People often try tools like ChatGPT, Claude, or Gemini expecting a perfect answer on the first try. When the result is poor, they think AI doesn't work. The most common cause is simple: the prompt is too vague, lacks context, or doesn't specify the output format.
> Tip from KP Solutions: If AI responds poorly, in most cases the problem isn't the AI but the unclear prompt. First improve the prompt, then judge the result.
1. How LLM Models Work (Simply)
An LLM (Large Language Model) doesn't read text like a human. It works with language patterns and predicts what answer best fits your prompt and context. That's why prompt quality is crucial.
Think of AI as an assistant who is fast but needs precise instructions. When you write "make this better," the model doesn't know whether to shorten the text, make it more formal, translate it, or prepare an email.
2. Choosing the Right Model
Not every model is for everything. The choice depends on the task type:
| Task Type | Recommended Model |
|-----------|-----------------|
| General text, emails, summaries | GPT-4o, Claude Sonnet |
| Analytical tasks, code | Claude Opus, GPT-4 |
| Creative content | Claude, Gemini |
| Quick answers, brainstorming | GPT-4o-mini, Gemini Flash |
3. Four Most Common Prompt Mistakes
Mistake 1: Too General
❌ Weak: "Write something about marketing."
✅ Good: "Write 5 specific Instagram marketing tips for a small café in Bratislava. Format: numbered list, max 2 sentences per tip."
Mistake 2: Missing Context
❌ Weak: "Rewrite this text."
✅ Good: "Rewrite this text for an IT manager newsletter. Tone: professional but not dry. Length: max 150 words."
Mistake 3: Unspecified Output Format
If you don't tell AI what format you want, you'll get a random format. Always specify: table, list, paragraphs, JSON, email...
Mistake 4: Everything in One Prompt
Break complex tasks into steps. First outline, then individual parts, finally revision.
4. The Good Prompt Formula
Universal formula: Role + Task + Context + Format + Constraints
Example: "You are an experienced copywriter (role). Write an introductory email (task) for a SaaS invoicing product (context). Format: subject + body max 100 words (format). Don't use clichés like 'revolutionize' (constraint)."
5. Five Prompting Techniques
Zero-shot
Direct prompt without examples. Works for simple tasks.
Few-shot
You provide 2-3 examples of desired output. AI learns the pattern and applies it.
Role Prompting
Assign AI a role: "You are a senior marketing strategist with 15 years of experience." Significantly improves response quality.
Chain-of-thought
Ask AI to think step by step. Ideal for analytical and logical tasks.
Self-check
Add at the end: "Check your answer, fix errors, and explain what you changed." AI self-corrects.
6. Ready-to-Use Templates
Document Summary: "Summarize the following text into 5 bullet points. Each point max 1 sentence. Use simple language understandable to non-experts."
Professional Email: "Write a professional email to [recipient] regarding [topic]. Tone: [formal/friendly]. Max [X] words. Include: greeting, main message, call to action, signature."
Option Comparison: "Compare [A] and [B] based on [criteria]. Format: table. Add a recommendation with reasoning at the end."
7. Pre-Send Checklist
- ☐ Is it clear what I want to get?
- ☐ Did I define a role for AI?
- ☐ Did I add sufficient context?
- ☐ Did I specify the output format?
- ☐ Did I set constraints (length, tone, language)?
- ☐ Is the prompt specific enough?
- ☐ Did I ask for a self-check?
Conclusion
The quality of AI output is directly proportional to the quality of your prompt. It's not magic, it's a skill that can be learned. Start with these principles and you'll see immediate improvement.