leetcode problems I solved to prepare for my Google interview.

A compact implementation of SGLang, designed to demystify the complexities of modern LLM serving systems.

A skill file for removing AI tells from prose

Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.

A tool for creating and running Linux containers using lightweight virtual machines on a Mac. It is written in Swift, and optimized for Apple silicon.

AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket, and the web - then synthesizes a grounded summary

Research into AI engineering interview assignments, take-home challenges, and hiring practices from 2026

An agent-managed museum exhibit, built in Rust with Gajae-Code / LazyCodex — developed and maintained with no human intervention.

AI agents running research on single-GPU nanochat training automatically

Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on-the-job training. Reinforcement learning for Qwen3.6, GPT-OSS, Llama, and more!

Machine Learning Systems: Foundations, Scaling, Agentic AI, and Physical AI (Vols I–IV) • Harvard CS249r | https://mlsysbook.ai

Multi-tenant MCP Server Platform

Generate Agent Skills from MCP server tools. Connects via Streamable HTTP, discovers tools, and outputs a skill with schema docs and a call script in the language of your choice.

Intercept LLM API traffic and visualize token usage in a real-time terminal dashboard. Track costs, debug prompts, and monitor context window usage across your AI development sessions.

🚀 SuperMCP - Create multiple isolated MCP servers using a single connector. Build powerful Model Context Protocol integrations for databases (PostgreSQL, MSSQL) with FastAPI backend, React dashboar…

🚀 The fast, Pythonic way to build MCP servers and clients.

AI-powered synthetic data generation — structured tables, unstructured documents, multi-provider LLM support, referential integrity, and code-gen mode for millions of rows

Elegantly manage your MCP services

Create any mcp tools for databases, rest and apis

LLM Zoomcamp - a free online course about real-life applications of LLMs. In 10 weeks you will learn how to build an AI system that answers questions about your knowledge base. Register here 👇🏼

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

Chat with your data - AI data analysis and visualization on CSV, Postgres, MySQL, Snowflake, SQLite...

My collection of handwritten notes and resources for learning distributed systems

The Patterns of Scalable, Reliable, and Performant Large-Scale Systems

Fork of Flask-RESTPlus: Fully featured framework for fast, easy and documented API development with Flask

Fast way to create access database

Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

Official repository for Spyder - The Scientific Python Development Environment