Advanced
Performance Optimization
Real case studies of using AI to optimize performance, with before/after metrics from actual client projects
Real Case: Client A Report Optimization
Initial state:
- Complex financial report
- 180+ seconds to generate
- Frequent timeouts
- User complaints piling up
Approach
Step 1: Profile
You: "Help me add performance logging to @ReportService.ts:
- Time each major operation
- Log database query times
- Log data processing times
- Output structured JSON"Step 2: Analyze with AI
You: "Here's profiling output from production:
[paste logs]
Identify bottlenecks."
AI:
"Main issues:
1. N+1 query loading related data (85% of time)
2. Processing all records in memory (12% of time)
3. Complex aggregations in application code (3% of time)"Step 3: Optimize iteratively
Iteration 1: "Fix N+1 queries with proper joins"
Result: 180s → 45s
Iteration 2: "Stream process large datasets instead of loading all"
Result: 45s → 20s
Iteration 3: "Move aggregations to database"
Result: 20s → 8s
Iteration 4: "Add Redis caching for frequent reports"
Result: 8s → 5s (cached)Final Result
- 180s → 5-20s (depending on cache)
- Zero timeouts
- Happy users
- Client showcase case
Key insight: AI excellent at identifying patterns from profiling data. Suggests optimizations you might miss.