Master production-grade LLM application development with hosted APIs (Anthropic Claude, OpenAI, Google Gemini). Learn prompt caching for 90% cost reduction, batch APIs for throughput optimization, reasoning models (o1/o3, extended thinking), structured outputs, agentic patterns, and multi-provider reliability strategies. Build job-ready skills for deploying cost-optimized, reliable LLM applications at scale.
Foundation concepts for production hosted LLM systems
Provider APIs, token economics, prompt caching strategies, cache optimization
Maximizing throughput while minimizing costs
Batch APIs, model routing, cost-quality tradeoffs, multi-tier strategies
Reliable structured outputs and tool orchestration
JSON schema enforcement, function calling, tool orchestration, computer use
Leveraging reasoning models and compute-optimal strategies
o1/o3, extended thinking, chain-of-thought, self-consistency, best-of-N
Building multi-step reasoning and memory systems
ReAct, planner-executor, multi-agent, context management, memory systems
Production reliability, cost optimization, and full observability
Rate limiting, circuit breakers, multi-provider fallback, Prometheus, Grafana, Postgres, cost tracking
Advanced hosted inference patterns: multi-provider orchestration, semantic caching, streaming, observability, rate engineering, and cost simulation
Multi-provider orchestration, semantic caching, production streaming patterns, hosted inference observability, rate limit engineering, inference cost simulation