







A practical guide to building successful LLM products, covering the tactical, operational, and strategic.
The Ultimate Guide to Fine-Tuning LLMs from Basics to Breakthroughs: An Exhaustive Review of Technologies, Research, Best Practices, Applied Research Challenges and Opportunities (Version 1.0)
LLMs are not like manufacturing machines - Ross Wintle
LLMs are not just machines. They are machine-building machines! This comes with way more responsibility. And understanding it may change how you use them.
Training great LLMs entirely from ground up in the wilderness as a startup — Yi Tay
Chronicles of training strong LLMs from scratch in the wild




The most important thing when working with LLMs
Blog post: The most important thing when working with LLMs by Steve Klabnik
Dan Shipper 📧 on Twitter / X
this is true and is a big reason why you don’t need to be a highly technical researcher to use LLMs in surprising and novel ways https://t.co/TuxNzXzToU— Dan Shipper 📧 (@danshipper) July 27, 2025
Brandon Stewart on Twitter / X
1/ New @Nature! We study how powerful institutions shape the information environment for LLMs. Commercial LLM training is opaque, so we trace a path from state-coordinated media -> training data -> model responses. pic.twitter.com/5LdFvzbFaf— Brandon Stewart (@b_m_stewart) May 13, 2026

Extensible Software in the age of LLMs | Jeremy Morrell
Solid core + capability-based sandboxes + LLMs = Users with superpowers

One year as an AI Engineer: The 5 biggest misconceptions about LLM reliability I've encountered
535 votes, 59 comments. After spending a year building evaluation frameworks and debugging production LLM systems, I've noticed the same…
How LLMs Actually Work
A from-the-ground-up walkthrough of how modern LLMs work, from tokens to transformer blocks to the next-token loop
LLM Architecture Gallery
A gallery that collects architecture figures from The Big LLM Architecture Comparison and related articles, with fact sheets and links back to the original s...

Notes on how to use LLMs in your product.
Pretty much every company I know is looking for a way to benefit from Large Language Models. Even if their executives don’t see much applicability, their investors likely do, so they’re staring at the blank page nervously trying to come up with an idea. It’s straightforward to make an argument for LLMs improving internal efficiency somehow, but it’s much harder to describe a believable way that LLMs will make your product more useful to your customers.
