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The Million Dollar Prompt

Hacker News

The Million Dollar Prompt

Hey HN! I was having a discussion with a friend the other day about a future in which chunks of system prompts are auctioned off for ad space. It got me thinking about the milliondollarhomepage.com. This is the milliondollarprompt.org. * What it is * An experiment to see how a crowdsourced system prompt changes over 64 generations. Free to contribute, with a limit of 50 tok/person to get some spread in inputs. Honesty basis. 32,000 token system prompt. 1 generation = 500 tokens of user submissions. Each generation runs the same 32 test questions with the prompt, and the answers are recorded/replayable. The successful version of this is utter chaos.

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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 · Missing: supports, reddit linkedin, podcasting
87%87% 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.
Hacker NewsStrong engagement from HN community · Strong signals: 000, io · Missing: https docs, excited, just released
65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: user · Missing: mac, agents, macos
53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: answers · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, 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 · Missing: web3, chat, crypto
4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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