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I just implemented WebMCP on my web app Some people will say it's still too early That's exactly when the arbitrage exists. Here's the timeline: - Google made the proposal two years ago - They launched it at the beginning of this year - They'd been talking about it...

11,491 просмотров • 19 дней назад •via X (Twitter)

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WebMCP by Microsoft and Google is HERE and I'm surprised more people aren't talking about it. Why does it matter? BILLIONS of dollars are about to move through agents, and the internet isn't built for them yet. 1. SEO was about Google understanding your page. 2. AEO was about AI citing you. 3. WebMCP is about the agent actually finishing the job (buying, researching, requesting quote etc). WebMCP is basically websites with agent buttons. Instead of an agent scanning a page like a human, screenshotting and guessing where to click, the site just tells it "here's how to search, here's how to book, here's how to buy." 2 cash flowing businesses you could start today using WebMCP: 1. A WebMCP conversion agency Make boring business websites agent-ready. Law firms, HVAC, med spas, dentists. Build them the first tools (request a quote, book a consult), sell the setup for $2k, then charge a few hundred a month to monitor and improve it. 2. An agent mystery shopper. Test whether agents can actually complete the important journeys on someone's site, buying the hoodie, booking the consult, filing the claim. Hand them a report on where the agent got stuck, missing tools, bad descriptions, lost conversions. Charge monthly, then turn the repeated fixes into software. Full episode on The Startup Ideas Podcast (SIP) 🧃 with Vinny below You'll learn what WebMCP really is, see examples of it IN ACTION, and hear more about 2 startup ideas using WebMCP you can start today. WebMCP is pretty cool. Watch.

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Andrew Ng, co-founder of Google Brain and Coursera, on the worst career advice being given about AI right now: He doesn't mince words about what he's hearing from supposed experts: "As early as earlier this year and certainly last year, there are a few people advising others to stop learning to write code because AI will automate it." His reasoning is rooted in a historical pattern most people miss: "As something becomes easier, more people should do it, not fewer. When the world moved from assembly language to COBOL, there were actually articles saying, 'Well, we now have COBOL. Programming is so easier. Looks like we don't need programmers anymore.' But the opposite happened." Andrew believes the same thing is happening now with AI-assisted coding: "As we now have AI assisted coding, a lot more people should be coding. And I think the demand for software, custom software, has no practical ceiling. So the cost of software engineering comes down, which it is, we'll just get more and more great software out in the world." But here's where the advice gets uncomfortable for experienced engineers. Andrew Ng is honest about what he's seeing on the ground: "It is true that a fresh college grad that is really on top of AI will outperform a full stack engineer with 10 years of experience that is still doing things they were back in 2022, 3 years ago before GenAI." However, there's a nuance most people miss when they hear that stereotype: "The other piece that is less well appreciated is the best engineers I know are not fresh college grads. They're actually very experienced engineers that deeply understand architecture and the conceptual framework of how to think about computers and additionally are on top of AI and on top of these AI skills."

