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LLM App Ecosystem: What's New and How Cloud Native Is Adapting - The New Stack

thenewstack.io · 5,796 words · saved by 1 readers

The developer ecosystem for AI-enabled applications is beginning to mature, after the emergence over the past year of tools like LangChain and LlamaIndex. There’s even now a term for AI-focused developers: AI engineer, which is the next step up from “prompt engineer,” according to its proselytizer Shawn @swyx Wang. He’s created a nifty diagram showing where AI engineers fit into the wider AI and development ecosystems: Via swyx. A large language model (LLM) is the core technology for an AI engineer. It’s no coincidence that both LangChain and LlamaIndex are tools that extend and complement LLMs. But what other tools are available to this new class of developer? The best diagram for an LLM stack I’ve seen so far is from the VC firm, Andreessen-Horowitz (a16z). Here’s its view of an “LLM app stack”: Via a16z; Click image to view full-size. Needless to say, the most important thing in an LLM stack is the data. In a16z’s diagram, that’s the top layer. The “embedding model” is where the LLM

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