If you’re wasting time cycling, you could just use the Playground and an API key. That’s what I do, no usage limit issues then. Or does ‘Pro’ do something importantly different than simply picking gemini-3.1-pro-preview in the Google Playground?
Anyway, this sounds like you’re experiencing the sycophancy of post-0325 Geminis in both directions: in the first, it’s pleasing you by talking about how wonderful the idea is; in the second, you’re presenting it for critique, and so it tears the idea down as you clearly expect. (This is why I use Gemini mostly for coming up with suggestions and critiques, but feed them into other LLMs like GPT-5.2 Pro or Kimi K2.5, with a warning to distrust Gemini feedback, before I act on them.)
Haven’t explored that option, thanks for the suggestion.
I agree sycophancy is part of the problem. However, the issue I’m getting at here has more to do with biases introduced by the way ideas are selected using my current approach.
Idea viability follows a multiplicative hurdle model based on independent factors. VALUE = A x B x C x D. AI (and human operator) only have intelligence and attention to address a subset of factors at one time (A and B). The others (C and D) are ignored. This problem is compounded by iteratively sampling ideas:
PARTIAL_VALUE1 = A1 x B1, PARTIAL_VALUE2 = A2 x B2, …
The problem is finally exacerbated by picking the idea with highest PARTIAL_VALUE and optimizing the in-focus factors (A and B) while refining technical execution plan focused on these factors.
Reintroducing the selected idea by itself to the AI identifies forgotten factors C and D, which contain fatal flaws simply because most untried ideas are unviable for multiple reasons in a competitive market. Selecting for ideas where in-focus factors (A and B) are viable also selects for ideas where out-of-focus factors (C and D) are unviable.
If you’re wasting time cycling, you could just use the Playground and an API key. That’s what I do, no usage limit issues then. Or does ‘Pro’ do something importantly different than simply picking gemini-3.1-pro-preview in the Google Playground?
Anyway, this sounds like you’re experiencing the sycophancy of post-0325 Geminis in both directions: in the first, it’s pleasing you by talking about how wonderful the idea is; in the second, you’re presenting it for critique, and so it tears the idea down as you clearly expect. (This is why I use Gemini mostly for coming up with suggestions and critiques, but feed them into other LLMs like GPT-5.2 Pro or Kimi K2.5, with a warning to distrust Gemini feedback, before I act on them.)
Haven’t explored that option, thanks for the suggestion.
I agree sycophancy is part of the problem. However, the issue I’m getting at here has more to do with biases introduced by the way ideas are selected using my current approach.
Idea viability follows a multiplicative hurdle model based on independent factors. VALUE = A x B x C x D. AI (and human operator) only have intelligence and attention to address a subset of factors at one time (A and B). The others (C and D) are ignored. This problem is compounded by iteratively sampling ideas:
PARTIAL_VALUE1 = A1 x B1, PARTIAL_VALUE2 = A2 x B2, …
The problem is finally exacerbated by picking the idea with highest PARTIAL_VALUE and optimizing the in-focus factors (A and B) while refining technical execution plan focused on these factors.
Reintroducing the selected idea by itself to the AI identifies forgotten factors C and D, which contain fatal flaws simply because most untried ideas are unviable for multiple reasons in a competitive market. Selecting for ideas where in-focus factors (A and B) are viable also selects for ideas where out-of-focus factors (C and D) are unviable.