AI prototyping tools built on Supabase (e.g., Lovable, Bolt) have insecure default settings that can expose all user data.
Developers using these tools are often unaware of the underlying architecture and the need to configure security settings like Row Level Security (RLS).
AI code generation can introduce subtle but critical errors, such as hardcoding 'localhost' URLs, that prevent successful deployment.
Opportunities Identified
Using a secure, pre-configured SaaS template can significantly accelerate development while avoiding common security and architectural pitfalls.
Combining a solid template with AI coding assistants (like Codex or Claude) within an IDE enables rapid, pattern-based feature development.
There is a clear opportunity for developers who understand full-stack principles to build more robust and secure AI applications.