AI Engineering Library

AI Engineering is developing quickly. We are often asked about the resources we can recommend to learn more. This is a non-exhaustive list of what we have found useful/interesting.

Prompting

Agents

  • Building Effective Agents, blog post, by Anthropic
  • Hugging Face Agents Course, course
  • How We Built Ellipsis (or: Lessons from 27 months building LLM coding agents), blog post, by Nick Bradford

LLMOps

  • What We Learned from a Year of Building with LLMs, by Eugene Yan, Bryan Bischof, Charles Frye, Hamel Husain, Jason Liu and Shreya Shankar, Part 1, Part 2, Part 3
  • Traceability and Observability in Multi-Step LLM Systems, webinar by Marc Klingen
  • Data Flywheels for LLM Applications, blog post, by Shreya Shankar
  • Latency optimization, cookbook, by OpenAI
  • The OSS LLMOps Stack, page by LiteLLM and Langfuse

Evaluation

  • Evaluating the Effectiveness of LLM-Evaluators (aka LLM-as-Judge), blog post, by Eugene Yan
  • Your AI Product Needs Evals, blog post, by Hamel Husain
  • Creating a LLM-as-a-Judge That Drives Business Results, blog post, by Hamel Husain
  • Evaluating Voice AI Agents, blog post and video, by Marc Klingen and Brooke Hopkins

LLM 101

Beginner-level, non-technical resources

  • Intro to Large Language Models talk by Andrej Karpathy
  • How I use LLMs talk by Andrej Karpathy

News

Libraries & Tools

While there are lots of libraries and tools out there, these are the ones we see most often among Langfuse users

  • Vercel AI SDK, TypeScript toolkit designed to help developers build AI-powered applications with React, Next.js, Vue, Svelte, Node.js, and more.
  • LiteLLM, use 100+ LLMs as a drop in replacement for OpenAI GPT models, either library or proxy.
  • Instructor, library for structured outputs with LLMs.
  • Popular frameworks to get started quickly with RAG/Chains/Agents: LangChain, LlamaIndex, Haystack
  • Search: Exa, Firecrawl
  • Browsing: Browserbase, Browser-use
  • Code sandboxes: E2B

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