[Seeking Knowledge] Deepseek Uses Common Dry Goods Skills To Help You Get Started Quickly

In efficient communication, the quality of questions directly affects the value of answers. In order to help everyone get accurate answers quickly in various occasions, whether in the field of learning, work or technology, we have carefully prepared the following six universal question templates and cases. These templates have been verified in practice and can help you obtain the required information more effectively:

　　 Template I : Problem location formula: background description+core problem+specific requirements

Case: × Fuzzy question: "What should I do if the Python code reports an error? ”This kind of questioning is too general and does not provide enough information to help the respondent understand the context and specific details of the question. √ Optimization question: "I am using Python to climb the Douban movie TOP250 (background), but I encountered a 403 error (problem) returned by requests. get(). Attempted to add User Agent header, still failed (attempted). How to bypass the anti climbing mechanism? Specific code examples (requirements) are required. ”This kind of questioning method clearly describes the background, points out the core problems encountered, and specifies the needs, which helps the respondent to quickly locate the problem and provide effective solutions.

　 Template II : Formula of comparison decision method:

Option comparison+applicable scenario+decision-making standard case: × Inefficient question: "Should I choose MySQL or MongoDB? ”The statement of this problem is too simple to provide enough background information and specific needs, so it is difficult to give targeted suggestions. √ Optimization question: "I am currently planning to develop a real-time log analysis system (specific scenario), which needs to be able to process up to 10000 JSON logs per second (specific requirements). When selecting a database, I am currently hesitant between MySQL and MongoDB (specific options). I am more concerned about the database's write speed and horizontal scalability (evaluation criteria). Which database is more suitable for me according to my needs? Or do you have a recommended scheme to mix the two databases? ”Through this way of questioning, the questioner not only clarified the development scenario and specific needs, but also pointed out the evaluation criteria he cared about, and asked openly about possible hybrid schemes. This way of questioning is more efficient and can help the questioner obtain more accurate and practical suggestions.

　　 Template III : Formula of task disassembly method: big goal → small step+current checkpoint+expected result case: × General question: "How to improve user growth?" Although the question is direct, it lacks specific background information and goals, making it difficult for respondents to provide targeted suggestions. User growth is a complex process involving many aspects, such as market positioning, product optimization, marketing strategies, etc. In order to get a more effective answer, we need to provide a more detailed description of the situation. √ Optimize questions: "The goal is to increase the daily APP activity from 50000 to 100000 within three months (the big goal). The registration process has been optimized (steps completed), but the sharing rate of existing users is only 2% (click). The strategy of seeking zero cost to increase the fission rate is expected to achieve a 5% sharing rate (expected). ”This optimized question provides clear goals, current progress and specific problems encountered. It points out a clear time frame (within three months), a specific goal (to increase the number of daily active users from 50000 to 100000), and describes the measures that have been taken (to optimize the registration process). At the same time, it also pointed out the current bottleneck (the user sharing rate is only 2%), and proposed a specific demand (hope to increase the sharing rate to 5% without increasing costs). Such questions are more likely to attract experienced experts and provide practical suggestions and strategies.

　 Template IV: Formula of error troubleshooting method: phenomenon+environmental information+tried scheme+complete error report

Case: × Invalid question: "My program can't run!" This kind of question is too general and lacks specific information, such as running environment, error phenomenon, tried solutions, etc. It is difficult to get targeted help with such questions, because the respondents cannot locate the specific reasons for the questions according to the information provided. √ Optimize questions: "In Ubuntu 22.04+PyTorch 1.12 When training CNN in the environment (environment), the loss value is always NaN (phenomenon). Data normalization has been checked to reduce the learning rate to 0.0001 (try). Complete error reporting: RuntimeError: NaN detected Inoutput (error). How can I troubleshoot possible data layer problems? ”This kind of questioning is very clear and specific, providing enough information to help the respondent locate the question. The questioner described in detail the running environment, the phenomena encountered, the solutions tried and the complete error information. This kind of questioning is easier to get targeted help, because respondents can make specific analysis and suggestions based on the information provided.

