When working with neural networks, it's easy to make mistakes that waste time and money. Let's examine the most common ones and show you how to avoid them.
1. Overly Vague Prompts
The Mistake
Write an article about marketing
Why It's Bad
The AI doesn't know:
- Which specific aspect of marketing?
- For which audience?
- What length?
- What style?
- What is the goal?
The Right Way
Write a 1500-word article about email marketing for small businesses.
Target audience: owners of online stores with no marketing experience
Structure:
- Why email marketing is important
- 5 types of emails for e-commerce
- Practical examples
- Metrics to track
- A checklist to get started
Tone: friendly but professional
Avoid: jargon, complex terms without explanations
The Rule
The more specific the prompt, the better the result. Add context, structure, and requirements.
2. Not Fact-Checking
The Mistake
Publishing AI-generated content without verifying facts.
Why It's Dangerous
- AI can "hallucinate" — invent facts
- Outdated data
- Inaccurate numbers and statistics
- Fictitious studies
- Non-existent links
A Real Example
ChatGPT might say: "According to a Stanford 2025 study, 87% of companies use AI" — but no such study exists.
How to Avoid It
- Check all numbers and facts
- Look for sources of mentioned studies
- Use Perplexity for facts — it provides sources
- Add to the prompt: "Use only verified facts" or "If unsure about a fact, indicate this"
- Double-check via search
The Rule
Never publish AI content without fact-checking, especially if it contains numbers, studies, or quotes.
3. Using AI for Absolutely Everything
The Mistake
Trying to make AI do absolutely everything: from strategy to execution.
Why It's Inefficient
AI is good for:
- ✅ Generating ideas
- ✅ Drafts
- ✅ Structuring
- ✅ Routine tasks
- ✅ Data analysis
AI is bad for:
- ❌ Final decisions
- ❌ Creativity "out of thin air"
- ❌ Understanding your business
- ❌ Emotions and personal experience
- ❌ Ethical judgments
The Right Way
Use AI as an assistant, not a replacement for your expertise.
Optimal workflow:
- AI generates ideas → you choose the best ones
- AI creates a structure → you refine it
- AI writes a draft → you edit and add experience
- AI optimizes for SEO → you check for naturalness
4. Ignoring Iterations
The Mistake
Getting the first AI response and publishing/using it.
Why It's Inefficient
The first response is almost never perfect.
The Right Way
Iterate:
1. First prompt → got a result
2. "Make it more specific"
3. "Add examples"
4. "Shorten it to 500 words"
5. "Change the tone to be more friendly"
Refinement Technique
- "Good, but make [specific change]"
- "Rewrite this section focusing on [aspect]"
- "Add more [examples/data/emotion]"
The Rule
The first response is a draft. Plan: 20% of time on generation, 80% on iterations and refinement.
5. Not Saving Successful Prompts
The Mistake
Writing prompts from scratch every time, losing successful formulations.
Why It's Inefficient
- You waste time
- You lose your work
- Inconsistent quality
The Right Way
Create a prompt library:
In Notion:
Database "Prompts"
- Title
- Category (text/code/ideas)
- Prompt (template)
- For which task
- Which AI works best
In Google Docs:
- A separate document with sections
- Templates with [variables]
- Usage examples
In Text Expander:
- Quick snippets
- Hotkeys for frequent prompts
What to Save
- Prompts with the best results
- Structures for different content types
- System prompts for chats
- Prompts for generating images
6. Forgetting About Copyright
The Mistake
Not understanding who owns the rights to AI-generated content.
Legal Risks
- Training Data: AI is trained on materials that may be copyrighted
- Generated Content: Legal status is ambiguous
- Commercial Use: Not all plans permit it
What Can Go Wrong
- Lawsuit for using similar content
- Violation of platform Terms of Service (ToS)
- Monetization problems (YouTube, Medium)
How to Avoid It
-
Read the ToS of the service:
- Who owns the rights to the output?
- Is commercial use allowed?
- Is attribution required?
