Advanced2.5 hours
0/3 complete
Generative AI Patterns
Architectural patterns for integrating AI generation into production systems — sync vs. async, caching strategies, and multi-model pipelines.
Who this is for
Senior engineers and architects who need to integrate AI generation into real production systems — at scale, with real constraints.
This isn't about single API calls. It's about the patterns that make AI features reliable, fast, and cost-effective at 100k requests/day.
What you'll learn
- When to use synchronous vs. asynchronous generation — and when the right answer is "both"
- Caching strategies specific to generative AI (prompt hashing, semantic deduplication, output reuse)
- Multi-model pipelines: image → video → audio chains with error recovery
Modules
Module 1 — Sync vs. Async Patterns
Decision framework for real-time vs. background generation. Queue architectures, backpressure, and graceful degradation.
Module 2 — Caching, Deduplication & Cost Optimization
Prompt hashing, semantic similarity caching, output TTL strategies, and budget guardrails.
Module 3 — Multi-Model Pipelines
Compose image, video, and audio models into reliable pipelines with fan-out, fan-in, and circuit breakers.
Start with Module 1 →