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AI Native Python - Roadmap

This document outlines future improvements and enhancements for the ai-native-python project.

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Ideas

1. Add Policy as Code

Add digestabot and pin all actions
Add zizmor
Ensure the python version is in line throughout the repo; python_version in the refurb config with .python-version, with the default in Dockerfile, etc.
Ensure that the correct task steps exist in Taskfile.yml

2. Improve flexibility/usability

Keep the public yes/no but split out a CodeQL yes/no (default to yes; secure by default but it may error if insufficient licensing)
Improve the docs around releasing and rulesets/branch protections
Add support for releasing to pypi via oidc

3. Improve project health checks

Automated security checks
Code quality metrics
Dependency health monitoring

4. Support additional runtimes

Dev container configuration / local testing
Lambda image runtime support in AWS
Docker Compose examples
Cloud-native deployments/IaC (ECS, EKS, AKS, GKE)

5. AI-powered project customization

Natural language project specification
Intelligent dependency selection
Code scaffold generation based on requirements

6. Integration with more pipelines

Cloud provider integrations (AWS, GCP, Azure)
CI/CD platform integrations (GitLab, ADO, bitbucket)

7. Project analytics and insights

Development velocity metrics
Dependency update compliance
Security posture tracking

Technical Debt to Address

Documentation

Add architecture decision records (ADRs)
Create video tutorials
Improve troubleshooting guides

Community Feedback Ideas

We welcome community feedback and contributions. Some areas where we'd especially appreciate input:

Additional project templates needed
Integration requirements with other tools
Security and compliance features
Developer experience improvements

Contributing

If you're interested in contributing to any of these roadmap items, please see our contribution guide, and thank you! 🎉