Bottom line: generative AI development combines prompt design, LLM APIs, retrieval, evaluation, safety, and product engineering.
Generative AI Development Course
Learn generative AI development with prompts, LLM APIs, embeddings, retrieval, evaluation, safety, and production app patterns.
Start learning AIDeveloper Skills
Generative AI developers need prompt workflows, API usage, streaming, embeddings, retrieval, evaluation, guardrails, logging, and UX patterns.
Production Patterns
Production applications need cost controls, safety checks, observability, fallback behavior, secure secrets, and clear user feedback.
What To Build
Useful projects include assistants, content tools, document search, RAG workflows, agentic automation, and domain-specific copilots.
Frequently Asked Questions
What is generative AI development?
Generative AI development is the process of building applications that use LLMs or other generative models to create, reason, retrieve, and assist.
Do generative AI apps need evaluation?
Yes. Evaluation is essential because LLM outputs can vary, and production systems need quality checks, safety controls, and monitoring.