Identify code paths that execute frequently and ensure they use performant, non-blocking solutions. Frequent operations should avoid expensive database queries, CPU-intensive synchronous processing, or anything that can block the event loop. For high-frequency database operations, use caching solutions like Redis instead of direct database queries. For CPU-intensive tasks like HTML parsing that run often, consider moving the logic to more performant runtimes or libraries. Example of what to avoid: ```typescript // Bad: DB query on every job insert const { data: recentNotifications } = await supabase_service .from("user_notifications") .select("*") .eq("team_id", team_id) .gte("sent_date", pastDate.toISOString()); ``` Example of better approach: ```typescript // Good: Use Redis for frequent lookups const recentNotifications = await redis.get(`notifications:${team_id}`); ``` Before implementing any operation that will run frequently, evaluate its performance impact and consider alternatives like caching, background processing, or more efficient libraries/runtimes.