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OpenAI CEO: “Goalposts keep getting moved” - if we were still using AGI definitions from 10 years ago, many would say GPT-4 is AGI. “In one year, AI will be dramatically more impressive.” He also said (surprisingly confidently - he did not hedge like usual) AGI is less than 10 years away. In the long term he’s not concerned about AI taking jobs, but he is concerned about the speed that AI will disrupt the job market. --- INTERVIEWER: What is AGI? When will it be here? And how will we know it's here? Predict how long - we'll call you in ten years? SAM ALTMAN: Less than that. We kind of define AGI as like the thing we don't have quite yet. there were a lot of people who would have ten years ago said, alright, if you could make something like GPT-4, GPT-5, maybe, that would have been an AGI. And now people are like, well, it's like a nice little chatbot or whatever. And I think that's wonderful. I think it's great that the goalposts keep getting moved, it makes us work harder. But I think we're getting close enough to whatever that AGI threshold is going to be, that we no longer get to handwave at it and the definition is going to matter. INTERVIEWER: What is the inflection point for AGI? SAM ALTMAN: I think it's going to be much more continuous than that. We're just on this beautiful exponential curve. Whenever you're on a curve like that, you look forward, it looks vertical. You look back, it looks horizontal. That's true at any point on there. So a year from now, we'll be in a dramatically more impressive place than a year ago. We were in a dramatically less impressive place. But it'll be hard to point. People will try and say, oh, it was AlphaGo that did it. It was GPT-3 that did it. It was GPT-4 that did it. But it's just brick by brick. 1 foot in front of the other, up, climbing this exponential curve. WILL AIs TAKE ALL OUR JOBS? SAM ALTMAN: Every technological revolution affects the job market. And over human history, every maybe 100 years, 150 years, half the jobs go away, totally change, whatever. I'm not afraid of that at all. In fact, I think that's good. I think that's the way of progress and we'll find new and better jobs. The thing that I think we do need to confront as a society is the speed at which this is going to happen. It seems like over two, maximum three, probably two generations, we can adapt. Society can adapt to almost any amount of job market change. But a lot of people like their jobs or they dislike change. And going to someone and saying, hey, the future will be better, I promise you, and society is going to win, but you're going to lose here. That doesn't work. That's not cool. That's not an easy message to get across. We are going to have to really do something about this transition. It is not enough to just give people a universal basic income. People need to have agency, the ability to influence this

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John Ternus, Apple's incoming CEO, on the Steve Jobs story that shapes every product decision at Apple: Ternus recalls the moment in his own words: "I think you know one of my favorite stories... It was about Steve when he was moving a piece of furniture, a chest of drawers and pulled it away from the wall and looked at the back and was just reflecting on, you know, the carpenter had made it beautiful. It finished the back as beautifully as the rest of it, even though nobody was going to see it." For Ternus, the story is a working philosophy: "I think about that all the time because I think that perfectly exemplifies what we do here." He points to Apple's most affordable Mac as proof that this standard applies across the entire product line, not just the premium tier: "We've been talking about the MacBook Neo. I mean, here is our most affordable Mac we've ever made, and it's absolutely beautiful. And if you open it up and look inside, it's just as beautiful, right?" Ternus continues: "That's true on an iPhone Pro Max or a MacBook Pro or an iPad Pro, but it's also true on a MacBook Neo. That's what we do." The takeaway is a clear signal about the direction Apple is heading under his leadership: "It's just been really good to kind of think about that and reflect on that because that is probably the best kind of clue as to where we're going in the future is we're going to keep pushing in that same way." The lesson? Excellence isn't about what people see, it's about what you refuse to compromise on, even when no one's looking. That principle shaped Apple under Jobs and Cook, and it's the standard Ternus is committing to carry forward.

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Chamath: Anthropic's Mythos Warning Is Theater @jason: “Chamath, is it the Boy who Cried Wolf, or is this the real deal now?” Chamath Palihapitiya: “I think it's mostly theater. In February of 2019 when Dario was still at OpenAI, they did the same thing with GPT-2. That was a 1.5 billion parameter model, which sounds like a total fart in the wind in 2026. But at that time, this model was supposed to be the end of days. And at the end of it, it was a huge nothingburger. If you actually think that Mythos is capable of doing what it says it can do, two things are true. One is, a very sophisticated hacker can probably do those things right now with Opus. And two, if these exploits are this easy to find, whether you use Opus or whether you use Mythos, the reality is you'd have to shut down the internet for about five years to patch them all. So when you see a large multi-trillion dollar GSIB bank, it's a bit of theater. Why? What do you think they can actually accomplish in two months? Do you actually think that if there's these vulnerabilities, it's all going to get fixed? Let's give them six months, let's give them nine months. So I do think that Sacks is right, that they have figured out a very clever go-to-market muscle here that activates hyper attention and hyper usage, and so I give them tremendous credit. But we've seen it before, we saw it when these folks were the principal architects at OpenAI, and we're now seeing the same playbook here. The reality is that capitalism moves forward, the funding needs moves forward, and the need for these guys to build adoption moves forward. And that's going to supersede what this is.”

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