Add rootless Podman fixes, and others

improve container startup for rootless Podman, plus related refactors and tests. Key changes:

- Add/modify Audiobookshelf-related code and wiring (src/lib/services/audiobookshelf/api.ts, library service refs) and update documentation TABLEOFCONTENTS to reference ABS implementation.
- Detect user namespace in docker/unified app-start.sh and redis-start.sh and skip gosu when running in rootless Podman to preserve UID mapping; improve startup logging and verification.
- Add utility/service files (auth-token-cache.service.ts, credential-migration.service.ts, cleanup-helpers.ts) and corresponding tests; update chapter-merger and metadata-tagger utilities/tests.
- Update many admin/auth API routes and tests to reflect changes in settings and integrations.
- Remove large AI agent and Audiobookshelf implementation guide docs (AGENTS.md and the implementation guide) and add README note about AI-assisted workflow.

These changes enable Audiobookshelf backend mode, improve compatibility with rootless container runtimes, and include cleanup/refactor work and unit tests.

README.md

@@ -91,10 +91,24 @@ Feature and fix Contributions are highly welcome. Documentation in `documentatio
 
 ## Support
 
-If you find this project useful, consider supporting development via [GitHub Sponsors]()
+If you find this project useful, consider supporting development via [GitHub Sponsors](https://github.com/sponsors/kikootwo) or [Ko-fi](https://ko-fi.com/kikootwo).
 
 If you'd like to support but cannot sponsor, a simple star on the GitHub repo is also greatly appreciated!
 
+## Built with AI Assistance
+
+This is a human-engineered application. Architecture, design decisions, code review, and project direction are managed by a principal engineer with nearly 15 years of professional software development experience.
+
+AI tools (Claude, GitHub Copilot) serve as force multipliers. Accelerating implementation, maintaining consistency, and handling boilerplate, while human expertise drives the technical vision. This mirrors how AI assistance is used at leading technology companies today.
+
+**The workflow:**
+- Token-optimized documentation system designed for AI consumption ([CLAUDE.md](CLAUDE.md))
+- Structured navigation enabling AI to find relevant context without reading entire codebases
+- Consistent architectural patterns that AI tools can follow and extend
+- Human review of all AI-generated code before merge
+
+The result: enterprise-grade velocity on a solo project without sacrificing code quality or architectural integrity.
+
 ---
 
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