I'm using Midjourney to create reward images for my word game Xordle

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I'm using Midjourney to solve a game design issue I had with my Wordle variant, Xordle, where it was fun to have themed puzzles but the themes tended to either be too hard to notice even after the puzzle was completed (missed opportunity for a fun moment for most players), or too easy to notice before the puzzle was completed (giving away the answer). It requires a little effort to generate prompts, but not too much; definitely worth it in this case as I can now do themes that are pretty vague and are revealed by the image, or connect totally un-themed words together to still get the fun moment at the end of the puzzle. This post talks about what lead to this feature and has example output.

Visit product View on Hacker NewsAug 10, 2022

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

54%54% 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.

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

48%48% 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

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: using · Missing: mac, agents, macos

30%30% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

25%25% 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

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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