Process

My Proven AI Development Framework

Transforming ideas into production-grade AI systems through a battle-tested methodology that delivers results in weeks, not months.

01

Discovery & Architecture Design

Deep dive into your domain. I analyze your data, map user workflows, and architect the optimal AI solution—whether it's RAG, fine-tuned models, or multi-agent systems.

  • Data pipeline design & vector DB selection
  • Model selection (GPT-4, Claude, Llama 3, Mistral)
  • Latency & cost optimization strategy
  • Scalability roadmap
02

Rapid Prototyping & Prompt Engineering

See your AI in action within days. I build functional prototypes using advanced prompt engineering, few-shot learning, and chain-of-thought reasoning.

  • Prompt versioning & A/B testing
  • Embedding model evaluation
  • Initial RAG pipeline construction
  • User feedback integration loops
03

Model Fine-tuning & Optimization

Make it yours. Fine-tune open-source models on your proprietary data. Implement RLHF, LoRA adapters, and custom tokenization for maximum performance.

  • Dataset curation & augmentation
  • LoRA/QLoRA fine-tuning
  • Evaluation against industry benchmarks
  • Cost reduction through model distillation
04

Production Deployment & MLOps

Deploy with confidence. Containerize with Docker, orchestrate with Kubernetes, and implement comprehensive monitoring for LLM-specific metrics.

  • CI/CD pipelines for models & prompts
  • GPU optimization & auto-scaling
  • Real-time monitoring & drift detection
  • Safety guardrails & content filtering

Typical Project Timeline

Week 1-2

Discovery & Architecture

Technical Spec Document

Week 3-4

Prototype & Testing

Working MVP

Week 5-6

Fine-tuning & Optimization

Custom Model

Week 7-8

Deployment & Monitoring

Production System

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