Latency & Performance
Master strategies to optimize response times and deliver fast, responsive AI agents
Your Progress
0 / 5 completedKey Takeaways
Latency optimization is about user experience, not just milliseconds. Apply these 10 principles to build fast, responsive AI agents that users love:
Latency directly impacts user satisfaction
Every 100ms of delay reduces satisfaction by 7%. Target <1s for interactive applications, <200ms for real-time agents.
Measure before you optimize
Break down latency into components: network, queue, model inference, post-processing. Identify the bottleneck before applying solutions.
Caching provides the highest ROI
90%+ latency reduction for cache hits with minimal implementation effort. Cache common queries, embeddings, and expensive computations.
Faster models for simple tasks
GPT-3.5 is 3-5x faster than GPT-4 for routine operations. Use smaller models for classification, simple Q&A, and structured extraction.
Parallel processing compounds gains
Execute independent operations concurrently. Three 500ms sequential calls = 1500ms. Three parallel calls = 500ms total.
Streaming transforms user experience
Users perceive streaming as 40-60% faster than batch responses. Optimize TTFT (time to first token) to <300ms for immediate feedback.
Async patterns prevent blocking
Use non-blocking I/O and background processing. Offload non-critical tasks (analytics, logging) to queues—don't make users wait.
Token count affects speed
Shorter prompts and outputs process faster. Every token adds inference time. Reduce unnecessary context and limit output length.
Pre-computation moves work offline
Generate embeddings, summaries, and extractive data before user requests. 2000ms runtime → 50ms lookup with pre-computation.
Perceived speed > actual speed
Show progress indicators, enable streaming, keep UI responsive. A 1s streaming response feels faster than 800ms batch with no feedback.
Priority: Optimize the Critical Path
Start with high-impact optimizations: caching (90% reduction), faster models (50-70%), parallel processing (40-60%). Measure P95 latency, set SLA targets, and iterate until you meet them. Focus on user-facing operations—offload background work to queues. Combine multiple techniques for compounding effects. Most importantly: perceived speed matters more than actual milliseconds—enable streaming and keep UIs responsive.