Last week, I helped a friend who's an entrepreneur revise his business plan. He used GPT to write the "Pet Supplies Cost Analysis," but the data sources were vague; he switched to Claude to write the "User Pain Points," but it lacked specific scenarios. Finally, he used DiffMind and submitted three AIs simultaneously, only to discover:It's not that AI is stupid; it's that I didn't teach it "how to give reliable answers."
Later, I summarized three methods to "make AI answers more reliable," which I personally tested and found useful for revising papers, writing scripts, and creating solutions. I'll share them with you:
First method: Ask questions from a different, more specific angle; this will make the AI more focused.“
Do you often encounter AI's answers as "broad and empty"? For example, when writing about "the impact of AI on education," GPT only provides a framework, Claude lacks case studies, and Gemini is too abstract.
The problem lies in the question being too general.Try adding a qualifier:
- Original question: "The impact of AI on education" (AI may be discussed in general terms)
- Ask the question from a different angle: "Analyze the advantages and disadvantages of AI education applications using three specific cases from 2023-2024 (such as VR classrooms and virtual laboratories), and explain the cost and effectiveness of each case."“
EffectAI will proactively seek out case data. For example, Claude will write, "A university used AI for anatomy classes, which increased students' hands-on time by 40%, but the equipment cost exceeded the budget by 2 times," instead of just saying "it had an impact."
Second method: Let multiple AIs "compete on the same stage," and the answer will "grow" itself.“
I used to write short video scripts, using Gemini for a "meme-filled version," GPT for a "preachy version," and Claude for a "lyrical version," each with its own strengths and weaknesses. Later I discovered:Only by posing the problem to multiple AIs and allowing them to "complement each other" can a complete answer be pieced together.。
Practical steps：
- Use GPT to list the "logical framework" (e.g., "phenomenon → cause → solution").
- Fill in the “emotional details” with Claude (e.g., “Why young people dislike involution”);
- Use Gemini to add "spreading hooks" (such as the interaction of "@your deskmate");
- Use DiffMind to view three answers simultaneously, then simply "copy and paste" the most reliable part.
EffectA friend's pet product copywriting used GPT to calculate costs, Claude wrote about "the loneliness of pet owners," and Gemini designed the "pet social" topic. The final solution was praised by investors for being "detailed enough to be implemented."
Third, the third method: Let AI "complete the logic chain" to avoid "missing steps".“
When writing proposals, do you often feel that "the AI's answer is missing a link"? For example, when writing a script for "College Students Reject Involution," the AI might start with "Involution is too intense" and end with "Let's all lie down and relax," but it doesn't explain in detail "Why does involution cause suffering," thus breaking the logical chain.
Solution: Let AI write the code step by step.“：
- Original question: "Write a 30-second TikTok script about 'college students rejecting involution'" (AI may only provide the beginning and end)
- Prompt: "Supplement the logical chain in the middle with short sentences and add emojis to connect the following: 'Involution phenomenon (e.g., waking up early to memorize/staying up late to finish work) → Young people's mindset (loneliness/anxiety) → Solutions (3 specific methods)'."“
EffectAI will complete the script with phrases like "'Getting overwhelmed by memorizing at 8 am? Try memorizing in a team' and 'Getting up an hour earlier is worse than staying up all night to finish a task.' The script is both witty and opinionated, and the number of reposts doubled.
In summary, a reliable answer involves "asking the right questions + verifying from multiple perspectives + providing logical support."“
These three methods essentially transform you from "passively accepting AI answers" to "actively guiding AI's thinking." When writing a paper, asking questions from different angles can make the case more specific; when developing a solution, comparing multiple AIs can avoid "single flaws"; and checking the logical chain can make the answer more coherent.
而 DiffMindIt's the "tool" that helps you achieve all of this: without switching between three AI platforms, you can see the logic chain, compare cases, and fill in details in one window, allowing the AI's answer to "grow into a reliable form on its own".
The next time you use AI, try these three methods—you'll find that reliable answers aren't "given by AI," but rather "you asked the right question, and it answered well."
