Understand the infrastructure, systems, and engineering tradeoffs behind real-world AI.
| Platform |  | Pricing | Freemium | Publishes | Twice weekly |
|---|---|---|---|---|---|
| Issues | 181 | Founded | 3 years ago | Last Issue | 19 days ago |
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aiforswes.comLatest Issues
Don't Tokenmax—Do This Instead
There’s been an interesting push recently for “tokenmaxxing”, or the idea that burning through more tokens means an engineer has been more productive. The thought process is more tokens mean more AI use, which means getting more done and sa...
Decoupled DiLoCo: How Google Is Enabling Multi-Region, Distributed LLM Pretraining
Large-scale LLM pretraining is a notoriously complex and resource-intensive process. Training these models can involve up to hundreds of thousands of AI accelerators being colocated. This physical requirement ensures high-bandwidth cabling...
Understanding Open Model Licenses
Google recently released Gemma 4, their next iteration of their small, open models with multimodal capabilities. The release was met with a lot of praise for the model’s performance, but more importantly, Google was praised for switching fr...
The Difficulties of Scaling Autoresearch | AI for Software Engineers 83
And agentic engineering's scaling impact on the software development and the internet
Hi everyone!
20 Years of Code Optimized in Two Days | Weekend Reads 4
Your AI reading list 03-15-2026
Welcome to the weekly reading list! This is how I keep up with AI news and deepen my understanding of the topics that matter for building production systems. I focus on primary sources and authors I trust to...
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ML infra & agents at Google. Pragmatic Optimist. Helping engineers build AI intuition.
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