Transcription
So Andre Karpathy, he's the guy who literally helped build modern AI, who was at OpenAI, who got Tesla autopilot working, and who coined the term vibe coding. He just told us if you're still building apps the way you were last year, he's got bad news for us.
So he just gave a brilliant talk. I've spent hours breaking it down to help you understand how it may affect what you build as a developer, founder, or software company. Thanks to monday.com for sponsoring this video. More on them later.
In the next few minutes, I'm going to walk you through what he actually said about 2026, what it means for what you should be building and how you should be building, and the four frameworks that I think every AI builder needs to have in their head right now. I'm Rob from Switch Dimension, and if you're trying to build with AI in 2026 and beyond, this might be the most important video you watch this month. So, stick with me.
This kind of a brain is the single most powerful thing I've built in the last couple of months. Highly recommend you do something similar yourself.
So one of the first things that stood out to me was Karpathy's point about the December inflection. So what Karpathy is saying is round about December the model's output started to actually just work. He stopped correcting it. He started just trusting the model and he basically went on this vibe coding bender. He said he has a ton of side projects that he's built up. And we all have that problem. Multiple different projects we're working on the same time because now we can build anything. So essentially if you haven't sat down in the last 60 days and seriously tried to build something end to end with uh claw codeex cursor in agent mode you are really flying blind according to Karpathy. So go do that this weekend. Seriously build something.
So I think Karpathy's biggest takeaway in this talk was the idea of software 3.0 and we've heard that so many different times before but this is a slightly different angle I don't think many have seen. So Karpathy's breakdown of the software evolution is software 1.0 is handwritten rules. So basically writing out code. Software 2.0 was training neural networks via large data sets. And software 3.0 is where the large language model itself becomes the programmable computer. The interpreter and your code basically is the prompt and the context window is your lever. So that's Karpathy's high-level take on it.
How does this affect us practically as builders? So, in traditional SaaS, this is Levercast, an app I built. It uses AI to help you post to all your social media platforms. So, I would just click create, drop in my thoughts, generate a post with an existing style guide, and then it takes the pain out of the first draft for my social media posts across the various different channels that I work on. So, that's a traditional SaaS app with a little bit of AI sprinkled in on top.
So, here's the big shift and here's what's changing. We're going to be increasingly using our agents to do more work for us. We're going to be living in claw code, codec, cursor, whatever is your agent of choice. In this new world, what people will increasingly be doing is basically just telling their AI agent to carry out a task. So instead of me going and logging into Levercast and going through all the workflow, I might just say, "Hey, I've got an idea for a post. I could drop it in and say, "Hey, use the Levercast MCP to carry this out." Or not even. I could actually use a skill that's pre-built in that will actually do all of this for me. I go off to do something else or I have this working on a schedule and then bang, all my posts are published.
So besides that being a cheap plug for my own software, really what we're getting at here is a change in how we need to think about building things. As a builder, you really need to think about the current capabilities of multimodal models and even think ahead a few months to what's coming next and how that might affect the software you're building or you've already built. Do you need to have an MCP, an API, or some kind of agentic workflow in front of it so that an agent can discover it quickly?
So, Karpathy's example of this was back last year, he built this quick app that basically allowed you to turn your menus into magic. It's the idea that you could take any menu and looking at this menu here, you might not know exactly what the food is or what it might look like. By dumping in this menu into his app, it basically was able to create AI representations of what the food was and what it looked like. So last year, this was an entire application that he built that somebody could use. This year, he could solve the same problem with just ChatGPT or Nano Banana. So you can see the entire menu gen workflow replaced by me just dropping in that original menu. And here you can see an overlay of the dishes on the starters.
So his big point here is the menu gen app that he built a year ago doesn't really need to exist anymore. And here's why that's really uncomfortable. A huge percentage of the apps people are building right now shouldn't exist either. They're basically orchestrating things the model can already do natively. That's only just appeared in the last couple of months. They're software 1.0 plumbing wrapped around what should just be a single software 3.0 zero prompt. Anyway, you get the point.
So, here's the test. Take what you're building and ask, could I do this with a single multimodal prompt and the right tool calls or an MCP or two? If the answer is yes, you're building plumbing that's about to get eaten by the next model release, stop or pivot. For you Americans or Canadians who love hockey, we don't even have ice in Ireland. This is where I insert a quote about you're skating to where the puck is going to be, not where it is right now.
So, if you watch this channel at all, you're going to be no stranger to vibe coding apps. And I wanted to talk today about monday.com's Vibe because basically I think it's different. It's a natural language app builder baked directly into the monday.com platform. So, yeah, of course there's tons of different app builders out there, but I think what's really different about this, you're actually building your application on top of your monday.com infrastructure and context. And as we talk about in this video, the context and the understanding is really important. You've got your workflows, your intakes, your OKRs, everything that's important to your company is managed in there. But often there's this last mile problem where you want to solve something like, you know, I wish I had the perfect form for pulling that in or uh we need a clean page that represents our OKRs. So, with monday.com's new Vibe, you can use natural language to create bespoke interfaces with inputs and outputs that write back to your monday.com data like a sales forecasting app, a campaign health tracker, a time tracker app. So, it's pretty much living in Monday where you and your staff works. This really is a super tool. Viewers can get started for free. Check out the link in the description down below.
So, already Karpathy has given us some real gold. Let's move on to his next point. And this is all about verifiability and building a moat as we go forward. So Karpathy went on to explain why a lot of frontier models fall down and how there's an advantage in that. The reason models are so good at code is because it's deterministic and it's verifiable and that's great feedback for the model. Unfortunately, a lot of the world isn't as verifiable as code.
