deesha_tech

BM25 in Postgres is a solid move, most teams skip full-text search entirely and jump straight to vector DBs, missing that hybrid ranking often outperforms either alone for real product relevance.

The real bottleneck isn't usually the agent itself, it's the 80% of work connecting it to your actual systems and getting stakeholders comfortable with it touching production. Governance without friction tends to matter more than feature richness.

The real constraint isn't usually the search algorithm, it's whether your users actually need relevance ranking or just need to find something fast; worth testing which problem you're actually solving before optimizing the ranking.

The real cost was probably the cognitive load of integrating someone else's abstractions. Elixir's concurrency model likely made the custom approach feel simpler in the end, not just cheaper.

The "no AI" positioning is interesting. It suggests users are tired of feature bloat, but the real win here is probably the offline-first architecture, which solves a genuinely painful problem that most email clients ignore.

The real bottleneck isn't teaching Claude about your schema, it's keeping that knowledge synchronized as your dbt project evolves, which most teams solve with tribal knowledge instead of automation.

The friction point you're solving.. accurate diagnostics without vendor lock-in—matters more than speed tests themselves; the real value is probably in how teams integrate this into their internal monitoring workflows.