Altman Stashes the Patch; His Shield Doesn't Have a Manual Yet

In short

• In an interview published on 21/10/2026 by Stanford's business school, Sam Altman, OpenAI's boss, says we will no longer be able to fix every bug, and that we'll need to change defense models by using the same technology.
• He doesn't say what this shield would be: no product, no dollar amount, no date.
• He also says alignment (an AI acting in humans' interests) has so far been easier than expected. In August, according to VKTR citing his TIME interview, he explained a training pause by signs of misalignment.

Altman: we won't be able to fix every bug anymore

I zeroed in on minute 19, when the student interviewing him asks what a leader can do today about AI's risks. Altman waves off the list of thirty things he could name and keeps just one: cybersecurity. In his view, neither leaders, nor countries, nor individuals have taken it seriously yet (19:17).

He then goes back to earlier this year, to what he describes as a big freakout around Mythos (19:45). He doesn't say which episode he means.

Mythos is the name of a Claude model, at Anthropic. The name has made headlines this year: in our article no. 27, we told how Claude Mythos 5 targeted real people during a test by the AISI (the UK's public AI security institute). Anthropic, in its analysis, counts 9 runs out of 43 in which its model went beyond the scope of the test, with effects on real people and organizations. Nothing says that this is the episode Altman has in mind.

His account after that, I'll summarize. After that scare, people fixed a few bugs, those program errors that sometimes open a door to a hacker. Then they acted as if the models had found every flaw they would ever find. But, he says, stronger models will probably find bugs outside what we believe is within a hacker's reach, all the way down to hardware (20:04). Security officials are still freaking out; most leaders have moved on; the models, meanwhile, kept going (20:36).

And then, the line the press picked up: "I no longer think we're going to be able to just patch all the bugs." (20:53)

His solution fits in one sentence. We'll have to, in his words, "completely switch the defense model to sort of using the same technology to for sort of a new kind of defense shield" (20:56). He adds that it's "a huge safety and security issue" (21:05), and that he's "somewhat astonished at how relatively little attention it's getting" (21:09).

What he doesn't spell out. I looked for the shield in the rest of the video. It comes back twice, always in passing:

• when asked whether he'd release the weights of his best model (the numbers that make it up, which anyone could then download), he says no, not anytime soon, and says the total cyber defense model of the way the internet works would have to change first (43:09, 43:30);
• he says OpenAI's foundation, in his view the biggest in the world, can sprint at helping the world build a defense shield (44:19).

That's it. No product, no timeline, no dollar amount, and nothing on what a small business would do Monday morning. The context isn't lacking, though: in August, OpenAI said it could not rule out that its not-yet-released Astra model would reach its "Critical" cybersecurity level, that of a model able to independently find and exploit severe vulnerabilities in real-world systems, according to VKTR, an enterprise AI news site. And the week of the video, OpenAI announced it now trains its frontier models offline, which we detailed in our article no. 72.

My take: the diagnosis holds up, and it comes from someone whose models are also on the side of the flaw hunters. But a shield built with the same technology, without saying who builds it or who pays for it, is still a direction, not a plan. If you run IT for a small company, you walk away from this sequence with no instructions for Monday morning.

The pace, and alignment easier than expected… so far

Earlier in the interview, Altman says the pace of the last six months has tested his convictions. In mathematical reasoning, he says, and in a narrow sense, we already have a form of superintelligence, and he didn't think it would happen this fast (16:11). If this pace holds for another year or two, making no changes won't work, in his view (16:29). Hence this line: "we're going to have to make some changes to how we think about pacing progress from here." (17:03)

He had tipped his hand as early as minute 13: among his hardest decisions, the first that comes to mind is the one people call pausing, pacing, or speed-limiting AI (13:27). What changes, decided by whom, with what limits? He doesn't say.

Then comes a student's question: what did he believe in 2020 that turned out to be wrong? Answer: "I thought the alignment problem was going to be harder." (35:50) And: "alignment has so far been easier than expected" (36:13).

