The author emphasizes the importance of speed over intelligence in AI coding tools, especially for those who struggle with attention issues, like ADHD. They share their experience with "agentic coding," which involves using smart AI models that take time to think through tasks. This approach often leads to frustration, as waiting for the model to complete its work can disrupt focus and productivity. Instead, the author advocates for quick, mechanical edits—referred to as "leaf node edits"—which are straightforward tasks like renaming functions or minor code adjustments. These tasks don’t require deep thought, making them ideal for AI assistance. The author highlights the performance of Cursor's Composer, praising its speed despite occasional mistakes. They note that it excels at making fast changes, even if the output isn't always perfect. Other models, like Gemini Flash, are mentioned for their speed but criticized for reliability issues, such as API outages and hallucination problems when handling large context inputs. The author prefers tools that don't add complexity or require extensive management, arguing that the goal is to streamline the coding process rather than complicate it with multiple providers. Ultimately, the author finds that faster models enhance their workflow, allowing them to make quick adjustments and iterate on their work without the drag of waiting for a model to produce thoughtful responses. They argue that speed is essential for maintaining productivity and sanity in coding tasks, particularly for those who may struggle with focus.