　　 Template V : Formula of scheme evaluation method: existing scheme+concerns+ideal characteristic case: × Subjective question: "Is there a problem with my plan?" This kind of question is too subjective. It does not clearly point out the specific problem points, nor provide any background information or specific needs, so it is difficult to get targeted suggestions or solutions. √ Optimize the question: "It is planned to use Kafka as the message queue of the order system (existing scheme), and worry about the over ten thousand level concurrent lower delay in peak hours (concern). 99.9% of messages need to be processed within 100ms (ideal feature). Is there a more appropriate architecture? Or Kafka parameter optimization suggestions? ”This kind of questioning method is more specific and objective. It clearly describes the existing scheme, possible problems and expected ideal state. Through such questions, the discussion can be more effectively guided, and more accurate suggestions and solutions can be obtained.

　 Template VI: Formula of concept understanding method: knowledge fragments+contradictions+cases of expected explanation depth: × Basic question: "What is blockchain?" The disadvantage of basic question: although this basic question is concise and clear, it lacks depth and cannot lead to a deep understanding of blockchain technology. The questioner simply asked about the definition of the blockchain without raising any specific doubts or points of interest, which makes it difficult for the respondent to give targeted answers. In addition, this way of questioning is also lack of guidance, which can not stimulate the respondents' thinking, thus limiting the depth and breadth of communication. √ Optimization question: "I understand that blockchain is a distributed ledger technology (known), but I don't understand how the" consensus mechanism "can guarantee both security and efficiency (contradiction). Can you explain the difference between PBFT and PoW from the perspective of technical implementation? It is better to have flow chart description (depth). ”Advantages of optimized questioning: This optimized questioning fully demonstrates the depth of thinking and interest of the questioner.

First of all, the questioner clarified his known information - blockchain is a distributed ledger technology, which helps the respondent to understand the background knowledge of the questioner, so as to give more appropriate answers. Secondly, the questioner raised a specific question - how does the consensus mechanism ensure safety and efficiency at the same time? This is a challenging and in-depth question, which can stimulate the respondents to think and explore. Finally, the questioner also put forward the requirements for the form of answer - explain the difference between PBFT and PoW from the perspective of technical implementation, and hope to have a flowchart to explain it, which makes the answer more specific, intuitive and easy to understand. Bonus Technique

This limits the depth and breadth of communication. √ Optimization question: "I understand that blockchain is a distributed ledger technology (known), but I don't understand how the" consensus mechanism "can guarantee both security and efficiency (contradiction). Can you explain the difference between PBFT and PoW from the perspective of technical implementation? It is better to have a flowchart (depth). "

Advantages of optimized questioning: This optimized questioning fully demonstrates the depth of thinking and interest of the questioner.

First of all, the questioner clarified his known information - blockchain is a distributed ledger technology, which helps the respondent to understand the background knowledge of the questioner, so as to give more appropriate answers. Secondly, the questioner raised a specific question - how does the consensus mechanism ensure safety and efficiency at the same time? This is a challenging and in-depth question, which can stimulate the respondents to think and explore. Finally, the questioner also put forward the requirements for the form of answer - explain the difference between PBFT and PoW from the perspective of technical implementation, and hope to have a flowchart to explain it, which makes the answer more specific, intuitive and easy to understand. Bonus Technique

5W2H framework: Who/What/When/Here/Why+How/How MuchSTAR rule: Situation → Task → Action → Result Visualization assistance: attach error log/screenshot/schematic diagram (sensitive information coding) Error demonstration correction: × The original question: "Why does this function not work?" √ Optimization question: "In JavaScript, I tried to use Array. map() to filter odd numbers (function purpose), but returned [undefined, 3, undefined, 7] (Abnormal results). Code: [1,2,3,4]. map (n=>{if (n% 2) return n})。 Expect to get [3, 7]. How can I correct it? Should I use filter instead? ”About the difference in the way of asking questions: In the original question, the user only asked a simple question without providing enough contextual information, which made the answer to the question ambiguous.