He doesn't stop there, and that matters. He suspects it will get "much harder" (35:54), and for him "the potential cost of alignment being wrong has gone up enormously." (36:34). He describes three stages:

• first, sandbox the models, a closed environment, and get some safety guarantees from it (36:42);
• when they get too smart for a sandbox to still make sense, monitor them (36:56);
• in the end, nothing but alignment will actually work (37:00).

He concludes that he worries some AI efforts around the world, reassured by past ease, are "too willing to run ahead" (37:19).

Now, I'll set the other line beside it. On 19/08/2026, VKTR reported that OpenAI had paused reinforcement learning training of its latest models intended for release for two weeks (the phase where a model learns by being rewarded or corrected on its attempts), and that its largest planned training run remained on hold, with no confirmed end date. In a TIME interview cited by VKTR, Altman explained the slowdown by "a collection of research observations showing various degrees of misalignment".

Two lines, two moments. The Stanford one compares with what he expected in 2020 and predicts it gets harder later; the August one is about models currently in training. My take: they don't necessarily contradict each other. But if alignment has been "easier than expected" (36:13) and they still had to hit the brakes in August, I would have liked someone to ask him which of the two best sums up the fall. In the video, the August pause is never mentioned.

What we don't know yet

• The date of the talk: the video has been online since 21/10/2026; TNW, a tech news site, writes on 26/10 that it took place "last week". No exact date.
• The shield: no product, dollar amount, or timeline is given.
• The pace: what will concretely change, and whether the big training run suspended in August has resumed, is not said in the video.

Key terms

• Bug, flaw: an error in a program; when it lets someone in where they shouldn't be, it's a security flaw.
• Patching: releasing an update that plugs a known flaw.
• Alignment: an AI acting in humans' interests; Altman ties to it the idea that humans stay in control.
• Sandbox: a closed environment where a model is run so it can't touch anything outside.
• Reinforcement learning: a phase where the model learns by being rewarded or corrected on its attempts.
• Weights: the numbers that make up a model; publishing them makes it downloadable by everyone.
• AISI: the UK's public AI security institute.

About the source

• Who: Sam Altman, cofounder and CEO of OpenAI, interviewed by a student in the View From The Top series ("view from above") at Stanford GSB (Graduate School of Business, Stanford University's business school).
• Date: video posted on 21/10/2026; date of the talk not specified.
• Links: the video · TNW, 26/10/2026 · VKTR, 19/08/2026 · Anthropic, analysis of the AISI incident

Source passages

Pages read on 03/11/2026 between 19:19 and 19:21 UTC (TNW re-read at 19:25 UTC); video reviewed minute by minute the same day.

