The whole data model fits in two tables:
Plan for iterative improvement rather than expecting immediate perfection. AIO is still an emerging practice without definitive best practices etched in stone. You'll make mistakes, try things that don't work, and occasionally optimize for factors that turn out not to matter. This experimentation is part of the learning process. What matters is systematic iteration—trying approaches, measuring results, adjusting based on feedback, and gradually improving your effectiveness over time.
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