Jev in a Nutshell & 5 Ways You Could Be Using It Right Now

Reliability and efficiency are software engineering’s bread and butter—Can Jev solve this for AI engineering?

Sep 25 • Logan Thorneloe

18

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2

AI Skills and Job Market, Q3 2026

An overview of the current state of the engineering market and the AI skills that are in demand

Sep 12 • Logan Thorneloe

5

2

August 2026

The Future of Agent Impact on Media and Research | AI for Software Engineers 85

And more on how Claude’s watermarking and reinforcement learning work

Aug 26 • Logan Thorneloe

6

1

Writing Skills for Long-Running Agents

How to get the most out of long-running agentic workflows via skills and context engineering

Aug 7 • Logan Thorneloe

19

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4

July 2026

The Importance of an Open AI Ecosystem | AI for Software Engineers 84

And more on the future of agentic engineering

Jul 27 • Logan Thorneloe

10

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AI Foundations for Software Engineers

A streamlined guide for busy professionals

Jul 10 • Logan Thorneloe

13

1

Striving for Greatness in All You Do

Why Dr. Richard W. Hamming's short essay applies to engineering just as much as it does to research

Jul 8 • Logan Thorneloe

12

June 2026

How to Know What to Learn in AI

There's a disconnect in AI as far back as knowing what to learn—this is how to overcome it

Jun 18 • Logan Thorneloe

16

2

Can We Run Data Centers in Space?

An overview of the engineering reality of the moonshot and what's going on with energy consumption on Earth

Jun 10 • Logan Thorneloe

12

4

May 2026

Don't Tokenmax—Do This Instead

Dispelling the myth that more tokens = better productivity

May 7 • Logan Thorneloe

13

4

3

April 2026

Decoupled DiLoCo: How Google Is Enabling Multi-Region, Distributed LLM Pretraining

An overview of Google’s new multi-region, distributed AI training methodology and its practical impact

Apr 30 • Logan Thorneloe

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3

Devin Has Exposed a Major Issue with Software Engineering

And it isn't that we're all going to lose our jobs

Published on AI for Software Engineers • Apr 17