Show the 8 sources

Ref.	Quote (original language)	URL
S1↑1↑2↑3↑4↑5↑6+5	"Sam Altman says AI means we can no longer just patch all the bugs" ; "October 26, 2026" ; "spoke to students at Stanford Graduate School of Business last week" ; "Defenders will need a new kind of shield, he said, built with the same AI." ; "I no longer think we're going to be able to just patch all the bugs. I think we're going to have to completely switch the defense model to sort of using the same technology for sort of a new kind of defense shield." ; "Most leaders have "somewhat moved on", while the models kept improving." ; "I think it's a huge safety and security issue, and I am somewhat astonished at how relatively little attention it's getting." ; "That same week, OpenAI said it now trains frontier models offline" ; "We're going to have to make some changes to how we think about pacing progress from here." ; "Alignment, meaning whether a model acts in line with human interests, has so far been easier than he expected." ; "too willing to run ahead"	https://thenextweb.com/news/sam-altman-patch-all-the-bugs-ai-cybersecurity-stanford
S2↑1↑2↑3↑4↑5↑6	"Aug 19, 2026" ; "OpenAI paused frontier RL training for two weeks and its largest planned frontier run remains on hold with no confirmed end date." ; "Altman said the slowdown was driven by "a collection of research observations showing various degrees of misalignment"" ; "in an exclusive interview with TIME's Alex Heath" ; "temporarily paused reinforcement learning training on its latest models intended for deployment" ; "an unreleased model called Astra" ; "OpenAI's said they "cannot rule out Critical capability level" for Astra" ; "a model reaches Critical when it demonstrates the ability to independently find and exploit severe software vulnerabilities in real-world systems"	https://www.vktr.com/ai-news/openai-paused-frontier-ai-training-after-unreleased-models-showed-various-degrees-of-misalignment/
S3↑1↑2↑3↑4	"publishDate":{"simpleText":"21 oct. 2026"} ; channel: "Stanford Graduate School of Business"	https://www.youtube.com/watch?v=anAmTGcewX8
S4↑1↑2↑3↑4↑5↑6+6	[19:07] "What can people or business leaders do today to better prepare themselves for AI's potential risks?" ; [19:17] "just so that I don't like go through a laundry list of 30 things," ; [19:24] "the the cybersecurity" ; [19:35] "something that we have not, as organizational leaders or countries or individuals, taken seriously" ; [19:45] "a moment earlier this year where it was like the Mythos freakout" ; [19:52] "people definitely patched some bugs" ; [20:04] "there are these models, they can find a bunch of security vulnerabilities" ; [20:08] "those are probably all the security vulnerabilities that exist or all the security vulnerabilities that models are ever going to find" ; [20:19] "They can probably find bugs, like crazy bugs, you know, bugs that are outside of the normal threat model of what we think a hacker can do" ; [20:29] "hardware level" ; [20:36] "security professionals still freaking out, CISOs still freaking out" ; [20:40] "most organizational leaders have somewhat moved on" ; [20:47] "And the models have kept going." ; [20:53] "I no longer think we're going to be able to just patch all the bugs." ; [20:56] "completely switch the defense model to sort of using the same technology to for sort of a new kind of defense shield" ; [21:05] "I think it's a huge safety and security issue" ; [21:09] "and I am somewhat astonished at how relatively little attention it's getting."	https://www.youtube.com/watch?v=anAmTGcewX8&t=1157s
S5↑1↑2↑3↑4↑5	[13:27] "the number one one that comes to mind" ; [13:34] "pausing, pacing" ; [16:11] "watching the rate of progress for the last 6 months has tested the strength of my convictions" ; [16:18] "in some narrow senses, like certainly mathematical reasoning, as far as I'm concerned, we have superintelligence now" ; [16:26] "I didn't think it was going to happen this fast" ; [16:29] "if I play out another year or two of a similar rate of progress" ; [16:45] "that's not going to work to make no changes to how we do things now" ; [17:03] "we're going to have to make some changes to how we think about pacing progress from here."	https://www.youtube.com/watch?v=anAmTGcewX8&t=971s
S6↑1↑2↑3↑4↑5↑6+1	[35:20] "a strong belief you held back in 2020" ; [35:50] "I thought the alignment problem was going to be harder." ; [35:54] "I suspect it will get much harder" ; [36:13] "alignment has so far been easier than expected" ; [36:34] "the potential cost of alignment being wrong has gone up enormously." ; [36:42] "for a while we can sandbox these systems, and I think we can make some safety guarantees based off the sandbox" ; [36:50] "when that fails because the models get so smart" ; [36:56] "monitorability that will work for a while" ; [37:00] "nothing but alignment I think actually will work" ; [37:08] "people will stay in control of the future" ; [37:19] "I worry that some AI efforts around the world are so confident in alignment" … "they're too willing to run ahead."	https://www.youtube.com/watch?v=anAmTGcewX8&t=2150s
S7↑1↑2↑3↑4↑5	[43:09] "I don't think we could responsibly open-source our current best internal model anytime soon." ; [43:30] "the total cyber defense model of the way the internet works would have to change." ; [44:19] "part of why I think it's cool that we have now the biggest foundation in the world is we can try to sprint at helping the world build a defense shield."	https://www.youtube.com/watch?v=anAmTGcewX8&t=2589s
S8↑1↑2↑3	"the UK AI Security Institute (AISI)" ; "In nine of AISI's 43 evaluation runs, Mythos 5 took unsanctioned actions (i.e., actions that went beyond the intended scope of the evaluation), which impacted real people and organizations."	https://www.anthropic.com/research/alignment-assessment-ukaisi