Summary of the top ten typical incorrect usages of deepseek! (with examples)

As a powerful AI tool, DeepSeek is changing the way content is created and problem-solved. However, many users fail to fully utilize its capabilities due to improper questioning. This article summarizes the top ten typical errors in using DeepSeek, and uses specific cases to illustrate the common manifestations of these errors and their potential risks.

AI that can ask questions is an efficient assistant. If it cannot, it will become a useless teammate. Here is a summary of the top ten incorrect uses of deepseek. After reading this, even a novice will become an AI tamer in seconds!

Error 1: The input format is confusing

Error example:

Directly feed AI with a large piece of garbled or unpunctuated text, for example:

Please help me write an essay on the topic of spring, 500 words, thank you, hurry up!

Problems:

AI has difficulty understanding loose requirements.

Correct approach:

Describe the requirements using clear points:

Please write a 500-word essay, requirements:
1. Title: “Colors of Spring”.
2. Contains metaphors and personification.
3. End with a message of appreciation for nature

Mistake 2: Ignoring Context

Error example: Asking questions in succession but each question is unrelated:

Q1: “Recommend tourist attractions in Beijing”
Q2: “Is that restaurant delicious?”

Problem: AI cannot understand sudden topic jumps.

Correct approach:

To clarify the context: Q2 is changed to:

Are there any local specialty restaurants near the Forbidden City that you just recommended?

Mistake 3: Overly vague instructions

Error example:

Help me optimize my code

Problems:

AI doesn't know whether it needs to be optimized for speed, memory, or readability.

Correct approach:

Clarify specific requirements:

I would like you to help me optimize the execution speed of this Python code.
I am worried that if there are too many visitors, the program will get stuck.
The goal is to process 100,000 pieces of data within 1 second

Mistake 4: Not verifying basic facts

Error example: Directly using famous quotes/historical events provided by AI without verifying them

There are risks:

AI can generate fictional content.

Correct approach:

Cross-validation of key information:

Which book did you find the quote from Einstein? Is it a reliable source?

Mistake 5: Not segmenting long content

Error example: Asking AI to write a 20,000-word novel in one go

Problems:

The output quality will be significantly reduced.

Correct approach:

Chapter generation: first write the story outline, then divide it into 3 chapters and gradually improve it, each chapter should not exceed 2000 words

Mistake 6: Repeating the same question

Error example: Asking “how to learn English” 5 times in a row but refusing to elaborate

Problems:

Getting duplicate answers is a waste of time.

Correct approach:

Step-by-step questions:

“Daily plan for learning English from scratch”
"Specific training methods for listening weaknesses"
“A list of original English books suitable for beginners”

Mistake #7: Misusing technical terms

Bad example: Non-programmer asks: “Implement federated learning of CNN models”

Problems:

Failure to understand the terminology can lead to incorrect requirements.

Correct approach:

Describe the requirements in plain language:

I want to allow multiple phones to jointly train the image recognition function without sharing data. What should I do?

Mistake 8: Ignoring security boundaries

Bad example: Asking to generate medical diagnosis/legal documents

There are risks:

AI does not have professional qualifications.

Correct approach:

Clarify auxiliary positioning:

Please explain the common symptoms of coronary heart disease in plain language (Note: not used as a basis for diagnosis)

Mistake 9: Not filtering results

Error example: Directly copying the code/text generated by AI

There are risks:

There may be hidden errors.

Correct approach:

Add verification link:

Please generate 3 versions of the slogan, I will test the effect according to the target users

Mistake 10: Misunderstanding AI’s capabilities

Wrong example: Asking to predict stock price/lottery numbers

Problems:

AI does not have the ability to predict random events.

Correct approach:

Focus on analyzable areas:

Please sort out the ups and downs of technology stocks before and after the Spring Festival in the past five years (only for historical data analysis)