1. What is DeepSeek

DeepSeek is the name of a large model developed by DeepSeek, an AI company founded in Hangzhou in 2023. The development of DeepSeek is as follows:

1. In January 2024, "DeepSeek LLM" was released, which is the first version of the DeepSeek large model they officially released.
2. In May 2024, "DeepSeek-V2" was released, officially starting the price war for large models in China. At that time, the API price of the newly released DeepSeek-V2 was only 2.7% of GPT-4o. In the following week, all domestic manufacturers followed suit, and ByteDance, Alibaba, Baidu, and Tencent all lowered their prices.
3. In December 2024, "DeepSeek-V3" was released and open source, with a training cost of only US$5.576 million. Excluding the early exploration costs of major companies such as Meta and OpenAI, it is about one-third of that of others. The overall model evaluation capability is comparable to that of closed-source models, which shocked overseas. Since then, the mysterious power of the East has been completely established.
4. In January 2025, a new inference model DeepSeek-R1 is released and open source. Its performance is comparable to the industry benchmark OpenAI o1. At the same time, the API price is only 3.7% of OpenAI o1, which once again shocked overseas and caused Meta to set up four research groups overnight. The global computing power plummeted, and Nvidia's myth was in jeopardy.

Next, let’s take a look at how to use the DeepSeek-R1 model, which is popular all over the world.

2. DeepSeek-R1 core usage tips

2.1 General Principles (recommended to read first)

1. Natural conversation first
   No need to deliberately design a thinking chain, just express your needs directly
2. Goal-oriented communication
   Explaining the application scenario is more important than providing instructions
3. Dynamic Difficulty Adjustment
   Control output complexity through instructions such as "speaking human language"
4. Professional depth optional
   Retains but does not rely on traditional cue word engineering techniques

The following will explain in detail how to implement each principle.

2.2 Core Skill 1: Abandon Structured Templates

Principle

As a large model specialized in reasoning, DeepSeek-R1 has a complete thinking chain built in. The step-by-step instructions in traditional prompt word engineering (such as "Please analyze according to the following steps...") will limit its reasoning ability.

Comparative Cases

• Traditional method:

As a new energy industry analyst, please write a report according to the following structure:

1. Market size (800 words)
2. Competition landscape (800 words) 
3. Technical route (800 words) Requirements: Cite the latest data in 2024...
   

• Optimization method:

Next week, we will negotiate with BYD's battery supplier and need to:

1. Explain their technology advantages in layman's terms
2. Predict possible quote range
3. Provide 3 professional negotiation terms and usage scenarios

Difference in effects : The former produces standardized reports, while the latter generates practical guides that include price anchoring strategies.

2.3 Core Skill 2: Target Scenario Description

Operation formula

[Identity Background] + [Usage Scenario] + [Core Objective] + [Special Focus]

Application Examples

• Basic version: "I want to explain quantum mechanics to high school students. I need three life metaphors"
• Advanced version: "As a medical device salesperson, you need to prepare meeting materials with the directors of tertiary hospitals, focusing on the infection prevention and control advantages of our consumables in operating room scenarios."

2.4 Core Skill 3: Dynamic Difficulty Adjustment

When you encounter obscure responses, you can optimize them in the following ways:

1. Instant Fix
   Add "Please explain in a more popular way" after the answer
2. Pre-conditions
   "Assuming the audience has a junior high school education, please rephrase the explanation."
3. Gradual upgrade
   “Now add technical details (suitable for engineer level)”

3. Usage suggestions for different users

• New users
  Ask questions directly in a daily conversational manner
• Advanced User
  Try the target scenario description formula
• Professional users
  Combine traditional prompt techniques for deep customization

4. Conclusion: Let technology return to its service essence

The technological breakthrough of DeepSeek-R1 is essentially a return to the essence of AI services - when the big model is good enough to understand human intentions, we no longer need to learn "special language to talk to machines". This transformation is just like smartphones replacing command lines: the ultimate goal of technological evolution is to make complexity disappear.