Interesting challenge! I've been playing with similar LLM setups for investment analysis, and I've noticed that the default "niceness" can be a hurdle.

Have you tried explicitly framing the prompt to reward identifying risks and downsides? For example, instead of asking "Is this a good investment?", try "What are the top 3 reasons this company is likely to fail?". You might get more critical output by shifting the focus.

Another thought - maybe try adjusting the temperature or top_p sampling parameters. Lowering these values might make the model more decisive and less likely to generate optimistic scenarios.