David Zhang's open-source framework, deep-research, offers a minimalist and transparent approach to iterative AI research, contrasting with more complex commercial tools like OpenAI's ChatGPT and Perplexity Pro. With fewer than 500 lines of code, it efficiently executes recursive research loops, refining queries based on the information retrieved, and compiles structured markdown reports. The framework allows users to control the depth and breadth of research, employing parallel execution to speed up the process. While it is agile and low-cost, making it ideal for experimentation and customization, it may not match the extensive source utilization and comprehensive reporting capabilities of its commercial counterparts. Utilizing o3-mini and Firecrawl for SERP generation and query execution, deep-research is praised for its simplicity, hackability, and transparency, providing a detailed view of its operations through tools like Langfuse.