I reverse-engineered how ChatGPT thinks. Here’s how to get way better answers.

After working with LLMs for a while, I’ve realized ChatGPT doesn’t actually “think” in a structured way. It’s just predicting the most statistically probable next word, which is why broad questions tend to get shallow, generic responses.

The fix? Force it to reason before answering.

Here’s a method I’ve been using that consistently improves responses:

1. Make it analyze before answering.
   Instead of just asking a question, tell it to list the key factors first. Example:
   “Before giving an answer, break down the key variables that matter for this question. Then, compare multiple possible solutions before choosing the best one.”

2. Get it to self-critique.
   ChatGPT doesn’t naturally evaluate its own answers, but you can make it. Example: “Now analyze your response. What weaknesses, assumptions, or missing perspectives could be improved? Refine the answer accordingly.”

3. Force it to think from multiple perspectives.
   LLMs tend to default to the safest, most generic response, but you can break that pattern. Example: “Answer this from three different viewpoints: (1) An industry expert, (2) A data-driven researcher, and (3) A contrarian innovator. Then, combine the best insights into a final answer.”

Most people just take ChatGPT’s first response at face value, but if you force it into a structured reasoning process, the depth and accuracy improve dramatically. I’ve tested this across AI/ML topics, business strategy, and even debugging, and the difference is huge.

Curious if anyone else here has experimented with techniques like this. What’s your best method for getting better responses out of ChatGPT?