The AI-as-Normal-Technology view of loss-of-control incidents

A middle ground between the cybersecurity and AI safety communities

Sep 14 • Sayash Kapoor and Arvind Narayanan

216

41

33

August 2026

AI agents can't yet do open-ended AI research

Early evidence from two case studies

Aug 5 • Sayash Kapoor and Arvind Narayanan

182

23

25

July 2026

What will be left for us to work on?

My keynote at ICML 2026

Jul 13 • Arvind Narayanan

339

28

58

Up the Stack: How AI’s Escape From the Commodity Trap Risks Enterprise Lock-in

Critics and boosters are both looking in the wrong place

Jul 9 • Arvind Narayanan

171

23

29

June 2026

Why AI hasn’t replaced software engineers, and won’t

Coding agents as normal technology

Jun 11 • Arvind Narayanan and Sayash Kapoor

592

87

109

May 2026

Did Google’s AI agents really build an operating system for $916?

The importance of independent evaluation

May 22 • Sayash Kapoor and Arvind Narayanan

144

24

11

Do AI Risks Require Extraordinary Government Intervention?

Let’s not skip the hard work of AI governance

May 21 • Sayash Kapoor and Arvind Narayanan

85

8

19

April 2026

Open-world evaluations for measuring frontier AI capabilities

Introducing CRUX, a new project for evaluating AI on long, messy tasks

Apr 16 • Sayash Kapoor and Arvind Narayanan

97

7

14

February 2026

New Paper: Towards a science of AI agent reliability

Quantifying the capability-reliability gap

Feb 24 • Sayash Kapoor and Arvind Narayanan

327

36

71

AI Won’t Automatically Make Legal Services Cheaper

Applying the AI as Normal Technology framework to legal services

Feb 12 • Justin Curl, Sayash Kapoor, and Arvind Narayanan

84

13

15

January 2026

Fact checking Moravec's paradox

The famous aphorism is neither true nor useful

Jan 29 • Arvind Narayanan

172

10

24

September 2025

A guide to understanding AI as normal technology

And a big change for this newsletter

Sep 9, 2025 • Arvind Narayanan and Sayash Kapoor

227

29

40