I didn't want to agree but…I do. I love that Grok shows its "thinking," helping you see its data sources and how it's reaching conclusions. I asked "Is Matt Asay for or against open source?" bc it seems like something ppl often get wrong. Tl;dr answer was spot on:
OPEN SOURCE
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GenAI Agents Hub: LangChain LangGraph Multi-Agent Systems
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GenAI Agents Hub A comprehensive collection of GenAI agent implementations, from simple bots to complex multi-agent systems. Built with LangChain and LangGraph, this repository empowers developers across business and creative applications. Start building your agents:
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More Content Coming Soon with GitHub Repository Updates
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It will take time, but yes, there will be more :). In the meantime, I added lots of bonus content to the GitHub repo you may like: https://
github.com/rasbt/LLMs-fro
m-scratch
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Tool Ahead of Time: JSON-based Tool Calling for LangChain
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Tool Ahead of Time An interesting community package – using JSON generation & parsing to enable tool calling for LangChain models that don't currently support it. Enables usage with `create_react_agent` Check it out
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TorchInductor Dynamic Kernel Generation Advances Tensor Compilation
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TorchInductor supports dynamic kernel generation, and is likely the state of the art at symbolic Tensor type systems. long gone are the days of static shape tensor compilers
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Choose Your Own Adventure: Building LLMs with JAX
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You probably could choose your own adventure! . Eg @_nerdai_ coded the first book in Jax https://
github.com/nerdai/llms-fr
om-scratch-rs
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2025 LLM Roadmap: From Fundamentals to Production Applications
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Here’s the 2025 LLM roadmap 1. Code and train your own LLM to really understand the fundamentals
2. Train models more conveniently using production-ready libraries
3. Learn about the big-picture considerations for real-world LLM/AI apps -

Embedding Fine-Tuning Guide for RAG Systems
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RAG Embedding Fine-Tuning Guide A practical guide demonstrating embedding model fine-tuning for RAG systems, featuring LangSmith monitoring and RAGAS metrics for performance evaluation. Check out the complete implementation https://
github.com/apatti/AIEBoot
camp/blob/main/09_Finetuning_Embeddings/Fine_tuning_Embedding_Models_for_RAG_using_RAGAS.ipynb
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PyTorch Democratizes Fast Kernel Writing Challenge
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we've been working on democratizing fast kernel writing on the @PyTorch team. try the challenge, either you or your AI!
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Building IntelliJ AI Assistant with Deepseek and LangChain
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IntelliJ AI Assistant Plugin Learn to build a coding assistant that integrates Deepseek AI into IntelliJ IDEA using LangChain. The plugin generates code and explains it in real-time, featuring Java Plugin DevKit and native IDE integration. Watch the tutorial now
