GP

GPTShirt – Describe shirt. Wear shirt.

Hacker News

GPTShirt – Describe shirt. Wear shirt.

Post: Hey HN! I built GPTShirt to make it ridiculously easy to create and buy good looking custom t-shirts, no design skills required. It's at https://gptshirt.app . How it works: 1) Describe your idea in a prompt, with optional reference images (people, objects, styles, etc.) 2) AI generates your design. Iterate and refine until happy. Powered by Nano Banana. 3) Order it - we handle printing and shipping 4) (Optional) Share it - handy for group orders. Some example shirts: - Family picnic with Totoro - https://gptshirt.app/designs/2910ae97-8c7a-4631-9271-291364f... - Cosmic Cat Island - https://gptshirt.app/designs/0d65835c-ea70-4a56-9f5e-92a0ec4... - Tropical Escher - https://gptshirt.app/designs/72cda84a-0862-4499-abf9-39ad3f9... It costs $20 per t-shirt, plus shipping. Shipping takes 3 to 5 business days. Would love to hear feedback - thanks for taking a look!

Visit product View on Hacker NewsSep 18, 2025

Actual performance

5points

Did not reach leaderboard

Launch Intel predictions

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

88%88% 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 · Missing: mac, agents, macos

58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

15%15% 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.

Correct prediction on native model

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