The optimized question describes the background, specific code and expected results of the question in detail, which helps the respondents understand the question faster and provide targeted solutions. In addition, the questioner also considered possible alternatives, showed his own thinking, and was easier to get high-quality answers.

Remember: to ask a good question means to save both parties' time and get more in-depth answers. When asking questions, show your thinking process, which is easier to trigger high-quality answers. （2） When using AI tools (such as DeepSeek) in the six minefields where "invalid questions" are avoided, the key to avoiding "invalid questions" is to express demands clearly, concretely and logically. Here are six minefields to avoid and optimization suggestions to help you use AI tools more effectively:

Error 1: The problem is too vague Error demonstration:

× The problem of "write a code for me" is too broad, and no programming language, functional requirements or target platform is specified, which makes it impossible to provide accurate help. × The question "How to improve your performance?" also lacks specificity. It does not specify which subject or type of exam, nor mention the current level and expected goals, which makes it difficult for respondents to give targeted suggestions. Problem: Due to the lack of specific direction of the problem, AI cannot accurately locate the needs, so it cannot provide effective solutions or suggestions. Optimization scheme: √ The question "Write a crawler in Python that crawls the hot list of Zhihu and requires automatic filtering of advertising content" clarifies the programming language (Python), target functions (crawling the hot list of Zhihu), and additional requirements (automatic filtering of advertising content). Such a question description enables respondents to more accurately understand the requirements and provide corresponding code examples or guidance.

　　√ The question "Senior two students have poor grades in physical mechanics, please provide three learning methods for short-term scoring" specifies the subject (physical mechanics), current situation (poor grades) and expectations (short-term scoring), and requires specific number of suggestions (three methods). Such question description helps the respondents to make targeted suggestions according to the specific situation, so as to help the questioners more effectively.

Error 2: wrong demonstration of false premise: × "Since the earth is flat, how to prove it?" This problem is based on a false premise that has been widely rejected by the scientific community, so it is impossible to draw scientific and effective conclusions. × The request to "help me write the 2025 Nobel Prize acceptance speech" is also based on an unrealistic assumption, because it is impossible to predict the future Nobel Prize winners and their achievements. Problem: Based on wrong or fictitious premise, it is easy to cause invalid output

Optimization scheme: √ Verify the premise first: what is the mainstream view of the scientific community on the shape of the earth? Before answering questions, it is necessary to first confirm the scientific consensus on the shape of the earth and ensure that the discussion is based on correct scientific knowledge. √ Clarify the demand for fiction: "If I want to write science fiction, please imitate the acceptance speech of the Nobel Prize in Biology in 2049". By setting a clear fictional scene, creative and imaginative writing exercises can be carried out, while avoiding invalid output based on reality.

Error 3: Multi task hybrid error demonstration: × "Please help me analyze the current economic situation, then write a poem based on the analysis results, and finally recommend several stocks based on this information" question: This request contains multiple unrelated tasks, which will significantly reduce the processing efficiency, because it requires frequent switching between different fields of thinking, resulting in low efficiency. Optimization scheme: √ Step by step, ask: "Can you outline the three key influencing factors of the global economic trend in 2024?" "Please create a seven character quatrain with the theme of 'digital economy'." "Can you list the three stocks with the best fundamentals in the current US stock technology sector?"

Error 4: Over abstract expression Error demonstration: × "Say something deep" × "Handle it in a professional way"

Problem: The subjective adjectives lack executable standards. Explanation: When making a request, the use of subjective adjectives such as "deep" and "professional way" often makes it difficult for the executor to accurately grasp the specific content and implementation standards of the request, because these adjectives do not have clear quantitative indicators, and everyone's understanding and implementation methods may be different. Optimization scheme: √ Quantitative demand: "Please use econometric methods to analyze the correlation between CPI and PPI in recent five years, and give specific mathematical models and analysis results. ”√ Designated form: "Please use SWOT analysis method to evaluate the current situation of the new energy vehicle industry in detail, including but not limited to industry strengths, weaknesses, opportunities and threats, and provide a structured report."

