Technology Stack
AI & LLM Stack
Large language models, AI frameworks, and generative AI tools. The frameworks and tools I use to build, experiment, and ship real solutions.
- BuildReal solutions
- ExperimentContinuously
- StayUp to date
- ShareWhat I learn
- Large Language Models
- Prompting
- RAG
- Agentic AI
- Evaluation
- Guardrails
- Deployment
AI & LLM
Large language models, AI frameworks, and generative AI tools.
From foundation models to real-world applications — I work with the latest AI technologies to solve meaningful problems.
Overview
Large Language Models (LLMs) and generative AI are transforming how we build software. I use a combination of hosted models, open-source models, and modern frameworks to create intelligent applications such as chatbots, AI agents, RAG systems, and automation tools.
My focus is on practical, production-ready solutions — combining the right models, frameworks, and infrastructure to deliver real value.
Key Focus Areas
- LLM application development
- RAG (Retrieval-Augmented Generation)
- Prompt engineering & optimization
- Model evaluation and monitoring
- AI guardrails and safety
- Deploying scalable AI solutions
- Exploring open-source alternatives
Tools & Technologies
A selection of the tools and platforms I work with.
OpenAI
Claude
Google Gemini
Hugging Face
Llama
Mistral AI
LangChain- LlamaIndex
- Vector Databases
FastAPI
vLLM
Ollama
CrewAI
Vercel AI SDK
Qdrant
PostgreSQL
Python
MCP
My Experience Level
Not just tools — real hands-on experience.
- Prompt Engineering90%
- RAG Systems85%
- Fine-tuning & Model Optimization70%
- LangChain / LlamaIndex85%
- Model Evaluation75%
- AI Guardrails70%
- Open-source LLMs (Llama, Mistral, etc.)80%
- Deployment (vLLM, Docker, Cloud)75%
Real-World Applications
How I use these technologies in practice.
- AI-powered assistants for business applications
- Document Q&A systems using RAG
- Multi-agent systems for complex workflows
- Automating repetitive tasks with LLMs
- Intelligent search and knowledge retrieval
- Content generation and summarization
- AI-powered analytics and insights
- Integrating LLMs with enterprise systems
Featured Projects
- AegiSense AI AssistantAn AI-powered assistant for identity and security operations. Uses RAG, tool calling, and guardrails to answer security questions and automate workflows.LangGraphFastAPIPostgreSQL
- Document Intelligence LabExperiments with different RAG pipelines, chunking strategies, and vector databases to find the best setup for real-world use cases.LlamaIndexQdrantOpenAI
What's Next?
Continuously learning and exploring.
- Explore multimodal models (vision + text)
- Experiment with local LLM deployments
- Build more domain-specific AI agents
- Evaluate and compare LLM performance
- Share learnings through tutorials and articles
Learning Resources
Articles and tutorials I've written on these topics.
New articles and tutorials on this topic are on the way.
Let's Build Something Amazing
Have a project in mind or want to collaborate? I'm always open to discussing new opportunities.
Let's Talk