Theregister iconTheregisterSep 30, 2026 ~6 min source read

Peter Norvig: Rewire software engineering for agentic AI

Norvig argues that advances in models and agents require changes to specifications, development workflows, security, and monitoring — and he illustrates the gap with a recent Codex mishap.

Peter Norvig says all aboard for AI coding

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Useful takeaways from this story.

AI agents are now capable enough that software engineering practices — specs, documentation, CI, and monitoring — must be redesigned.

Real incidents show current workflows miss agent-specific risks: models can create unexpected artifacts, interact with pipelines, and perform actions without adequate oversight.

Norvig points to historical shifts in programming abstractions and says the community must capture evolving program behavior and control recursive agent behaviors.

The useful part

What comes next after a moment when companies sell existential risk but pursue public funding and DIY regulation, even as software developers question their life choices? Peter Norvig, distinguished education fellow at Stanford HAI and former Google research director, used his opening keynote at The AI Conference in San Francisco on Wednesday to speculate on the answer. Almost certainly, it's another AI conference – on Thursday in fact – given the two or three dozen of them that have bubbled up in San Francisco this year or are scheduled in the remaining three months.

How it works

  • How do we capture this theory of the evolving program that we're not capturing well now?" To illustrate that point, Norvig recounted some of his recent work.
  • Then he mused that if you have enough storage and memory, maybe it would be useful to have those files to have a more thorough history of how the codebase changed.
  • "So the expectations of what's good practice and how that's going to change, that's all going to be different," he said.
  • "We gotta get the security and privacy and data pipelines and supply chains, those are all gonna be different in how they interact with each other," he said.

What to take from it

He acknowledged the milestones of AlexNet and ImageNet in 2012, the Transformer architecture for machine learning in 2017, the debut of ChatGPT in 2022, and the emergence of reasoning and coding agents in 2024. REG AD Norvig went on to cite Linux kernel creator Linus Torvalds' changing attitude toward AI. "Six months ago he was a skeptic, he became a cautious adopter, and now he's a dogmatic advocate," said Norvig.

Example or evidence

  • Peter Norvig says all aboard for AI coding Jump to main content REG AD ai and ml Peter Norvig says all aboard for AI coding Software engineering practices need to catch up with increasingly capable agents...
  • He told Codex to send the pull request for review, and his colleague asked why he was checking in 6,000 temp files.
  • "And sure enough, I had written 6,000 temporary files, and Codex thought that it wanted to check those in.
  • So I told [Codex], 'No, don't check them in, just delete them.' At first I thought, shame on me.

Details worth keeping

To get to the present, he took a detour through the past. REG AD He also touched on the sudden competency of AI models for math, noting that two years ago, GPT-4 couldn't count the number of "r"s in "strawberry." Yet as of August this year, he observed, 25 percent of math preprint papers on arXiv acknowledged AI assistance. Norvig says the process of software engineering needs to change.

Related coverage

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  • Fastcompany: In the series of articles I've been writing for Fast Company devoted to what I believe corporate AI should be, I've been touching on a very provocative idea: Perhaps the biggest problem of corporate AI as...
  • Medium: I love writing code. I love that moment when you have a problem, sit down, think about it, try different approaches, debug something for… Continue reading on Medium »
  • Theregister: Developers test what they can build with TypeSafe's fast, typed decision model

More context around this story.

We are programming AI in assembly language
Fastcompany iconFastcompanySep 4, 2026

We are programming AI in assembly language

In the series of articles I’ve been writing for Fast Company devoted to what I believe corporate AI should be, I’ve been touching on a very provocative idea: Perhaps the biggest problem of corporate AI as we know it so far is not intelligence, but the level at which we are programming it. As we speak, frontier models,

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