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Why ChatGPT Gives Generic Answers And How To Fix It

13 0
30.09.2026

OpenAI said in 2026 that ChatGPT now reaches more than 900 million weekly users, including over 9 million paying business subscribers, a scale that all but guarantees the model was tuned to satisfy an average user, not your specific company. That scale is exactly why the advice feels borrowed from nowhere in particular.

Founders get generic ChatGPT answers because the model was trained through reinforcement learning from human feedback to produce responses that please the average rater across millions of conversations, not because it lacks the capacity to reason about a specific business. The fix involves custom instructions, ChatGPT Projects, and prompts that hand the model real business context instead of asking it to guess.

Why Do Founders Get Generic ChatGPT Answers in the First Place?

Generic output isn’t a bug. It’s the intended result of how OpenAI built the model to behave for strangers.

During training, human labelers rank multiple ChatGPT outputs against each other, and a reward model learns to predict which response people tend to prefer. That reward model, described in detail in OpenAI’s InstructGPT research, was built to optimize for outputs that satisfy a broad population of raters rather than any single reader’s context. If you ask a fresh chat “how do I grow my startup,” the model has no idea if you run a three-person SaaS company or a solo consulting practice, so it defaults to the answer most likely to be inoffensive and broadly true. That’s why ChatGPT gives generic answers to specific business questions: it’s playing the odds across every founder who has ever asked something similar.

The context window compounds the problem. Unless you tell ChatGPT who you are in that exact conversation, it starts from zero every time. There’s no persistent sense of your stage, your traction, or your constraints unless you’ve explicitly stored that somewhere the model can read.

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The Statistical Averaging Behind Generic ChatGPT Answers

Large language models predict the next most probable token given everything they’ve seen so far. Stack millions of business questions on top of each other, and the statistically safest answer becomes a blend of every answer, which is why “know your audience” and “post more........

© Forbes