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Many people's first impression of AI is a chatbot - it's fun to talk to, but after a few conversations it gets boring. This is because you treat it as a toy rather than a tool. The real value isn't in chatting with AI, but in using AI to solve specific problems - like writing emails, fixing code, organizing meeting notes, analyzing data - these are areas where AI can actually save you time. The goal of this chapter isn't to list all possible application scenarios, but to give you a framework for finding AI use cases, and then let you experience how to use AI through a few typical scenarios. > The value of AI isn't in what it can do, but in how much time it can save you. Before each use of AI, first clarify: What problem do I want to solve? * * * ## Writing and Content Creation This is one of the most mature and easy-to-get-started application scenarios for AI. As long as it involves text, AI can almost always help. ### Article Writing and Polishing AI isn't here to write a perfect article for you, but to help you quickly turn ideas into words. You provide the viewpoints and structure, and AI is responsible for organizing language and enriching details. Here are several commonly used writing Prompt templates: > **Template 1: Article Outline Generation** > > I want to write an article about , targeting . Please help me generate a logically clear outline, including: 1. A compelling opening 2. 3-5 core points 3. A simple example for each point 4. A persuasive closing Topic: Target audience: [e.g., newcomers in the workplace, tech managers, entrepreneurs] > **Template 2: Article Polishing** > > Please help me polish the following text, keeping the core meaning unchanged, but making it more . Style options: more concise, more professional, more conversational, more impactful, more logical Requirements: 1. Keep the original meaning, don't add new information 2. Make sentences more smooth and fluent 3. Remove redundant expressions Text to polish: > **Template 3: Style Conversion** > > Please rewrite the following content into a version. Target styles: report version for leaders, popular science version for beginners, short version for social media, formal email version Original text: ### Marketing Copy Generation Writing copy is AI's strength - it can quickly generate multiple versions to help you find the best expression. | Scenario | Applicable Tools | Typical Prompt | Expected Effect | | --- | --- | --- | --- | | Product Feature Extraction | ChatGPT, Claude | I have a , main functions are , target users are . Please help me extract 3 core selling points, each expressed in one sentence. | 3 clear and powerful feature descriptions | | Social Media Copy | Any LLM | I want to promote [product/service] on social media, please help me write 5 versions of copy in different styles, each no more than 100 words, with appropriate emojis. | 5 ready-to-use social media posts | | Email Marketing Subject Lines | Any LLM | I'm writing a promotional email with the subject , please help me come up with 10 possible titles, divided into three categories: "direct", "curiosity", and "discount". | 10 email subject lines in different styles | | Landing Page Copy | ChatGPT, Claude | Please help me write a landing page copy structure for , including: title, subtitle, 3 core values, FAQ. | Complete landing page copy framework | ### Email and Report Writing Office workers write emails and reports every day - this is the scenario where AI can save the most time. > **Email Writing Template** > > Please help me write a . Recipient: [recipient's role, e.g., leader, client, team member] Core information: [what you want to say, listed in bullet points] Expected action: Tone requirements: [formal/friendly/concise/detailed] Reference information: [background info, e.g., previous conversation, related data] Here's a practical example: > **Practical Email Prompt** > > Please help me write an email. Recipient: All project team members Core information: - The project review meeting originally scheduled for Friday has been moved to Wednesday next week at 2 PM - The meeting room remains unchanged, still 302 - Please prepare a 5-minute progress report - If you have special circumstances and cannot attend, let me know by noon tomorrow Expected action: Please reply to confirm if you can attend Tone requirements: Formal but friendly, not too stiff Reference information: This is the 3rd review meeting for the tutorial project AI-generated content is just a draft - you need to adjust the details based on actual circumstances. But at least you don't have to start from scratch. ### Practical Example: From Idea to Finished Product We use a complete example to demonstrate how to write a technical blog using AI: > **Step 1: Generate Outline** > > I want to write an article about "How AI Helps Programmers Improve Efficiency", targeting developers who are just starting to explore AI. Please help me generate an outline including: 1. Start with a programmer's daily pain point scenario 2. 3 core application scenarios (code completion, bug debugging, code refactoring) 3. A specific example for each scenario 4. Give practical action suggestions at the end > **Step 2: Write Section by Section** > > Please help me write the opening section, using a programmer's daily pain point scenario to introduce the topic. Requirements: - Start with a specific story, not vague - Make the scenario realistic so programmers can relate - 200-300 words Reference scenario: Monday morning, programmer Xiao Wang discovers a bug in the code he wrote last Friday, spent the whole morning trying to find the cause, then remembers he can use AI to assist with debugging... > **Step 3: Overall Polishing** > > Please help me review the entire article and do the following polishing: 1. Make transitions between paragraphs more natural 2. Explain technical terms in more accessible ways 3. Ensure consistent article style 4. Check for any typos or awkward sentences Full article: * * * ## Code-Assisted Development AI is changing the way programmers work - not by making programmers unemployed, but by allowing programmers to focus on more valuable things. ### Code Generation and Explanation Writing repetitive code, checking documentation, writing boilerplate code - these are things AI is best at. | Scenario | Applicable Tools | Typical Prompt | Expected Effect | | --- | --- | --- | --- | | Writing Boilerplate Code | GitHub Copilot, Cursor | Please help me write a Python function to read a CSV file and count the data type of each column, with comments, exception handling, and return the statistical results. | A complete, usable function | | Technology Selection Comparison | ChatGPT, Claude | I'm working on a , torn between and , please help me compare from four dimensions: performance, learning curve, ecosystem, and applicable scenarios. | Structured technology comparison analysis | | Code Explanation | Any LLM | Please help me explain what this code does, line by line, then give an overall summary. Code: | Clear code explanation | | Adding Comments | Any LLM | Please help me add appropriate comments to this code, focusing on explaining the design approach and key logic, don't add meaningless comments to every line. | Code with comments | ### Bug Debugging and Fixing Asking AI first when encountering a bug - this has become a habit for many programmers. > **Debugging Prompt Template** > > I encountered a bug, please help me analyze possible causes. Phenomenon: [describe what happened, not what you think is wrong] Expected result: Actual result: Related code: Error information: Already tried: [troubleshooting steps you've already taken] Key principle: Tell AI what happened, not "I think it's wrong in this area." If you directly say "I think it's a database problem," AI might follow your line of thinking and miss the real cause. ### Code Refactoring and Optimization AI can help you turn "working code" into "good code." > **Refactoring Prompt Template** > > Please help me refactor this code with the goals of: 1. Improving readability 2. Reducing duplication 3. Better naming 4. Adding necessary error handling Requirements: - Keep functionality completely unchanged - Provide refactoring explanation: what you changed and why Original code: ### Usage for Non-Programmers You don't need to be a professional programmer to use AI to write some simple code to improve efficiency. For example: ## Example # ============================================ # Using Python to Call AI API for Document Summarization # This example demonstrates how to automatically shorten long documents # ============================================ import requests import json def summarize_text_with_ai(text: str, api_key: str) ->str: """ Use AI API to summarize long text