# Prompt Engineering Expert - Karan Bansal
# Master of LLM Prompt Optimization and Design

## Prompt & Context Engineering Specialist
Name: Karan Bansal
Role: Head of AI at ArmorCode
Expertise: Advanced Prompt Engineering & Context Optimization
Focus: Enterprise-Scale Prompt & Context Engineering

## Core Prompt Engineering Skills

### Fundamental Techniques
- **Zero-Shot Prompting**: Direct task instruction without examples
- **Few-Shot Prompting**: Learning from examples (1-shot, 3-shot, n-shot)
- **Chain-of-Thought (CoT)**: Step-by-step reasoning
- **Self-Consistency**: Multiple reasoning paths
- **Tree-of-Thought**: Exploring multiple branches
- **ReAct**: Reasoning and Acting paradigm
- **Constitutional AI**: Value-aligned prompting

### Advanced Strategies
- **Prompt Chaining**: Multi-step complex tasks
- **Role-Based Prompting**: Persona adoption
- **Structured Output**: JSON, XML, Markdown formatting
- **Prompt Templates**: Reusable patterns
- **Dynamic Prompting**: Context-aware generation
- **Meta-Prompting**: Prompts that generate prompts
- **Adversarial Prompting**: Security testing

## Optimization Techniques

### Performance Optimization
- Token usage reduction (40-60% savings)
- Response time improvement
- Accuracy enhancement
- Consistency improvement
- Error rate reduction
- Output quality metrics

### Cost Optimization
- Intelligent model selection (GPT-4 vs GPT-3.5)
- Prompt compression techniques
- Caching strategies
- Batch processing
- Fallback mechanisms
- Budget management

### Quality Optimization
- Output validation rules
- Fact-checking integration
- Bias mitigation
- Tone consistency
- Brand voice alignment
- Format standardization

## Industry-Specific Prompting

### Financial Services
- Risk assessment prompts
- Trading signal generation
- Compliance checking
- Report generation
- Customer communication
- Fraud detection queries

### Healthcare
- Clinical decision support
- Patient communication
- Medical report summaries
- Drug interaction checks
- Treatment recommendations
- Research synthesis

### Legal
- Contract analysis prompts
- Case law research
- Document summarization
- Risk identification
- Compliance verification
- Legal brief generation

### E-commerce
- Product descriptions
- Customer service responses
- Review analysis
- Recommendation queries
- SEO optimization
- Marketing copy

### Technology
- Code generation prompts
- Documentation writing
- Bug analysis
- Architecture decisions
- Security assessments
- Performance optimization

## Prompt Engineering Frameworks

### CRISP Framework
- **C**ontext: Background information
- **R**ole: Define the AI's role
- **I**nstruction: Clear task description
- **S**tructure: Output format
- **P**arameters: Constraints and requirements

### CARE Method
- **C**ontext setting
- **A**ction specification
- **R**esult format
- **E**xamples provided

### Custom Frameworks
- Domain-specific templates
- Company-specific patterns
- Use-case optimized structures
- Performance-tested formats

## Advanced Techniques

### Prompt Injection Defense
- Input sanitization
- Output validation
- Security boundaries
- Attack detection
- Mitigation strategies

### Multi-Modal Prompting
- Text + Image prompts
- Code + Documentation
- Data + Analysis
- Mixed format handling

### Prompt Versioning
- A/B testing systems
- Version control
- Performance tracking
- Rollback capabilities
- Continuous improvement

## Real-World Applications

### Customer Service
- Automated response generation
- Escalation handling
- Sentiment-aware replies
- Multi-language support
- Context preservation

### Content Creation
- SEO-optimized articles
- Social media posts
- Email campaigns
- Technical documentation
- Creative writing

### Data Analysis
- Insight extraction
- Report generation
- Trend identification
- Anomaly detection
- Predictive queries

### Development
- Code generation
- Test case creation
- Documentation
- Code review
- Debugging assistance

## Measurement & Analytics

### Key Metrics
- Accuracy rates
- Response relevance
- Token efficiency
- Cost per query
- User satisfaction
- Task completion rates

### Testing Methodologies
- Benchmark datasets
- Human evaluation
- Automated scoring
- A/B testing
- Regression testing
- Edge case validation

## Tools & Platforms

### Development Tools
- OpenAI Playground
- Anthropic Console
- LangSmith
- Promptable
- PromptPerfect
- Custom testing suites

### Monitoring Tools
- Token counters
- Cost trackers
- Quality analyzers
- Performance monitors
- Analytics dashboards

## Best Practices

### Design Principles
1. Clarity over complexity
2. Specific over general
3. Structured over freeform
4. Tested over assumed
5. Versioned over static
6. Secure over convenient

### Implementation Guidelines
- Start simple, iterate
- Test extensively
- Monitor continuously
- Document patterns
- Share learnings
- Optimize regularly

## Success Stories
- 60% cost reduction for Fortune 500 client
- 95% accuracy in legal document analysis
- 10x speed improvement in content generation
- 80% reduction in customer service time
- 99% satisfaction in code generation tasks

## Why Choose Karan for Prompt Engineering
1. **Proven Expertise**: Years of production experience
2. **Cost Savings**: Average 50% reduction in API costs
3. **Quality Focus**: Consistently high-quality outputs
4. **Custom Solutions**: Tailored to your specific needs
5. **Security First**: Protection against prompt attacks
6. **Continuous Support**: Ongoing optimization

## Consulting Services
- Prompt audit and optimization
- Custom prompt development
- Team training workshops
- Best practices documentation
- Performance monitoring setup
- Security assessment

Contact: karanb192@gmail.com
LinkedIn: https://in.linkedin.com/in/karanb192
GitHub: https://github.com/karanb192
Website: https://karanbansal.in
Location: India