Exploring AI-native Runtime for Robust CRUD Applications
In the rapidly evolving landscape of Artificial Intelligence, I’m excited to share my work on an AI-native runtime designed for long-lived CRUD, workflow, and dashboard applications. The core challenge? Tackling not just the initial code but subsequent iterations that can lead to system failures despite “valid JSON.”
Key Features Include:
- No Broken Joins: Canonical models ensure valid entity evolution.
- Repeatable Migrations: Preview migrations with append-only history and rollback options.
- Controlled RBAC Drift: Semantic-breaking permission changes require explicit acknowledgment.
- Stable UI Bindings: Prevent data drift by binding components to named datasets.
- Meaningful Change Summaries: Receive semantic diffs instead of raw JSON.
This system aims to redefine lifecycle management by making schema evolution paramount—almost like developing a domain OS for vertical SaaS.
Join the Conversation!
I invite AI and tech enthusiasts to share insights on runtime invariants and solutions to semantic drift. Let’s connect and foster innovation!
