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Dungeon Master in Your Console

Hacker News

Dungeon Master in Your Console

I don't normally share side projects here(or in general). Don't have much time to open them up to too much attention. I started this project while riding in a car last weekend. Mainly to explore OpenAI Codex. Using Github mobile I wrote the initial specifications into the readme, and using the ChatGPT iOS app, had Codex build a simple CLI based dungeon master. Switched back to Github for managing the PRs and back and forth for the whole car ride... It kinda got a little out of hand from there, and it's now a mix of AI(mostly AI) and myself making adjustments... The first version was entirely OAI and it worked OK but was too easy on the player. Thanks to HN I had heard about the Wayfarer model and I find that model to be pretty entertaining. In the end I thought this turned out pretty "cute" and makes a decent time waster that looks like work wink wink

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Actual performance

14points
Made the leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, codex, chatgpt · Missing: mac, agents, macos
88%88% 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.
Indie HackersFits the IH revenue-focused audience · Strong signals: started, ios · Missing: supports, reddit linkedin, podcasting
81%81% predicted probability of success on Indie Hackers, 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
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: ios, way · Missing: mobile apps, personal, entrepreneurs
47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
44%44% 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
18%18% 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
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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