The open-source AI stack is a set of models and tools that enables developers to build state-of-the-art AI applications without sacrificing control over deployment, privacy, and performance. This shift democratizes access to AI capabilities, allowing developers to leverage the increased reasoning capabilities of open-source large language models while retaining full control over their data and deployment choices. The stack includes open-source large language models like Meta's Llama 3 family, Alibaba Cloud's Qwen 2.5, Microsoft's Phi 3, DeepMind's Gemma 2, and Ollama, a tool that abstracts away infrastructure challenges, streamlines deployment, and provides access to hundreds of LLMs and embedding models. The stack also integrates with PostgreSQL, the most loved database in the world, which has an ecosystem of open-source extensions for storing and retrieving AI applications. Additionally, FastAPI is used as the framework of choice for developers, offering asynchronous capabilities, automatic documentation, and efficient systems. NextJS emerges as the go-to React framework for production deployments, handling complex state management and dynamic updates. The evaluation ecosystem remains a key challenge, but projects like LangFuse and Phoenix offer promise, and the community is expected to define reliable, real-world AI applications.