AI help for debugging RLS query errors (assistant CTA in tester)

AI help for debugging RLS query errors (assistant CTA in tester) targets a $8.0B = 20M developers x $400 avg annual spend on developer and DB tooling total addressable market with medium saturation and a year-over-year growth rate of 15% (developer productivity and cloud DB tools growth).

Key trends driving demand: LLM-assisted development -- LLMs are integrated into IDEs and consoles, creating demand for contextual, domain-specific assistants.; Cloud-native DB adoption -- more teams run managed Postgres/Cloud SQL with RLS, increasing need for permission debugging tools.; Shift-left security -- teams test security earlier in CI and consoles, creating demand for tooling that reduces manual policy troubleshooting.; Embedded analytics & tooling -- consoles are expected to offer active help (telemetry, suggestions) rather than static docs..