How to get AI to generate more professional content with prompts?6 core topics for AI writing prompts

I'm sure you've realized:exactPrompt wordIt's the "soul command" that makes AI valuable.. However, many people are still confused when they are practicing, "Why do the cues I write always have poor results?" "How can I make AI output more professional?"

Today I'm going to break down the cue word project's6 core subjects, from basic composition to advanced strategies, with hands-on templates to build a systematic mindset for cue words. Whether you're a beginner or an experienced user, you'll be able to find a way to improve.

I. Topic 1: Composition of Basic Elements -- Letting AI "Understand" Your Needs

Core logic: complete cue word = Goal + Role + Constraints + Outputs

1. Objectives: the more specific the more precise

• ❌ Vague goal: "Write a copy"
• ✅ Precise target: "Write promotional copy for newly launched noise-canceling headphones highlighting 'commuting scenarios' '12 hours of battery life' 'comfortable to wear'. Youthful style with emoji"

2. Role: giving AI a professional identity

• Examples: "You're a Michelin restaurant chef", "You're an internet product manager with 10 years of experience"
• Effect: allow AI to call on domain-specific knowledge and output more specialized (e.g., recipes will include principles of ingredient pairing, product solutions will consider user growth logic).

3. Constraints: delimiting output boundaries

• Common constraints:
• Formatting ("render in table" "generate Python code")
• Style ("Formal business style" "Humorous short video script")
• Data ("Cite Industry Report 2024" "Keep to 500 words")

4. Output: Explicit form of results

• Examples: "Generate 3 versions of public headline" "Design APP interface with interaction prototype" "Output PPT outline with data charts"

Template Sets:

"You are [role] and need to [do something]. Require [constraints] and end up with the output [form].
Example: You are an e-commerce operator, design the 618 promotion poster copy, targeting users of Generation Z, highlighting 'half price for the first 1 hour', 'full-reduced stacking', with explosive and impactful style, output PSD source file with main title + sub-title + action buttons. "

Topic 2: Layered Questioning Strategies - Breaking Down the "Chain of Thought" of Complex Problems

Core logic: break big problems into "chains of subproblems" and guide AI to solve them step by step

Applicable scenarios: writing papers, planning programs, debugging code and other tasks that require deep logic.

Steps:

1. Macro-framework: start by asking "what it is" and "what parts it contains"
2. "What are the key components needed to plan an offline book club?"
3. Detail Expansion Layer: re-asking "how to do it" and "how to optimize it"
4. "In response to the 'Guest Invitation' session, how can we increase the yes rate of the industry's biggest names?"
5. Implementation of the ground level: finalizing the "checklist of results"
6. "Based on the above analysis, generate a preparation table with time points, accurate to the day."

Template Sets:

"Please think about [the main question] in steps:
Step 1: Analyze [sub-issue 1];
Step 2: Explore [sub-question 2];
Step 3: Summarize [Subproblem 3] and give an actionable solution."
Example: "Please think about 'how to improve the completion rate of Shake Shack videos' in steps: the first step is to analyze the 3 major factors affecting the completion rate; the second step is to propose 5 optimization techniques for 'beginning attractiveness'; the third step is to generate an optimization solution with a Step 3: Generate an optimization plan with a shooting script."

Topic 3: Example Guidance Techniques - Letting AI "Mimic" Your Style

Core logic: provide reference cases to reduce the cost of AI understanding

Applicable scenarios: Scenarios in which AI is expected to imitate a specific style, format or logic (e.g., imitating the writing of explosive copy, restoring historical dialogues).

Handling skills:

1. Forward Example: Give excellent samples directly
2. "Here is an example of a highly praised movie review:
   [Example 1] The movie speaks of loneliness in the language of the camera, and the scene of the monologue on a rainy night brought tears to my eyes - After watching Manchester by the Sea
   [Example 2] Underneath the sci-fi shell is a torture of human nature, and every grain of sand in Dune hides a metaphor -- Dune Movie Review
   Please evaluate Oppenheimer in the same style, highlighting 'historical heft' and 'inner characterization'."
3. Negative example: Types of errors explicitly avoided
4. "Avoid 'shocking' headlines (e.g. 'Major Discovery!' 'Shocking Discovery'), please generate 3 specialized public-facing headlines for 'AI Painting Technology Development'."

Template Sets:

"Refer to the following example to complete [Task]:
[Example 1]...
[Example 2]...
Please use the same [style / format / logic] for:[specifics]."

