My

My 4 year old made a game

Hacker News

My 4 year old made a game

Bored playing the nth round of Uno, I thought it would be fun to write a game with my 4 year old daughter. Using Claude Sonnet 3.7 as our "developer" and me acting as the "Product Manager" aka LLM translator, I tried to capture her instructions as verbatim as I could, only adding context to make the prompts work. The result is a simple browser game which you can play. I added a writeup of all the prompts along the way so you can see how this was put together. It was only after I realised where she drew her inspiration from. If you have kids, it's definitely a fun exercise. My wife and I were blown away with how quickly we got something working, my daughter grew tired of it after about a minute.... I fear that this generation will never really appreciate how much effort this used to take. (No analytics, no signup, etc)

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4points
6comments
Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Strong signals: wife · Missing: supports, reddit linkedin, podcasting
78%78% 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: claude, context, using · Missing: mac, agents, macos
73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal
54%54% 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
42%42% 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
19%19% 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
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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