The architecture of today's LLM applications - The GitHub Blog
This GitHub Blog article explains the architecture of today’s LLM applications and ways to begin building one.
About The architecture of today's LLM applications - The GitHub Blog
This GitHub Blog post, written by Nicole Choi, covers five major steps to building an LLM app and the emerging architecture of today's LLM apps. It also points to problem areas that readers can start exploring. The article is aimed at developers who want to build their first LLM app and need a sense of datasets, embeddings, and parameter weights. It was published October 30, 2023 and updated February 7, 2024.
Pricing is not clearly stated.
Key features
- Explains five steps to building an LLM app
- Covers choosing a pre-trained model by licensing, size, and performance
- Describes in-context learning, RLHF, and fine-tuning
- Explains offline evaluations and incremental scoring
- Discusses problem spaces to explore
Best for: Developers who want to build their first LLM app.
Watch out for
- Written at a high level, so it gives an overview of each step
- Fine-tuning requires time-intensive labeling
The architecture of today's LLM applications - The GitHub Blog at a glance
- Official website
- github.blog/engineering/the-architecture-of-to…
- Category
- Development › Developer News & Communities
- Type
- Publication
- Platforms
- Web
- Details verified
- Oct 21, 2026 · Official source
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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The architecture of today's LLM applications - The GitHub Blog FAQ
Does the article point to other resources?
Yes. It links to a developer's guide to open source LLMs and generative AI, and it points to RLHF resources, including codebases.
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