Anthropic's Interactive Prompt Engineering Tutorial

A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.

Daytona is a Secure and Elastic Infrastructure for Running AI-Generated Code

Repository for a content generation and research agent built with Google ADK

AGENTS.md — a simple, open format for guiding coding agents

DSPy: The framework for programming—not prompting—language models

AI-powered document intelligence platform for automated analysis, processing, and insights extraction from various document formats.

Real-time data analysis and control system leveraging AI for dynamic decision-making and automated response mechanisms.

Monoscope lets you ingest and explore your logs, traces and metrics. We store these in S3 compatible buckets. Query in natural language via LLMs.

An open-source AI agent that brings the power of Gemini directly into your terminal.

An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.

12 Lessons to Get Started Building AI Agents

Agent2Agent (A2A) is an open protocol enabling communication and interoperability between opaque agentic applications.

The Go programming language

A curated list of VULNERABLE APPS and SYSTEMS which can be used as PENETRATION TESTING PRACTICE LAB.

Docker Model Runner

The Intelligent Copilot for Solana

Write a large text on your GitHub profile, with your commits history (contribution graph).

Full stack, modern web application template. Using FastAPI, React, SQLModel, PostgreSQL, Docker, GitHub Actions, automatic HTTPS and more.

Autonomous coding agent right in your IDE, capable of creating/editing files, executing commands, using the browser, and more with your permission every step of the way.

🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 12 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴

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

Represent, send, store and search multimodal data

Seesaw v2 is a Linux Virtual Server (LVS) based load balancing platform.

Starlark in Go: the Starlark configuration language, implemented in Go

Starlark Language

Summaries and resources for Designing Machine Learning Systems book (Chip Huyen, O'Reilly 2022)