put that in at some point in the future... And on the incredibly minuscule chance that you even know or remember ][CdK][… sup bucko, we still ain’t dead.

Visit product View on Hacker NewsApr 30, 2026

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

84%84% 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: chatgpt · Missing: mac, agents, macos

75%75% 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

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 · Missing: plus, platform, intuitive

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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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