AI for Software Engineers
Logan ThorneloeBreaking down AI concepts every software engineer should understand. Spans machine learning foundations, systems engineering, research, infra, and more.
| Platform |  | Pricing | Freemium | Publishes | Twice weekly |
|---|---|---|---|---|---|
| Issues | 180 | Subscribers | Read | aiforswes.com |
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Latest Issues
Recent posts by this newsletter. Browse the email archive.
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
20 Years of Code Optimized in Two Days | Weekend Reads 4
Your AI reading list 03-15-2026
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Authors
The writers behind this newsletter.
ML infra & agents at Google. I break down AI concepts every engineer should understand.
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