Spoon-Bending – a framework for analyzing GPT-5 alignment behavior

Hacker News

I put together a repo called Spoon-Bending, it is not a jailbreak or hack, it is a structured logical framework for studying how GPT-5 responds under different framings compared to earlier versions. The framework maps responses into zones of refusal, partial analysis, or free exploration, making alignment behavior more reproducible and easier to study systematically. The idea is simple: by treating prompts and outputs as part of a logical schema, you can start to see objective patterns in how alignment shifts across versions. The README explains the schema and provides concrete tactics for testing it.

Visit product View on Hacker NewsAug 25, 2025

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Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

42%42% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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40%40% predicted probability of success on TrustMRR, 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

39%39% 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 HuntUnlikely to reach the leaderboard · Strong signals: plain · Missing: mac, agents, macos

35%35% 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

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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16%16% predicted probability of success on BetaList, based on ML models trained on real launch data.

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.

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