Unlike programming languages or search engines, AI doesn't require specific keywords, operators, or formatting. Just explain what you need in plain, conversational language.
Frequently Asked Questions
Common questions about AI, prompting, and getting the most from this resource.
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Getting Started
New to AI? Start here with fundamentals.
Prompting Methods
Questions about CRISP, COSTAR, and other frameworks.
Limitations & Safety
Understanding what AI can and cannot do.
Code Security
Security practices for AI-assisted development.
About Praxis
Questions about this resource.
Natural Language
Why you don't need special syntax.
Understanding Natural Language AI
Key Insight
AI assistants are designed to understand and respond to natural language—the same way you'd talk to a colleague or friend. You don't need special syntax, keywords, or formatting.
You Don't Need Special Syntax
Example: Instead of complex syntax, simply say "Help me write an email to my team about the project deadline."
Techniques Are Training Wheels
Methods like CRISP and COSTAR help you learn what information to include, not how to format it. Once you understand what makes a good prompt, you can communicate naturally.
Goal: Internalize the principles, then let go of the rigid structure.
Context Matters More Than Format
AI responds better to clear context and specific details than to perfectly structured prompts. A conversational prompt with good information will outperform a rigid template with vague content.
Focus: Learn what information AI needs, then communicate it however feels natural to you.
Getting Started
New to AI? Start here with the fundamentals.
What is a prompt?
A prompt is simply the text you send to an AI assistant. It can be a question, instruction, request, or any combination. The quality of your prompt directly influences the quality of the AI's response.
Users who learn to provide clear context and specific details tend to see significantly better outcomes from AI interactions.
Learn more about prompts →Which AI should I use?
The techniques taught here work with any modern AI assistant, including ChatGPT, Claude, Gemini, Copilot, and others. Each has slightly different strengths, but the fundamentals of good prompting are universal.
The principles of effective human-AI communication transfer across different AI systems with minimal adaptation.
Do I need technical skills to use AI effectively?
No. AI assistants are designed to understand natural language—the same way you'd communicate with a person. You don't need coding skills, special formatting, or technical knowledge. Just clear communication.
Most successful AI users attribute their results to clear communication rather than technical expertise.
Where should I start learning?
We recommend starting with Prompt Basics to understand core concepts, then moving to the CRISP Framework as your first framework. From there, explore other methods based on your needs.
View frameworks →Prompting Methods
Understanding the frameworks and when to use them.
| Method | Best For | Complexity | When to Use |
|---|---|---|---|
| CRISP | Everyday tasks | Beginner | Quick requests, simple tasks |
| CRISPE | Creative work | Beginner+ | When examples help clarify output |
| COSTAR | Professional content | Intermediate | Specific tone/audience needs |
| ReAct | Complex problems | Advanced | Multi-step reasoning tasks |
| Flipped | Discovery | Any level | When you're not sure what you need |
Which prompting method should I use?
CRISP is great for everyday tasks and quick requests. CRISPE adds examples for creative work. COSTAR is ideal for professional content with specific tone and audience. ReAct works best for complex, multi-step problems. Flipped Interaction is perfect when you're not sure what you need.
Compare all methods →Do I have to memorize these frameworks?
No. The frameworks are learning tools to help you understand what information AI needs. Once you internalize the concepts, you'll naturally include the right details without consciously following a structure. Think of them as training wheels.
Can I combine different methods?
Absolutely. The methods aren't rigid rules—they're guidelines. Feel free to take elements from different frameworks based on what your task needs. Many effective prompts blend concepts from multiple methods.
What's the difference between CRISP and CRISPE?
CRISPE adds an "Example" component to the CRISP framework. This is particularly useful for creative tasks where showing the AI an example of what you want is more effective than describing it. It enables few-shot learning.
Learn CRISPE →AI Limitations & Safety
Understanding what AI can and cannot do safely.
Critical Understanding
AI systems generate responses based on patterns in training data. They can produce incorrect information with high confidence. Always verify important information from authoritative sources.
What is a hallucination?
A hallucination is when AI generates information that sounds plausible but is actually incorrect or made up. This includes fake citations, invented statistics, fictional events, or confident statements about things the AI doesn't actually know.
Hallucinations are a common occurrence in AI responses, varying based on the domain and complexity of the question.
Practice spotting hallucinations →Can I trust AI for medical, legal, or financial advice?
No. AI should never replace professional advice in high-stakes domains. It can help you understand concepts, prepare questions, or organize your thoughts, but critical decisions about health, legal matters, and finances require qualified human professionals.
Health and professional organizations emphasize that AI tools are assistive technologies, not replacements for licensed practitioners.
