advanced RAG techniques like RAPTOR and using Clues

Cursor, RepoAgent, Aider, and some more coding agents - overview and interesting architectural concepts

Technical review of the new Realtime API introduced on the dev day

How to migrate the llm provider in your AI app safely

If you need to build an llm-app that uses an open-source llm, this episode is for you. Intermediate level

end to end guide on how to get started and deploy to production your llm app

Build LLM-app with legal documents that have many references and domain verbiage

Getting started with LangGraph, the most popular multi agent framework

Utilize no-code tools for fast POCs

Review of why and how to build a multi-agent system. Assaf is Head of R&D @ Wix and GPT-researcher open source creator.

everything about adopting open source code and models for your llm app

build trust with users and stakeholders - transparency and explainability, reliability and consistency (how to fail safely), automation vs user control. how to evaluate with uncertainty, prompt engineering, effective bug reports

examples and practices of advanced agents, and use of LangGraph for effective tool usage by agents

how to solve latency issues with minimal compromise on quality and cost

The 12 most common challenges around building an effective RAG pipeline and the best practices for solutions

exploring the reranker component in the 2 stage retrieval system

how to define effective requirements for llm apps, and first steps after going to production

What are transformers, why it is so expensive to train a Transformer-based model and what is the architecture of the future LLMs

LCEL, LangGraph, LangSmith

Indexing knowledgebases with KG for RAG applications

ragas framework for evaluating unstructured retrievals and generations

Retrieval Augmented Generation process, Llama index vs LangChain, indexing

OpenAI DevDay announcements recap

Evaluating LLMs and AI pipeline in dev and production environments. How to work with datasets