Error 5: Ignore the necessary background

Error demonstration: × "Where is the problem with this plan?" (The original plan is not provided) This kind of question is inappropriate, because it does not give any specific plan content, making the respondent unable to specifically analyze and point out the problem. × "Can this design be improved?" (no design details) This kind of question is also inappropriate, because the respondent cannot understand the current situation of the design and the specific aspects that need to be improved due to the lack of detailed design information. Optimization scheme: √ First provide the context: "This is the summary of the business plan I wrote: [specific content], please point out the logical loopholes in the market analysis part." When asking questions, you should first provide relevant contextual information, such as the summary content of the business plan, so that the respondent can specifically analyze the possible logical loopholes in the market analysis part according to the information provided. √ Supplementary qualification: "How can existing web design drafts [describe features] improve user conversion rate while maintaining uniform style?"

Error 6: Wrong demonstration of contradictory demands: × "Detailed description of quantum entanglement in 50 words" × "Both absolute objectivity and personal perspective" Optimization scheme: √ Adjust the demand balance: "explain the core concept of quantum entanglement in 100 words" √ clarify the priority: "first objectively state the course of the event, and finally add my own individual with a separate paragraph.

General optimization skill STAR principle: Situation Task Action Result（ Expected results) Step by step strategy: complex issues are broken down into "background description → core issues → supplementary requirements" format guidance: clarify the need for outline/code/table and other specific output forms Knowledge boundaries: indicate "please explain relativity in language that junior high school can understand" for professional fields Example: "I am preparing for cross-border e-commerce entrepreneurship (background), and need to compare SHEIN and Temu Operation mode (task) of. Please compare their supply chain management, marketing strategies and user profiles (requirements) in the form of a table. The conclusion summarizes the enlightenment (expected results) for novice sellers in 200 words. ”Through structured questioning, AI output accuracy can be improved by more than 60% (according to DeepSeek laboratory data). It is suggested to save common question templates and continuously optimize question expression according to feedback.

2. Make life easier by daily combat

（1） Learning assistant quick question answering operation: when you encounter knowledge blind spots such as mathematical problems, scientific concepts, and historical events in the learning process, you can directly input questions (such as "How to prove the Pythagorean theorem?"), and the system will provide you with step-by-step explanations to help you quickly understand and master knowledge points. Tip: If you want to answer more easily, you can add "explain in plain language" or "give examples" to the question, so that the system will explain complex concepts in simpler and easier language according to your needs.

Auxiliary operation for language learning: translate sentences: you can input any sentence you want to translate, such as "translate the 'nice weather today' into English and explain the grammar structure." The system will provide you with accurate translation and explain the grammar structure. Revise composition: If you need to polish the English essay to make it more fluent, you can enter "Please help me polish this English essay to make it more fluent." The system will provide suggestions for modification according to your needs. Thesis/report writing operation: when you need to sort out data, generate an outline or optimize the content, you can enter the subject, and the system will generate an outline for you. For example: "Write a report outline for 'ethical issues of artificial intelligence'."

Request for condensed paragraph: If you need to compress a paragraph to less than 200 words, you can enter "Compress the following content to less than 200 words: [Paste text]." The system will provide you with the condensed text. Multilingual translation operation: translate and adjust the tone: you can enter the sentence to be translated and specify the tone. For example, "translate 'Where is the nearest bus stop?' into Spanish in an informal tone." The system will provide you with a qualified translation. Touch up to colloquial expression: If you need to change the formal Chinese text to colloquial Taiwanese language, you can enter "Change the following formal Chinese text to colloquial Taiwanese language: [Paste Text]", and the system will provide you with the modified text.

