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title: Understanding the generative AI development process
description: The generative AI development process involves model selection, prompt engineering, hyperparameter tuning, retrieval-augmented generation (RAG), agents, model...
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# Understanding the generative AI development process

**[InfoWorld](https://daily.dev/sources/infoworld)** · 10 min read · 3 upvotes · 0 comments

## Summary

The generative AI development process involves model selection, prompt engineering, hyperparameter tuning, retrieval-augmented generation (RAG), agents, model fine-tuning, and continued model pre-training. Model selection should consider future updates and ongoing cost. Prompt engineering techniques include providing clear instructions, exemplars, using documents, and utilizing chain-of-density or chain-of-thought prompts. Hyperparameter tuning involves adjusting temperature, context window, maximum number of tokens, and stop sequence. Retrieval-augmented generation helps to ground LLMs with specific sources using embedding and semantic similarity search. Agents expand on conversational LLMs and specialize LLMs to specific domains.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.infoworld.com/article/3715396/understanding-the-generative-ai-development-process.html>

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Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#deep-learning](https://daily.dev/tags/deep-learning), [#genai](https://daily.dev/tags/genai), [#prompt-engineering](https://daily.dev/tags/prompt-engineering)

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