AI learning answer
How do I move from LLM demos to production AI apps?
Short answer from Learnetto's Best AI engineering courses for developers guide.
Short answer
Add evals, tracing, model comparisons, cost and latency checks, failure handling, and user feedback. Production AI engineering begins when the demo has to survive real users.
Context from the full guide
Use AI Hero or LangChain courses for app-building practice, Chip Huyen and Full Stack Deep Learning for production judgment, and eval/observability resources once your demo needs to survive real users.
Useful resources
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AI SDK v6 Crash Course
Workshop · Matt Pocock · Intermediate
You want a structured AI SDK v6 course that covers model choice, text and object generation, UI streams, agents, persistence, context engineering, evals, and advanced app patterns.
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The AI Engineer Roadmap
Free tutorial · Matt Pocock · Beginner to intermediate
You want a guided path through core AI concepts, model selection, the AI engineering mindset, evals, and techniques for improving LLM-powered apps.
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LangChain for LLM Application Development
Short course · DeepLearning.AI · Beginner to intermediate
You want a fast introduction to building LLM applications with chains, retrieval, and tools.
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AI Engineering
Book · Chip Huyen · Intermediate to advanced
You are moving from demos to production systems.
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OpenAI Cookbook
GitHub repo · OpenAI · Beginner to advanced
You need implementation examples rather than theory.
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Microsoft AI Agents for Beginners
GitHub repo · Microsoft · Beginner to intermediate
You want a structured agent learning path with code.
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Prompt Engineering Guide
Guide · DAIR.AI · Beginner to advanced
You want examples of prompting techniques and patterns.
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LLM Fundamentals
Free tutorial · Matt Pocock · Beginner
You need clear mental models for system prompts, tokens, context windows, tools, and agents before building or using AI systems seriously.