AllAmericanBreakfast's Shortform

DirectedEvolution

This is a special post for quick takes by DirectedEvolution. Only they can create top-level comments. Comments here also appear on the Quick Takes page and All Posts page.

I've been spending a lot of time exploring business ideas with Gemini 3.0 pro. It is both persuasive and inconsistent.

The pattern that has emerged is this:

I run a set of ideas, along with my goals and context, by Gemini sequentially. It rejects most, but approves one or more of them. Some ideas are my originals, others are Gemini-proposed improvements of my ideas.
I use Gemini to develop the idea and produce a rough business plan. It strongly encourages me to take immediate, costly steps to execute: purchasing administrating infrastructure, taking long trips to inspect leads, contacting vendors or potential customers. It suggests Google products at times, though it's possible these simply are the best choices for the problem it's addressing.
After hitting my Gemini pro usage cap, I continue using fast mode to explore "pro-approved" business ideas. Fast mode lacks judgment to evaluate ideas, but can accurately answer many questions about practical execution details.
The next day, when my usage limit refreshes, I summarize the previous business idea for Gemini. It immediately identifies a profound flaw in the idea that I find compelling, causing me to drop the idea.

My explanation for this pattern is that business viability is all-or-nothing: solve every problem, or fail. There are too many problems to focus on all of them in a single conversation. When the subset I can focus on gets solved by an idea, execution of the idea becomes the new focus of the conversation. But reintroducing the idea outside the previous context allows Gemini to focus on a new set of problems. Since nearly all business ideas have at least one fatal flaw, there will almost always be one for Gemini to discover.

Here are some examples of this dynamic. As a reminder, many of these ideas are Gemini-proposed modifications of ideas I'd suggested that were subsequently immediately rejected by Gemini in a followup conversation.

Idea: Providing business intelligence mined from government sources to rural real estate developers. Fatal flaw: tells experts what they already know or devolves into a consulting gig.
Idea: Facilitate paying owners of unlisted property to discuss a possible sale. Fatal flaw: willingness to sell is not bottlenecked by willingness to discuss a sale.
Idea: Pay to message CEOs. Fatal flaw: already tried and failed. CEOs won't manage a separate inbox and won't disclose their email.
Idea: Biotech recruiter lead sourcing from academia based on academic data exhaust. Fatal flaw: Turned from bullish to bearish on ability to extract valuable information from this exhaust.
Idea: Healthcare admin for allied health professionals working in home settings or remotely. Fatal flaw: Unacceptable unit economics.

8gwern8mo

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 = ... (read more)

2DirectedEvolution8mo

Also, according to Gemini pro itself in response to me pasting this post into the chat, "System recommendations for Google products during execution phases occur because they are statistically dominant in enterprise operational datasets, not due to hardcoded upselling directives."

AllAmericanBreakfast's Shortform

7

AllAmericanBreakfast's Shortform

7