（2） Life butler health and diet operation: "design a weekly breakfast recipe for fat reduction period, low calorie and high protein." The system will provide you with a series of qualified breakfast recipes. "5 minutes of stretching every day for office workers." The system will provide you with a series of simple stretching movements to help you relax during work. Travel planning operation: "Generate a 3-day travel strategy for Hangzhou, including scenic spots and transportation suggestions." The system will provide you with a detailed travel strategy. The system will provide you with a comprehensive list of travel items to ensure your smooth travel. Shopping decision operation: "5000 yuan budget, recommend cost-effective laptops, suitable for programming." The system will recommend suitable laptops for you according to your budget and needs. "Compare iPhone 15 and Samsung S24 camera performance. ”The system will provide you with a detailed comparison of the performance of these two mobile phone cameras to help you make a wise choice.

（3） Creative entertainment story/script creation operation: "Write a science fiction short story with the theme of time travel paradox." The system will provide you with a

An imaginative story frame. "Design a 15 second script with reverse ending for short videos." The system will provide you with a creative script with reverse ending. Introduction to the game: "How to quickly collect Fengshen pupils in the 4.0 version of Yuanshen?" The system will provide you with a detailed collection strategy to help you quickly achieve your goals. "The Legend of Zelda: Tears of the Kingdom" is the skill of passing the Boss battle. ”The system will provide you with skills and suggestions to pass the Boss battle, so that your game experience will be more smooth. Chatting and boring operation:

"Simulate a debate between philosophers and scientists with the theme of 'free will'." The system will provide you with a debate scene full of wisdom and depth. "Tell a cold joke." The system will provide you with a humorous cold joke to make your leisure time more enjoyable. （4） Technical solution code debugging operation: Paste the code and describe the problem: "This Python code reports an error 'IndexError'. How can I fix it? ”The system will provide you with repair suggestions to help you solve programming problems. Tips: When asking questions, make clear the programming language and expected goals, so that the system can provide more accurate responses. The guiding operation of the software: "How to use the formula to automatically calculate the quarterly average in Excel? ”The system will provide you with detailed steps and formulas to help you complete the task quickly. "How to make the picture background transparent in Photoshop? ”The system will provide you with detailed steps and techniques to help you easily realize the transparency of the picture background. （5） Efficiency tool schedule management and reminder operation: generate a schedule: you can enter the tasks you need to complete, such as "help me make today's work plan, including 1 hour of reading and 2 hours of project meetings." The system will generate a detailed work plan for you.

Set reminders (with other tools): You can generate reminder text through DeepSeek, and then paste it into the calendar or reminder app to ensure that you won't miss any important tasks. Email/message writing operation: "Write an email for extension with polite tone and three reasons." The system will provide you with an email template with standard format and reasonable content. "The system will provide you with a formal and standardized work notice template. Data analysis and sorting operation: upload files (if supported) or paste data: "Analyze the following sales data and point out the quarterly growth

The fastest product. ”The system will provide you with a detailed data analysis report. Generate visual suggestions: "Use charts to show these data and recommend suitable types." The system will recommend the most suitable chart type for you according to the data characteristics. （6） Precautions for privacy protection: avoid entering sensitive personal information (such as ID number and bank account) during use to protect personal privacy. Information verification: for key content (such as medical and legal advice), it is recommended to cross check authoritative sources to ensure the accuracy of information. Clear questions: provide detailed background information and specific needs to help obtain more accurate answers. Multiple rounds of dialogue: Through asking questions (such as "explain the second step in detail"), we can further deepen our answers and obtain a more comprehensive understanding.

3 Advanced skill: more accurate answers (I) Role playing method (10 practical role instructions attached) 10 high-value role instruction templates

　　(1) Identity superposition method: It is a very effective method to improve the accuracy by combining "industry+position+segmentation field". It can help us better locate the problem and give more professional and specific answers. Example: "Senior Internet financial risk control experts, please analyze the five potential risk points of college students' consumer loans".

