AI-driven security defends at a fundamentally new speed: adversaries find vulnerabilities in seconds where it once took months, while organizations' time-to-detect remains days—so the security infrastructure of a year ago is wholly unfit for the year ahead.
Nikesh Arora argues AI collapses vulnerability-discovery time from months to seconds while average patch time is 55 days and detection/response is 4 days, making existing security infrastructure unfit for purpose. ✦ AI generated
Nikesh Arora · 20VC · 2026-08-06 · original ↗
starts at this moment · 36:57
“How are your enterprise customers reacting? Because this feels to me like the mother of all of I mean security sells on fear and this is terrifying.”
These things are finding vulnerabilities in split seconds and then turning around and building an attack on the back of that. So I think the the fundamental speed at which cyber attacks will happen and need to be defended changes... That is fundamentally not true. Now, we we found 14,000 vulnerabilities in open source in the last 14 weeks testing open source packets... The average time to detect and respond is 4 days. How are you going to get it down to a minute? So, it's not a fear problem. It's a capability problem. It's an infrastructure readiness problem.
verbatim transcript · starts at 36:57
36:53The amount of effort that goes the problem we have is like and I sorry to go back to the Whimo example because it's kind of I think it's the most obvious one out there. It took I I drove in the first sort of Google self-driving car. I don't know what I was thinking in 2009 when I used to work there. It was a Lexus with a bunch of cameras. It drove me from San
37:12Francisco to San Martin on the highway and my hands were not on the wheel and then I took the they told me at 11 p.m. to take the the wheel in my hands. as I was driving a quarter wall and I did and I sort of was more relaxed about saying, "Oh, maybe it's just going to figure it out when I make a wrong turn because it
37:28was so smart drove me." I was like, "No, dude. This does not drive when it turns off." So that was 2009. It's taken 14 years after that to get one with all the edge cases trained from machine learning perspective for us to rely on that as being the agency that we've given the agency that to that replacement. So I don't believe we're going to give 100% agency to use cases for some time. And
37:54for us to be able to do that, the amount of data collection and and context we're going to create is going to be humongous. Basically, you have to literally take every edge case in customer support, get into your AI brain of your organization so that you can start relying on AI instead of the human. So you're getting 80% right now. You're getting 80% of customer support solved. All the edge cases are waiting
38:14to be solved with AI. Then there is the for a given app how much of the value is purely in the model versus all the other thing and you're right for something like customer support we you know you're probably paying 10 or 15% of the revenue you're getting for intelligence and the rest of it is all the other it takes to make that intelligence actionable in the context of answering
38:34tickets. And one of the things we look at is just super interesting on the app level is the tokens as a percentage of total revenue and it varies from you know the sales forces the we were in intercoms stuff like that where it's you know sub plus or minus 10 15%. Obviously in coding and things like that it's 70 80% which means it's just raw intelligence and a mild harness and
38:55those are just very different. >> I think over the next 3 four years we won't be paying for intelligence we'll be paying for compute through our nose. I mean, speaking of paying for compute through our nose, we often get chastised for being too public markets focused or too anthropic and open AI focused. Valor Atomics triples to $6 billion price as Sequoia bets on nuclear for AI. Uh, it's
39:16a three-year-old small modular reactor company. Um, raised at 2 billion, now Sequoa leading around at six. Um, and specifically, there's an Nvidia partnership to power AI data centers, which caused a lot of excitement for the company. Harry, I met somebody who's got, you know, I was talking to him and he's in the the business where they take, you know, chicken feces and turn that into methane and and produce gas.