Four ways I build.
Not one generic toolkit — four distinct competencies that show up together in everything I ship, from the pixel to the schema.
Design
I design in the browser as much as in Figma — component-first, with a real type scale, spacing rhythm, and both light and dark palettes worked out before a single feature ships.
- Design systems: type scale, spacing tokens, color roles (light + dark)
- Component-driven UI with shadcn/ui + Tailwind, built for reuse
- Motion and micro-interaction with Framer Motion
- Accessible, responsive layouts down to mobile
Frontend
Next.js and React are where I spend most of my time — building reusable component libraries, wiring global state, and integrating REST APIs into features that hold up under real usage.
- HTML, CSS, JavaScript & TypeScript fundamentals
- React.js / Next.js (App Router)
- shadcn/ui + Tailwind CSS for accessible, responsive UI
- State management with Redux Toolkit
Backend
On the backend I work across Node/Express and Python's FastAPI, model data in both MongoDB and PostgreSQL, and went deep on Redis (including pub/sub) and RabbitMQ for queueing — plus the Linux/Docker/AWS layer that ships it.
- Node.js + Express REST APIs, FastAPI + Pydantic on the Python side
- MongoDB (Mongoose) & PostgreSQL (Prisma) data modeling
- Redis for caching and pub/sub, RabbitMQ for queues
- Linux, Docker, Git/GitHub, AWS EC2 & S3
Full-Stack + AI
I'm deliberately extending full-stack work into applied AI: learning to design retrieval and agent systems, not just call an API endpoint. This section will keep changing as projects land.
- Generative AI fundamentals & prompt design
- RAG (Retrieval-Augmented Generation) pipelines
- LangGraph for agentic, stateful workflows
- Vector databases for semantic search
What I'm learning right now
I'd rather show you the in-progress list than pad the skills section with things I haven't shipped yet.
Generative AI fundamentals
Prompting, model behavior, and evaluation basics
RAG pipelines
Chunking, embeddings, and retrieval-augmented generation
LangGraph
Stateful, multi-step agent workflows
Vector databases
Semantic search and similarity retrieval at the data layer
Credentials along the way
Data Analytics and AI
Dell Technologies
C++ Programming
Coding Ninjas
Web Development (HTML, CSS, JavaScript)
Coding Ninjas