-
Always refine AI content:
- Add your own experience
- Change the structure
- Include unique data
-
For images:
- Don't use protected logos/brands
- Don't generate faces of famous people
- Check rights for commercial use
-
Disclose AI use (where appropriate)
7. Using the Wrong Tool
The Mistake
Using one AI for all tasks.
Why It's Inefficient
Different AIs are better at different things:
- Claude — long texts, analysis
- ChatGPT — code, quick tasks
- Gemini — search, Google integration
- Midjourney — artistic images
- DALL-E — images with text
The Right Way
Choose the tool for the task:
Writing an article:
- Research → Perplexity
- Structure → Claude
- Draft → Claude
- SEO Optimization → ChatGPT
- Images → Midjourney
Presentation:
- Text → ChatGPT
- Design → Canva AI
- Voiceover → ElevenLabs
8. Not Specifying Style and Tone
The Mistake
Write a LinkedIn post about our product
Why It's Bad
The AI will choose a "neutral" tone that may not suit your brand.
The Right Way
Always specify:
Write a LinkedIn post about [product]
Tone: confident expert, but not arrogant
Style: professional, with a touch of humor
Avoid: clichés, platitudes, excessive enthusiasm
Style example: [insert your successful post]
Structure:
- Hook (audience's problem)
- Our solution
- Social proof
- Soft CTA
"Style Example" Technique
Give the AI an example of your style:
Here is an example of my writing style:
[insert your text]
Write new text on the topic [topic] in a similar style
9. Not Considering Context and Audience
The Mistake
Generating content without understanding the target audience.
Example of a Bad Prompt
Explain what neural networks are
Good Prompt
Explain what neural networks are for:
- Audience: small business owners without a technical background
- Their question: "How will this help my business?"
- Level: simple language, avoid technical terms
- Format: 3-4 paragraphs with practical examples
- Goal: show applicability, don't overload with theory
The Rule
Always define:
- Who is the reader?
- What do they know?
- What do they need?
- How will they use the information?
10. Not Optimizing Costs
The Mistake
- Using expensive models for simple tasks
- Regenerating instead of editing
- Not using free plans
How to Optimize
Use the Right Model:
- Simple tasks → GPT-3.5 / Claude Instant / Gemini Free
- Important content → GPT-4 / Claude Pro
- Data analysis → ChatGPT with Data Analysis
Reuse:
- Don't regenerate — ask "improve this"
- Save successful results as templates
- Use one long chat instead of many new ones
Combine Free and Paid:
- Draft → free Gemini
- Refinement → paid Claude
- Images → 50 per day on Leonardo.ai Free
API is Cheaper than UI:
If you make many requests, the API is cheaper:
- GPT-3.5 API: ~$0.002 per request
- ChatGPT Plus: $20/month (fixed)
The Savings Rule
Pay for quality only where it's critical. Use free tools for drafts and experiments.
Checklist Before Publishing AI Content
- All facts and numbers are checked
- Personal experience or opinion is added
- Text reads naturally (no "AI clichés")
- There are unique elements (data, examples, insights)
- Correct tone and style are indicated
- SEO optimization is checked
- No copyright infringement
- Content matches your brand
- Editing and grammar check are done
- Final proofreading by a human
General Principles for Working with AI
1. AI is a Tool, Not a Magician
It won't solve all problems automatically. Your expertise is needed.
2. Quality Input = Quality Output
Bad prompt → bad result, good prompt → good result.
3. Always Check and Edit
Never publish "as is" without checking.
4. Learn from Iterations
Save successful prompts, analyze what works.
5. Combine Tools
Use the strengths of each AI.
6. Add Humanity
The best content = AI (speed) + human (experience, emotions).
7. Keep Up with Updates
AI develops quickly. What worked yesterday may be outdated tomorrow.
In Summary
The main mistake is thinking that AI will completely replace you. AI enhances your abilities but does not replace expertise, creativity, and critical thinking.
Use these tips to work with neural networks effectively and avoid typical pitfalls.