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

(github.com)
21 points pablo-chacon | 5 comments | 25 Aug 25 06:48 UTC | HN request time: 0.625s | source

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.

1. ◴[25 Aug 25 06:48 UTC] No.45011005[source]▶
2. _jab ◴[26 Aug 25 15:30 UTC] No.45027949[source]▶
Gotta be honest, I think the spoon bending metaphor is unhelpful, and only misleads the audience and buries the lede here. It took me a while to figure out what this repo actually does.

But the insights are indeed interesting. I'm curious if you've found any way to quantify alignment differences between GPT-5 and the previous generation?

3. PoignardAzur ◴[26 Aug 25 21:48 UTC] No.45032751[source]▶
This seems like strong evidence that what the model learns is "Avoid answering questions in a way that would make OpenAI look bad when the screenshot shows up on social networks".

I wonder how much this is a result of various heuristics combining vs the network explicitly learning to model and maximize the above objective.

4. conception ◴[26 Aug 25 23:55 UTC] No.45033796[source]▶
This is pretty necessary if you’re using scientific jargon on Claude. Generally talk of blood or cleavage sites tends to get flagged but if you ask, is there anything in this prompt that is against your acceptable use policy they will read the prompt and say no it’s all fine and then you can say execute the prompt then and it’ll go forward.