AI Context Separator Cockpit
Indie HackersSource Code ZIP Fix memory leaks W/ Vaults-Context Recycler
Hey everyone, I got sick and tired of AI tools like Cursor leaking memory, bleeding context between my different coding projects, and hallucinating completely fake code. So I built a custom, local AI Context Separator
Visit productView on Indie HackersMay 1, 2026commitment-side-projectemployees-10-plusfounders-code-yes
Share cardActual performance
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: cursor, context, coding · Missing: mac, agents, macos90%90% 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.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: para · Missing: mobile apps, ios, personal41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: para · Missing: supports, reddit linkedin, podcasting34%34% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive31%31% 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, revenue19%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, crypto3%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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