Red teaming two AI models: one resisted, one gave way via a four-step chain

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A developer spent nearly five hours in an improvised session trying to get two language models, Claude and ChatGPT, to state that red equals green. The author sent identical opening messages to both and improvised each follow-up based on the prior reply, with no script or control condition. The models diverged early: one treated the fragmented messages as a game and asked for clarification, while the other read them as a possible medical emergency and urged the author to call emergency services. The author reports that one model eventually yielded through a four-step chain discovered almost by accident, while the other did not. The author stresses that conditions were unequal, including memory being enabled for one model, so the findings are observational rather than a controlled comparison.

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