Columns - SiliconNoon (Page 3)

The Stack

The Take — An agent grading its own homework is an alibi, not proof

The most important product promise made this week isn't that agents write better code. It's that you can stop reading it. Cognition's pitch for wiring GPT-6 Astra into Devin, and Perplexity's parallel claim that it checks in less on a production answer engine, both sell the same trade: human review out, agent-produced evidence in. I think that trade is being made in the wrong direction, and that this week's other stories explain exactly why. The reason isn't that automated tests are unreliable

The Everyday

The Take — Meta fixed the prompt, and that is the confession

Meta's fix for its prying assistant is a prompt rewrite, and that is the tell. The suggestion that started this — "Who's the child passenger?" — is gone. The system that assembled a stranger-grade dossier about a woman's children from her own years of public posts is still there, still switched on, and still Meta's stated plan for its assistants. Meta patched the sentence, not the capability, and it expects the sentence to be the story. I think the reverse is true. The intrusive question was ne

The Guardrails

How to — decide what an AI agent may do

You're about to give an assistant access to something — a repo, a mailbox, a database, a shell. Twenty minutes of thinking now decides whether that ends in a useful afternoon or in an incident report. This is the routine: name the job, grant the minimum, cap the damage, and never let the model be the thing that says no. The reason this needs a routine is that the failure isn't exotic. An agent with your inbox and a send button doesn't need to be hacked to hurt you; it only needs to be persuaded

The Guardrails

The Take — A 'voluntary slowdown' is levelling up, not down

When OpenAI's chief scientist asks for "voluntary slowdowns to become commonplace," the word doing all the work is commonplace. A voluntary slowdown that only OpenAI observes is a marketing asset. A slowdown that becomes commonplace is not a pause at all — it is a levelling up. That is the ask, and it deserves to be judged as one. Not as a company being brave, and not as a company being cynical, but as a proposal about how binding rules get made in an industry where nobody has to agree to anyth

The Guardrails

How to — spot prompt injection in a product you use

By the end of this you'll be able to answer one question about any AI product you rely on: if a stranger hid a sentence inside something your assistant reads tomorrow, what is the worst thing that could happen, and would you notice? Six moves, no security background required. Prompt injection is not a hack of the software — it's text. Somebody writes instructions into a page, a document, an email or a file name, your assistant reads that text while helping you, and follows it. The reason this i

The Guardrails

The Take — OpenAI's disclosure framework will fail, and the company knows it

OpenAI says it is "working on a framework" for disclosing AI misalignment incidents. I think the framework is worthless as written, and that this is obvious to the people writing it — which is the most damning thing about it. A disclosure rule a company writes about itself, enforces on itself, and can revise whenever it likes is not a disclosure rule. It is a press release with a deadline. The pattern it is meant to fix is now three incidents deep, and each time the sequence has been identical:

The Frontier

The Take — Calling Astra AGI is flippant. The field's silence is worse.

M.G. Siegler is right that calling GPT-6 Astra "AGI" is marketing. He is wrong that OpenAI alone is to blame. When Greg Brockman stood in front of reporters last Thursday and told them "we are now in the AGI era," he was performing exactly the move Siegler calls flippant — but he was performing it on a stage the rest of the frontier-AI field had abandoned to him. Nobody serious has bothered to define the term in a decade, and the bill is now due. I think the AGI argument is the wrong argument.

The Frontier

How to — tell a real benchmark from a marketing one

Every model launch ships a benchmark table. Almost every one of them is, in some sense, true. None of them are telling you the same thing. The job is not to find a fake benchmark — most aren't fake — but to find the one whose number you can carry into a decision. Here is the routine. Benchmarks are the scoreboard the field runs on, and the scoreboard is under strain. Terminal-Bench 4.0 spent recent releases removing saturated tasks and fixing broken ones; SWE-bench had to be split into a "Verif

The Arena

The Take — Uber's war on robotaxis is a toll booth, not a conscience

Uber is not trying to stop robotaxis. It is trying to make sure that when they arrive, they arrive on Uber's platform and pay Uber a cut. Every piece of the company's new labor politics — the union alliances, the workforce-transition language, the 85 percent rule its lobbyists are pushing in New Jersey — is aimed at that outcome, not at slowing the technology down. I think the distinction matters more than it sounds, because it changes who we should root for. If this were a company making commo

The Arena

The Take — SoftBank's $5.5B warrants prove AI infrastructure is funding itself

SoftBank just handed OpenAI $5.5 billion in stock warrants to stay in a data center lease, and the most important word in that sentence is "just." This is not a customer buying compute. This is a landlord paying its tenant to remain a tenant, then preparing to sell the resulting revenue stream to public market investors as if it were organic demand. The AI infrastructure boom is real. The financing underneath it is more circular than anyone with an IPO to file wants to admit. The facts, as we c

The Frontier

How to — read a model launch without getting spun

The first 90 minutes after a frontier model drops, every claim in the launch post is competing for your attention with another claim that contradicts it. The way to read a model launch is not to chase the headline number; it is to walk through the same five things the people who actually use these models look at, in the same order, every time. Here is the routine. A "model launch" in 2026 is rarely one model. It is a small stack of claims, each with a different shelf life: a new checkpoint, a n

The Guardrails

The Take — The Anthropic–Pentagon ruling isn't a win for one lab. It's a red line for all of them

A federal judge just told the US government it cannot punish an AI company for refusing to let its model kill people without a human in the loop. That sentence is bigger than Anthropic, bigger than the $200 million contract at the center of the fight, and bigger than Pete Hegseth's bruised ego. It is the first time a court has converted an AI lab's stated safety principle into something the Constitution actually defends — and the next two quarters will reveal whether OpenAI and Google treat that

See all