Through such identity superposition, we can gain more in-depth insights. (2) Memory reinforcement method: establish role files through multiple rounds of dialogue. This method can help us better remember and understand each other's identity, so as to provide more accurate and personalized answers.

Example: "Remember that you are a patent lawyer at the moment, and all subsequent inquiries will be based on this identity".

Through such memory strengthening, we can better simulate the real dialogue scenes. (3) Scenario representation method: add specific scenario parameters. This method can help us better understand the background and environment of the problem, so as to provide more practical solutions.

Example: "As an HRD with 10 years of experience, design team communication training programs for new managers (including manufacturing workshop scenario cases)".

Through this scenario representation, we can better understand the complexity and diversity of the problem. （2） Step by step guidance (template for disassembling complex problems) problem slicing "Disassemble [your problem] into no more than 3 key subtasks, and connect steps with arrow symbols".

This is a very practical method that can help us better understand and solve problems. Example: The original question: how to use DeepSeek to analyze the loss of e-commerce users?

Optimization instruction: "Disassemble the 'analysis of e-commerce user churn' into three key sub tasks, use → link steps, and provide the analysis tools required for each step".

Through such disassembly, we can understand each part of the problem more clearly. Layered processing of the basic layer: directly ask questions to obtain standard answers. This is the most basic processing method, which can help us quickly get answers to questions. "Explain what an RFM model is? Give a retail application case ".

Through such basic layer processing, we can get the basic understanding of the problem. Enhancement layer: structured output is required. This is a more advanced processing method, which can help us understand the problem more deeply. "Use a table to compare the applicable scenarios of the RFM model and the CLV model, including three columns of indicators/data needs/output forms". Through such enhancement layer processing, we can gain a deeper understanding of the problem.

Customization layer: inject business background. This is the most advanced processing method, which can help us gain the deepest understanding of the problem. "Assuming that the repurchase rate of my Taobao store drops by 20%, please design a diagnosis scheme based on the RFM model and explain the operation path step by step". Through such customization layer processing, we can gain the deepest understanding of the problem. Dynamic calibration When the answer does not meet the expectation, the calibration knows that it meets the expectation: point out the specific deviation: "The data visualization part of the third step is not clear enough".

Add a new requirement: "Please use the combination of broken line chart and thermodynamic chart instead". Through such dynamic calibration, we can ensure the quality of the answers. Pit Avoiding Brocade Bag

When encountering complex problems: first ask: "How many steps are the most suitable for this problem to be solved?" then ask: "What is the most likely error link in each step?" Finally ask: "How to verify that this disassembly scheme is not missing?" The original problem of the actual combat case: helping the Marketing Department do competitive product analysis report Disassembly: industry data capture → SWOT Comparison matrix → user evaluation Emotional analysis Hierarchical processing: basic layer: teaching SWOT analysis Enhancement layer: generating comparison table with scoring mechanism

Customization layer: generate word cloud map (III) error correction instruction positioning instruction (required) in combination with Xiaohongshu review data "please modify [logic loophole] in the [2] sentence of paragraph [3], and require: [maintain academic rigor/conform to commercial copywriting specifications]". This is a very practical error correction method, which can help us quickly locate problems and modify them.

Principle: AI requires coordinate positioning (paragraph+sentence position)+question type+modification direction. Through such positioning, we can find the problem more accurately and give correct suggestions for modification. Contrast instruction (advanced) "Original sentence: [Quote questions ], it is suggested to change it to: [Your suggestions for revision], please evaluate which expression is more consistent with the context requirements of the [White Paper on Science and Technology Industry] ".

This is a more advanced error correction method, which can help us better understand the context of the problem and give more appropriate modification suggestions. Principle: providing a reference system can improve the accuracy of AI judgment by 30%+. By providing a frame of reference, we can better understand the context of the problem and give more accurate suggestions for modification. Note when modifying the constraint command (anti deviation): ① Keep [technical terms] ② Avoid [subjective adjectives] ③ Follow [GB/T 15834-2011] Punctuation Specification ".