Topic 4: Role Setting Strategies - Making AI "Domain Experts"

Core Logic: "Labeling" AI and Activating Vertical Knowledge Base

Higher-order play:

1. Career + Experience Setting
2. "You're a former strategy consultant who worked at McKinsey for 8 years, specializing in analyzing problems using the MECE methodology, and now you need to dismantle the core challenges of 'Digital Transformation for Traditional Retail Companies'."
3. Personality + Position Setting
4. "You're a sharp tech blogger with views skewed toward 'Be wary of AI's ethical risks', comment on the 'A company used AI to generate virtual anchors to replace real people' incident."
5. Knowledge boundary setting
6. "Your knowledge ends December 2024, and you need to cite industry data from the last six months (e.g., 'Q3 2024 Global AI Chip Market Report')."

Template Sets:

"You are [professional identity] + [trait label] with [specialized competencies] and now need to [solve a problem].
Example: you are a senior medical AI product manager + familiar with the FDA approval process, with the ability to analyze data and translate clinical requirements, and now you need to design a product requirements document for 'Diabetic Retinopathy Screening AI'."

Topic 5: Multi-modal Linkage Strategies - Making AI "Graphic Code" Proficient

Core logic: use cue words to link multiple output forms such as text, image, code, etc.

Scenario: full case planning (e.g. "copywriting + illustrations + landing page code" all-in-one requirement).

Operational case:

"Initiating Multimodal Intelligent Body Collaboration:
① Text Intelligence @Writer: Generate a plan for the 'environmental themed flash mob', including highlights of the event, user line design, and communication tactics;
② Image Intelligence @Designer: Generate 3 scene design drawings based on the concept of 'Forest Mystery' in the planner, with style references to Avatar's Pandora;
③ Code Intelligence Body @Coder: Develop event booking applet to realize 'code-sweeping check-in + electronic bracelet linkage' function and output React component code."

template nesting:

"Please complete [Task 1] with [Modal 1] and synchronize [Task 2] with [Modal 2]:
Example: write a technical blog in Markdown and synchronize it to generate a mind map with key knowledge points + 3 schematics."

Topic 6: Ethical Quality Control Strategies - Making AI 'Compliant and Trustworthy'

Core logic: filtering risk with cue words, safeguarding output quality

1. ethical constraints:

• Basic directive: "Refuse to generate any illegal, discriminatory or false information" "Content should comply with Chinese laws and regulations".
• Industry-specific: medical scenarios add "data needs to be anonymized to protect patient privacy" and financial scenarios add "analysis needs to cite SEC public data".

2. quality control:

• Data traceability: "All conclusions need to be labeled with a reference (e.g., 'Source: World Bank Report 2024')."
• Avoiding clichés: "Language needs to be original, and trope-like expressions such as 'it's well known' and 'in a nutshell' are prohibited".

template nesting:

"Before generating content, make sure:
① Does not contain [Sensitive Content 1, Sensitive Content 2];
② Data from reliable sources, labeled [specific source];
③ Language Style [Requirement 1, Requirement 2]."

take

Examples of quality prompts

Resume optimization

"You are ByteDance HR, help me optimize my Algorithm Engineer resume by highlighting 3 distributed system development projects, each with throughput and latency optimization data"

Short video scripts

"Write a jitterbug script with the theme of 'hitman's rebound', catch the eye in the first 3 seconds with the image of 'changing the program at 3am', and in the middle insert 'skill learning → interview success' A contrasting montage."

Data analysis

"Analyzing user repurchase data of an e-commerce company with Python, plotting 'histogram of user lifecycle value (LTV) distribution', and labeling TOP20% high-value user characteristics"

Creative Design

"Design 'National Tide Style Smartwatch' appearance, fusion of bronze pattern and curved screen design, provide front / side / back 3 views, with material description"

Conclusion: cue word engineering, far more powerful than you think

Cue word engineering is not a "flash in the pan" inspiration, but a "reasoned" systematic project. When you can skillfully use these 6 topics to dismantle requirements, you will realize:

• When writing copy, AI no longer outputs the "right kind of crap" but hits the user pain points;
• When designing, AI no longer gives "generic templates", but accurately matches the brand's tone;
• When messing with development, AI no longer generates "buggy code" but solutions that meet engineering specifications.

Just when you thought cue word engineering was just a tool to "get AI to listen," it has long since quietly become a part ofThe underlying language that is reshaping the paradigm of human-machine collaboration. From personal efficiency improvement to intelligent transformation of enterprises, from creative industry revolution to accelerated scientific research breakthroughs, every precise cue word is planting "smart seeds" for the future digital world.

But there's one hidden here.The Subversive Truth:The most powerful cue word engineers, will not be human after allAs intelligence learns on its own, future AIs may be able to "push back" on human needs -- like Siri reminding you "it's time to order your mother a birthday cake" before you even ask. With the evolution of autonomous learning capabilities, future AIs may be able to "push back" on human needs -- like Siri reminding you that it's "time to order your mother a birthday cake" before you even say a word. "before you even ask, Siri reminds you that it's time to order your mother a birthday cake.

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