Learn about AI safety →Is my data safe when using AI?
Assume that anything you type into an AI system could be stored or used for training. Never share passwords, personal identifiers, confidential business information, or sensitive data. Check each AI provider's privacy policy for specifics.
Why does AI sometimes give wrong answers confidently?
AI doesn't "know" things the way humans do. It predicts likely text patterns based on training data. When it lacks information or makes errors, it doesn't have uncertainty signals like humans do. This is why verification is essential—confidence doesn't equal accuracy.
AI & Code Security
Critical security and privacy considerations for AI-assisted development.
Security Warning
Using AI to write code without understanding security practices can expose your applications to serious vulnerabilities, data breaches, and compliance violations. Always review AI-generated code with security in mind.
Why is security critical when using AI for coding?
AI models are trained on vast amounts of code—including code with security flaws. They can inadvertently reproduce vulnerabilities like SQL injection, cross-site scripting (XSS), insecure authentication, or improper data handling. AI doesn't inherently understand security context or your specific compliance requirements.
The risk is real: A single vulnerability in production code can lead to data breaches, financial loss, legal liability, and damaged reputation.
What data should I never share with AI coding assistants?
Never paste or reference the following in AI prompts:
- API keys, tokens, or credentials of any kind
- Database connection strings or server configurations
- Personal Identifiable Information (PII) from users or customers
- Proprietary business logic or trade secrets
- Production data—use anonymized or synthetic data instead
- Security configurations or firewall rules
Assume anything you share could be stored, logged, or used for model training.
How do I review AI-generated code for security?
Always treat AI-generated code as untrusted input that requires thorough review:
- Input validation: Does the code sanitize and validate all user inputs?
- Authentication: Are credentials handled securely? No hardcoded secrets?
- Data exposure: Could this code leak sensitive information in logs, errors, or responses?
- Dependencies: Are suggested packages/libraries reputable and actively maintained?
- Permissions: Does it follow the principle of least privilege?
Use automated security scanning tools (SAST/DAST) as an additional layer of review.
What are the privacy policies I should understand?
Before using any AI coding tool, understand these key privacy considerations:
- Data retention: How long is your input stored? Is it deleted after the session?
- Training usage: Can your code be used to train future models?
- Third-party sharing: Is your data shared with other companies?
- Compliance: Does the service meet your regulatory requirements (GDPR, HIPAA, SOC 2)?
- Enterprise vs. consumer tiers: Business plans often have stronger privacy guarantees
Many organizations require approved AI tools and have specific policies for their use. Check with your security team.
What are the real-world risks of insecure AI-generated code?
The consequences of deploying vulnerable code are severe and real:
- Data breaches: Exposed customer data, financial information, or health records
- Malware injection: Vulnerabilities exploited to install ransomware or backdoors
- Supply chain attacks: Compromised dependencies affecting downstream users
- Compliance violations: Fines and penalties for GDPR, HIPAA, PCI-DSS violations
- Reputational damage: Lost customer trust that takes years to rebuild
- Legal liability: Lawsuits from affected parties
Security is not optional—it's a fundamental responsibility of anyone writing code.
What security practices should I always follow?
When using AI for any coding task, make these practices non-negotiable:
- Never copy-paste code blindly—understand every line before using it
- Use environment variables for all secrets and configuration
- Implement proper error handling that doesn't expose system details
- Follow OWASP guidelines for your platform (Top 10, ASVS)
- Keep dependencies updated and monitor for vulnerabilities
- Use version control and code review processes
- Test security before deployment—not after an incident
About Praxis
Questions about this resource and how it was built.
Is Praxis really free?
Yes, completely free. No account required, no premium tiers, no ads, no tracking. We believe AI skills should be accessible to everyone, regardless of budget.
Does this site use AI?
Absolutely! In a very real way, this entire site exists because of AI and thrives on it. The content, methodologies, and tools were developed in collaboration with AI assistants. Every page reflects the power of human-AI partnership.
However, the site itself runs without sending your data to external AI services. All interactive tools work locally in your browser—nothing you type is transmitted anywhere. This lets you learn and practice without privacy concerns or needing an AI account.
We practice what we preach: use AI as a powerful collaborator while being mindful of security and privacy.
Who created Praxis?
Praxis was created by Basiliso (Bas) Rosario with the mission of demystifying AI and making effective prompting skills accessible to everyone.
Learn more about the founder →How can I provide feedback or suggestions?
We'd love to hear from you. Reach out via the contact information on our About page with your thoughts, suggestions, or questions.
Contact us →Ready to Learn?
Start with the basics or test your knowledge with our readiness quiz.