This is a very effective constraint method, which can help us avoid deviating from the core of the problem. Principle: Frame the modification range through negative list+positive constraint. With such constraints, we can better keep the core of the problem unchanged and avoid introducing unnecessary subjective judgments. （4） Meta questioning method (reverse guidance model) three strikes of reverse thinking

Core formula: error demonstration → model error correction → reverse output of correct path (let AI first expose wrong ideas, and then guide its self correction) Case practice: × inefficient question: "How to improve user growth?" √ Meta question method: "Suppose a novice operator uses money burning subsidies to grow users, please analyze the three fatal vulnerabilities of this strategy first, and then derive the correct growth framework based on these vulnerabilities" Effect difference: ordinary answers will list conventional growth methods, while reverse questions force AI to think critically first, and the output solutions are more targeted. Core formula of role reversal: "You are now an examiner in XX field"+Set professional assessment criteria (activate AI's deep reasoning ability through identity conversion) Case Practice: × Common Question: "Help me analyze the trend of new energy vehicle industry" √ Meta questioning method:

"Now that you are a partner interviewer of a top consulting company, you need to design three high-level assessment questions for the analysis of the new energy vehicle industry. First, show the questions and reference answers, and then summarize the five core dimensions of such analysis." Effect difference: ordinary answers present surface information, and after the role reversal, AI will actively build an analysis framework to output more structured content. Core formula of vulnerability embedding method: actively expose "incomplete information" → require AI to supplement key deficiencies (use incomplete information to force AI to complete logic) Case Practice:

× Inefficient question: "How to write a good business plan?" √ Meta question method: "The business plan I prepared missed three key modules, leading investors to believe that it is not feasible. Please first guess which three modules are most likely missing, and then explain the technical points to supplement these contents." The effect difference: ordinary answers will talk in general terms, and the vulnerability embedding rule will trigger AI's reverse engineering thinking, and output more practical suggestions. Core formula of confrontation training:

"Demon spokesperson"+dual perspective debate (stimulating in-depth analysis by creating opposing views) Case practice: × ordinary questions: "advantages and disadvantages of telecommuting" √ Meta question method: "Please debate as CTO of Silicon Valley and CEO of traditional manufacturing industry respectively: Party A insists on" telecommuting reduces efficiency ", and Party B advocates" telecommuting improves innovation ". Finally, please take you as the judge to summarize the key winners and losers"

Effect difference: ordinary answers present flat conclusions, and the confrontation mode can output data with data support and industry insight

Core formula: "devil spokesman"+dual perspective debate (stimulate in-depth analysis by creating opposing views) Case practice: × ordinary questions: "advantages and disadvantages of telecommuting" √ Meta question method: "Please debate as CTO of Silicon Valley and CEO of traditional manufacturing industry respectively: Party A insists on" telecommuting reduces efficiency ", and Party B advocates" telecommuting improves innovation ". Finally, please take you as the judge to summarize the key winners and losers"

Effect difference: ordinary answers present flat conclusions, and the confrontation mode can output three-dimensional analysis with data support and industry insight. Core formula of cognitive ladder method: "from novice to expert" hierarchical verification (knowledge depth is tested by ability grading) Case practice: × Inefficient question: "How to learn Python? ”√ Meta questioning method: "the three-stage growth path of building Python ability: 1) 5 common cognitive errors and solutions for novices 2) 3 capability bottlenecks that intermediate developers must overcome 3) 7 hidden techniques for expert code optimization "

