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The question isn’t if AI will transform your business, but how to use it to maintain your competitive edge. Vercel CTO Malte Ubl shows how companies can understand AI’s fundamental shifts, adapt their skills, and integrate AI into their businesses.

Lightweight coding agent that runs in your terminal - openai/codex

A blog post covering tips and tricks that have proven effective for using Claude Code across various codebases, languages, and environments.

What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers? - humanlayer/12-factor-agents

A comprehensive guide to voice AI in 2025

Stanford CS25: Transformers United Since their introduction in 2017, transformers have revolutionized Natural Language Processing (NLP). Now, transformers ar...

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Model architectures, data generation, training paradigms, and unified frameworks inspired by LLMs.

Best-practices on how to fine-tune OpenAI models.Notes, links, and more resources available Here: https://parlance-labs.com/education/fine_tuning/steven.html...

My guest today is Nat Eliason.Nat teaches the “Build Your Own Apps with AI” course which made $200K in just 7 days. I’m one of his 1,000+ students so natural...

I’ve been playing with Anthropic’s MCP for a little while now, and I have a few gripes.

Tips and tricks for getting the most out of Cursor AI coding assistant while avoiding its pitfalls.

Blindspots in LLMs I’ve noticed while AI coding. Sonnet family emphasis. Maybe I will eventually suggest Cursor rules for these problems.

Learn how to build an MCP CLI client to leverage the versatility of Anthropic's protocol without the limitations of a desktop client.

A surprisingly common complaint I see from developers who have tried using LLMs for code is that they encountered a hallucination—usually the LLM inventing a method or even a full …

The example-driven, practical walkthrough of Large Language Models and their growing list of related features, as a new entry to my general audience series o...

This post outlines the common components of a generative AI platform, what they do, and implementation considerations. It'll start from the simplest architecture and progressively add more components: context construction, guardrails, router, gateway, cache, agentic workflows, orchestration, and observability.

Join me to Master Python for AI Projects 👉 https://python-course-earlybird.framer.website/Get data science/ AI insights in your inbox 👉 https://thu-vu.ck.p...

Title: From ML Engineering to AI EngineeringDate: June 27, 2024Duration: 1 HRSPEAKERChip HuyenVP of AI & OSS, Voltron DataMODERATORAlejandro SaucedoDirector ...

On today’s episode of The Pragmatic Engineer, I’m joined by Chip Huyen, a computer scientist, author of the freshly published O’Reilly book AI Engineering, a...

A TL;DR version of Andrej Karpathy's "Deep dive into LLMs like ChatGPT" video.

Methods and Strategies for Building and Refining Reasoning Models

Learn about the importance of chunking for RAG, choosing optimal chunk sizes, text splitting methods, and advanced smart chunking strategies to enhance your RAG system's performance.

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

Few great and free resources to learn about RAG and its usage in Generative AI.

Large language models (LLMs) may not be replacing developers anytime soon, but can still be of use in the design process.

Supabase is an open source Firebase alternative providing all the backend features you need to build a product.