Columns - AI Midday

The Guardrails

The Take — OpenAI's safety firings are a test only OpenAI can grade

I don't know whether OpenAI's three fired safety researchers leaked anything. Nobody outside the company does — and that is my take. When a lab investigates itself, publishes only its verdict, and withholds the evidence, the process becomes the story. By that process, OpenAI has already failed the test — not because the firings are necessarily wrong, but because in a self-policing industry, the company made itself the only witness, the only investigator, and the only judge, then told us to take

The Everyday

How to — cut an AI app off from your accounts

You connected an AI tool to your mail or calendar once, used it for a week, and stopped thinking about it. By the end of this, every connected-apps list you own will show only apps you can name a reason for — and you'll know exactly how to pull the plug. What you granted wasn't a one-time peek. When you tapped "Allow" on a consent screen, you issued the app a standing key: a bundle of permissions, which the standards call a scope, that keeps working while you're not looking. That's the point of

The Guardrails

The Take — Meta's tax credit is a subsidy nobody voted for

The US is having its loudest argument yet about who pays for AI, and it is having it about the wrong bill. Congress voted 417 to 3 to make data centers pay for their own power. Meanwhile, on the other channel — the tax code — a single company moved $6.7 billion of its federal tax bill into a line item the public never debated. I think that is the more consequential number of the two, and the more fragile one. Start with what the reporting establishes, because the facts are checkable and they ch

The Frontier

The Take — A refusal rate is a capability score

Artificial Analysis put out a serious benchmark this week and buried its most interesting result in a second chart. I think that is the wrong way round. A model that declines 38 percent of a job does not have less capability on the other 62 — it has a policy. The Cyber Index's headline score turns that policy into a capability gap, silently, and the headline is the thing that spreads. Here is the mechanism, because this is an arithmetic complaint, not a philosophical one. The index is an equal-

The Stack

How to — check an AI-generated citation before you rely on it

An AI-drafted citation can point at a real document and still misdescribe it — that is the failure mode a link check misses. Verification means opening the source and reading the sentence your citation is attached to. This is a job you can finish in an afternoon for a normal reference list, and it is the difference between using AI as a research assistant and signing your name to something you never read. 1. Separate the two checks — one is mechanical, one is not. There are two different ques

The Guardrails

The Take — Medicare's denial pilot has the burden of proof backwards

Medicare's AI prior-authorization pilot is being argued about as if the scandal were the algorithm or the bounty. I think the real defect is smaller, plainer, and more fixable than either: the program never has to prove a denial was correct, and the only party who can force the question is the patient. Flip that burden of proof — put the reviewer before the patient rather than after — and most of this fight evaporates. Start with the money, because that's where the argument keeps getting stuck.

The Stack

How to — keep your AI feature alive when a model is retired

Every model you call has a shut-down date, and most teams only learn it from a failed request in production. The dates are published months ahead. The breakage happens anyway. Treat retirement as a scheduled maintenance window rather than an emergency: know what you depend on, know your provider's clock, and have the replacement tested before the deadline arrives. 1. Inventory every model identifier you depend on — not just the one in your config. The model name is usually in more places than

The Guardrails

The Take — The chip ban's biggest hole is a rental agreement

Nscale's IPO filing has done what export controls could not: it put a number on the loophole. According to Financial Times reporting built on the company's US SEC filings, ByteDance accounted for 73% of Nscale's $33 million in 2025 revenue — and its access route was a rental agreement. Spring, a Singaporean subsidiary, contracted for 2,304 of Nvidia's B200 chips in a data center in Glomfjord, Norway, hardware that TikTok's parent cannot lawfully buy under US export controls. The company rents th

The Stack

Fastcrawl wants to be the web layer for AI agents — and it is priced like a utility

Every AI agent that needs to read the web runs into the same wall, and it is not the model. It is the page. A modern news homepage arrives as 400 to 900 kilobytes of markup wrapped around a few thousand words of actual text — navigation, adverts and script tags around the part worth reading. Handing that to a model wastes tokens and produces worse answers than the same text would have. So the operator either builds a scraping stack — headless browsers, session handling, retries, anti-bot evasion

The Arena

The Take — Give shopping agents a name, not a permission slip

Amazon cut Meta's Muse off from Amazon.com over the weekend, and by Monday the argument had settled into the usual shape: open web versus walled garden, scrappy agents versus the store that owns the shelf. I think that framing buries the only question worth arguing about. Amazon is right that an agent should have to say who it is. It is wrong that a merchant's consent should decide whether the person who owns that agent gets to buy something. Those are two different demands wearing one sentence,

The Stack

How to — cut your LLM bill without switching models

Your token spend keeps climbing, and the obvious fix — swap in a cheaper model — is the one you should try last. In a live AI feature, most of the waste isn't the price per token. It's paying full price for tokens the provider has already seen, and generating output tokens nobody asked for. Work the list in this order. The first three moves usually move the number more than a model swap would, and none of them cost you quality. 1. Find out where the tokens actually go. Before changing anythin

The Frontier

The Take — ICLR's flood is a credential problem, not a review problem

ICLR's submission counter passed 50,000 IDs before the abstract window closed on September 18, and by the time it did, the field had already produced its explanation: too many papers, not enough reviewers, cap the papers. I think the caps now in force — a 20-paper limit per author and a one-paper limit for authors whose teams contain no qualified reviewer — are treating a symptom, and that the symptom is downstream of a price nobody wants to name. A conference acceptance is not a publication. It

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