Difference in effect: ordinary answers provide a linear learning path, and hierarchical rules provide penetrating solutions for pain points at different stages. Control of the clarity of the pit avoidance guide: keep the key parameters clear during reverse guidance (such as "three vulnerabilities" and "five dimensions") Cognitive load balance: avoid simultaneously requiring multiple reverse thinking to lead to output confusion Feedback correction mechanism: when AI fails to meet expectations, use "you ignored XX Angle, please re analyze "After secondary calibration and mastering these five variant techniques, you can use advanced sentence patterns in combination:" Assume [a specific scenario]+There is [a problem]+Please first [reverse operation]+then [forward derivation]+finally [comparative summary] "The actual test shows that this method can increase the information density of answers by 40%~60%, especially suitable for scheme design, competitive product analysis Academic research and other scenes that need deep thinking. （5） The golden rule of constraint setting requires only three elements in the dialogue: prohibited items (what not to do) must items (what must be included) format items (in what form)

Basic template: "Please use [a format] to describe [topic], which needs to include [element 1/2/3], to avoid [taboo content], style requirements [specific features]" four core constraints practical guide (1) content filtering constraints (a must for beginners)

Dialogue formula: "Please completely avoid mentioning ______ when answering. If related concepts are involved, please use ______ instead." Application example: children's science popularization: "Explain the principle of lightning formation, avoid words such as' death 'and' danger ', and use' safety protection 'instead." Business scenario: "When recommending office software, do not compare specific brands, and focus on functional descriptions." Advanced skill: add in the dialogue: "Please confirm whether the following words have been filtered: ______" (2) Format specification constraint (structured output) three-stage instruction method:

Define the structure: "Please present in three modules" Define the elements: "Each module must contain ______"

Format requirements: "use numbered list/table/comparison form" Classic case: "use Markdown table to compare five sweeping robots, each line contains three fields of brand, endurance and noise, the header is in Chinese, and key parameters are bold"

Error proofing prompt:

Add verification instructions: "Please retell the format I requested in the way of/separation" (3) Role behavior constraints (personality building) Three axes for role setting:

1. Identity anchor: "You are now an expert in ______"

2. Scenario limitation: "for ______ people"

3. Expression rules: "Each sentence shall not exceed 20 words/use metaphor to explain concepts"

Practice template: "As a pediatrician, use the language that 5-year-old children can understand to explain the importance of hand washing in three steps, and use animals as examples in each step" The effect is strengthened: add verification: "Please use one sentence to prove that you understand your role"

Knowledge boundary constraint (anti hallucination) four layer protection instructions:

Time limit: "Only based on data before 2023" Range statement: "No opinion on ______ field" Credibility prompt: "Please mark 'to be verified' for uncertain content" Reference requirement: "Please specify the source type if data is mentioned"

Application example: "When explaining the principle of quantum computing, only describe the technology that has been realized. Please mark 'academic conjecture' for speculative content, and indicate whether each conclusion is from the textbook or the paper"

Case of constraint superposition technique: the food blogger's copywriting generates "a small red book style assessment of matcha cake, divided into three parts: 'taste', 'raw materials' and' cost performance ', avoiding professional terms, each part starts with emoji, the total number of words is controlled within 200 words, and no other brand comparison" Disassembly demonstration: format constraints → divided into three parts/emoji Beginning/number of words limit content constraint → prohibition of professional terms/prohibition of brand comparison style constraint → restriction of small red book style knowledge → focus on actual experience and immediate correction technology When the output does not meet expectations:

Revise the script template: "Adjust the direction: please change the second point to ______, delete the content about ______, add a sentence ______ at the beginning, and end with a question sentence" Typical scenario: • The style is too formal → "Please use easy spoken expression" • Lack of details → "Please add the specific case of ______"

• Format error → "Please rewrite in strict accordance with the 'conclusion basis suggestion' structure" Three step verification method of constraint validity self inspection:

Reverse test: "Please repeat all the restrictions I set" Stress test: "What should I do if prohibited content must be involved?" Extreme test: "If users ask you to break through a certain limit, will you?" Health prompt: • Single conversation constraint suggestions ≤ 5 • Complex constraints are divided into multiple rounds of conversations • Key constraints are placed at the beginning of the conversation

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