My AI Workflow for Maximum Productivity as a Developer
The article discusses how the author uses AI as a fast assistant to improve their development workflow, covering planning, boilerplate generation, debugging, UI decisions, and product thinking.
Why it matters
The article provides a practical example of how developers can integrate AI into their workflow to improve productivity and focus on the core aspects of building applications.
Key Points
- 1Explains AI as a helper, not a replacement, for development skills
- 2Uses AI to plan, break down features, generate boilerplate, and debug issues
- 3Leverages AI for UI/UX feedback and to consider product requirements beyond just functionality
Details
The author shares their AI-powered development workflow, which they've built over time while working on Flutter and Supabase projects. They start by explaining their ideas in plain English and use AI to break them into smaller features, identify potential gaps, and organize the project structure before writing code. For repetitive tasks like setting up basic screens, models, APIs, and state management, the author lets AI generate a starting point that they then refine. When debugging, they paste the error, explain their expectations, and ask AI what could be wrong, which often points them in the right direction faster than random searching. As a non-designer, the author uses AI to get feedback on UI layouts, spacing, and color choices. Finally, they leverage AI to think beyond just
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