Creating an AI Development Manifesto, inspired by the Agile Manifesto, is an excellent idea. This manifesto can serve as a guiding principle for your AI development practices, emphasizing the core values and principles that you deem most important in this field. Given your preferences for Python, Django, HTMX, Alpine JS, Bootstrap, Pytest, Celery, and deployments on DigitalOcean with GitHub for version control, I will tailor the manifesto to reflect these choices and your development philosophy. Here's a draft:

AI Development Manifesto

In the pursuit of excellence in AI development, we are constantly exploring more effective ways of creating and implementing artificial intelligence. Through our experiences and collaborations, we have come to value:

1. Innovative Algorithms and Data-Driven Insights over Rigid Coding Practices: We believe in the power of innovative AI algorithms and the insights drawn from quality data, more than just adhering to traditional or rigid coding practices.

2. Practical, Scalable AI Solutions over Theoretical Models: While appreciating the importance of theoretical underpinnings, we prioritize the development of practical, scalable AI solutions that can be effectively integrated and used in real-world applications.

3. Collaboration and Openness in AI Development over Working in Silos: We value collaborative efforts and open sharing of knowledge in AI development, as it leads to more robust, creative, and inclusive AI solutions.

4. Adaptability and Continuous Learning over Confinement to Established Tools: In the ever-evolving field of AI, adaptability and a commitment to continuous learning and experimentation are valued more than confinement to established tools and technologies.

5. Ethical Considerations and Social Impact over Merely Technological Advances: We give priority to ethical considerations and the social impact of AI technologies, aiming for advancements that are not only technologically profound but also socially responsible.

6. User-Centric AI Development over Purely Code-Centric Approaches: Our focus is on developing AI that enhances user experience and meets user needs, rather than focusing solely on the technical aspects of coding.

7. Efficiency and Performance in Deployment over Theoretical Optimization: While theoretical optimization is important, we place higher value on efficiency and performance in real-world deployments, ensuring our AI solutions are accessible and effective in practical scenarios.

8. Continuous Integration and Feedback over One-Time Deployment: We believe in continuous integration of AI systems with regular feedback loops, rather than one-time deployments, to ensure ongoing improvement and relevance.

9. Sustainable and Maintainable AI Systems over Quick Fixes: Long-term sustainability and maintainability of AI systems are prioritized over short-term or quick-fix solutions.

Remember, this manifesto is a living document and should evolve as your understanding and the field of AI development evolves. It's meant to reflect your current principles and practices, and it should be open to changes as new insights and experiences shape your approach.