Small Qubit Labs

AI Lab

Building with AI.
Not just talking about it.

The AI Lab is where I ship software. Tools, agents, automations, and applications — built with the best AI APIs and frameworks available today. Every project is a real thing that runs, not a prototype that never left a Jupyter notebook.


Status: first projects in development

What I build

AI Agents

Autonomous systems that actually work

Agents built on top of LLM APIs that handle real tasks — research, synthesis, code generation, workflow automation. Focused on reliability and production-readiness, not demos.

Developer Tools

Software for people who build software

CLI tools, APIs, and libraries that make AI capabilities accessible and composable. Built with the same precision I'd want as a user.

AI-Powered Apps

Products with intelligence built in

Full applications where AI is the core feature, not a bolt-on. From idea to deployed — exploring what's possible when you build AI-first rather than AI-last.


Projects

In developmentActive

Project 01

Details coming soon. Building in the open — this card will update as the project takes shape.

Next.jsClaude APITypeScript
In developmentActive

Project 02

Details coming soon. Building in the open — this card will update as the project takes shape.

PythonOpenAI APIFastAPI
PlannedNext

Project 03

On the roadmap. Stack and scope being defined.


The stack

AI / LLM APIs

Claude (Anthropic), GPT-4o (OpenAI), Gemini

Agent frameworks

Claude Agent SDK, LangChain, custom orchestration

Languages

TypeScript, Python

Frontend

Next.js, React, Tailwind CSS

Backend & APIs

FastAPI, Node.js, Vercel Edge Functions

Data & storage

PostgreSQL, Supabase, Pinecone (vector)

Infrastructure

Vercel, GitHub Actions, Docker

Observability

Langfuse, custom evals


How I build

Ship over theorise

The best way to understand what AI can do in 2026 is to build something real with it. Reading papers and watching demos tells you what others found. Shipping tells you what you find.

Production-first

Demos are easy. Reliable systems are hard. Every project is built with observability, error handling, and real users in mind — even when it's a side project at 11pm.

Composable over monolithic

AI systems built as modular, composable components age far better than tightly coupled pipelines. The tools and APIs will change. Good architecture shouldn't have to.


Have a problem worth solving?

If you're looking for AI software built with architectural discipline — not a no-code wrapper — let's talk.

Get in touch