My Personal AI Stack in 2026

Ask ten AI developers what tools they use, and you'll probably get ten different answers. The AI ecosystem is evolving so quickly that it's easy to believe you need every new framework, model, and application to stay productive. I don't think that's true. Over the past year, I've experimented with dozens of AI tools while building products, writing technical content, managing prompt libraries, and developing AI workflows. Along the way, my stack has become surprisingly simple. It's not built around the "best" tools. It's built around the tools that work well together. Here's the AI stack I rely on in 2026 and, more importantly, why each tool has earned its place. 1. ChatGPT: My Primary Thinking Partner ChatGPT is where most of my work begins. Not because it can do everything, but because it helps me think faster. I use it for: Brainstorming ideas Structuring articles Reviewing technical concepts Exploring architectural trade-offs Refining prompts Research assistance I rarely expect the first response to be perfect. Instead, I treat it like collaborating with a knowledgeable teammate who accelerates my thinking. 2. Cursor: My AI-Powered Development Environment When it's time to write code, I move into Cursor. Its strength isn't just code generation. It's understanding the context of an entire project. Whether I'm building a FastAPI backend, integrating APIs, or refactoring an existing codebase, having AI directly inside the editor removes a huge amount of friction. The less I switch between applications, the more productive I become. In fact, one of the biggest lessons I've learned is that adding more AI tools doesn't automatically improve productivity. Sometimes it has the opposite effect. I explored this idea in The Hidden Cost of Using Too Many AI Tools , where I explain why a smaller, well-integrated stack often outperforms a collection of disconnected applications. 3. GitHub: The Source of Truth Every project eventually ends up in GitHub. Not just source code. I