So, Karpathy suggests what are the domains that the large frontier labs are not focusing on right now that have some level of verifiability. Financial trading, supply chain and routing optimization, continuous integration and migration agents, data cleaning, labeling. You all have domain expertise in some niche part of any workflow or company. What are the things that you can build in that space that take advantage of the things Karpathy is talking about in this conversation?
So thankfully in this talk he basically retires the term vibe coding and replaces it. So vibe coding is great. It raised the floor. Pretty much anyone can build now. We all needed that. It pretty much democratizes building. But he says what professionals are doing now is agentic engineering. And that's the kind of stuff I teach a lot in my channel and on my course. This means things like using specs, plans, managing your context window, doing proper review, making sure that we have unit-level smoke tests to end-to-end tests and blockers in place in continuous integration so that we're not pushing bad code. Karpathy says he's seen people who are getting good at this go 10x faster. If you're on X at all, you'll see that, oh, people running 10 to 20 agents at the same time. Personally, I kind of think that's nonsense. I'm really good at this. I've been doing it for two years and the most I can keep in my head at any time is maybe three to four agents running at the same time. I give them a little bit of work. I check what they're working on. I have to review the code. These are production databases, production systems I'm working on. I'm not just going to push up whatever the agent was working on.
So, if you're feeling behind and you're working with agents, but you don't feel like you're working with 10 or building entire uh empires in a single prompt, then don't worry. But the thing is we really need to think about how we get to that point because what Karpathy is talking about is we need to build again for where that puck is going. So we get to that point where not unlike in December when things just worked. I think we'll get to a point where our our agentic harnesses just work and we can run 10 to 20 agents at the same time if we choose. We're not there yet, but we're on that path.
By the way, if you're interested in building Agentic harnesses and production systems like that, so you can build apps really quickly, you can join my course and community at switchdimension.com. It's currently closed to new members right now, but I have a new course dropping in the coming weeks. If you want to be part of that cohort, just drop your name and email into the waitlist.
Okay, so let's wrap this all up into the four things you should build. So the first thing he suggests you build are tools that enhance your understanding, not just your speed. So here's what I do myself and here's a really easy way for you to get started with this. Here I've got clawed co-work, but it doesn't matter what tool you use. I could do this in clawed code. You could do this in cursor. You can do it wherever you want. Essentially what you need is a folder and an initial prompt. So that prompt to your agent is where you tell it about your company, your app, your domain space, your life, whatever it else it is, and ask it to create a set of strategy documents around that application, business, whatever the domain space is. So in my case, I have a company called Switch Dimension that helps people learn how to build with AI. And I got it to produce a whole lot of strategy documents around that through various conversations. And they're just simply stored as markdown in a folder. So my big problem is I want to build everything and take every opportunity. I just have a quick conversation with my strategy agent which now has an understanding of where I'm going and it keeps me on track. It gives me focus. It says you're going in the wrong direction if you work on that. Here's what you should be focusing on. Here's the opportunities. And every time I ask it to generate a doc or create new content, it does that with real context and understanding of my Switch Dimension world. This kind of a brain is the single most powerful thing I've built in the last couple of months. Highly recommend you do something similar yourself.
So the next thing you should build is agent-first infrastructure. Everything we've built is pretty much built for humans. That's documents, dashboards, install flows, DNS settings. The entire internet is built really for humans. So the real win in this next generation is stripping away all of the human UI. Would an agent know how to use this directly without any kind of human translation in between? We're seeing this on websites in e-commerce where LLM.txt files are there so that when agents arrive on a website, they can quickly figure out how to use it rather than reading through all the emotional marketing that's directed at humans. It wants to just know how the API works, how can work with your product, is it trustworthy as fast as possible. Build for that.
Number three, we talked about verifiable domain capabilities. So, a lot of the big labs are covering the large domain areas, but they're not going to have the time or be specifically focused on reinforcement learning for all these little sub-niches. There are millions of them in every part of our life and business. Can you build a reinforcement learning environment around this? Fine-tune it and own that capability. So, don't dismiss this as an opportunity for you. We can now build anything. That's exciting. Take your handbrake off and go and do it.
And number four, the big one, let's build apps that only exist now because of software 3.0. So that is not a faster spreadsheet, a faster uh UI interface on top of a workflow. We need completely new things like that large language model knowledge base Karpathy was talking about that literally we couldn't exist because there was no code that could actually do it. There's so many new things we can build now that we're still thinking about apps and the old way of doing things. There's a whole new approach now with these reasoning models that we can apply.
Let's be honest, AI will change the jobs market. It will change how we work. If we think positively about what we can build now, the reframing of data, the compilation across all these modalities. We've got large language models now that actually push and progress other areas of science and medicine. We have a really exciting time ahead of us.
On a personal note, I went through my own side project folder this week and I killed at least three projects after watching Karpathy's talk. Both of them failed the menu gen test and the software 3.0 test. They were basically software 1.0 plumbing for things the next model release is probably going to do natively. This of course is painful, but it's better just for me to kill them now than to ship them and watch them die in 3 months time. But saying that, there are one or two apps that I am doubling down on that hits all four of the criteria up above. I'll be sharing more on that soon.
So, hit me up in the comments and I'm asking this seriously. What is the app you've built that probably shouldn't exist anymore? I want to see how many of us are in the same boat. No judgment. I'm in it, too. If this was useful, subscribe. I'm doing a follow-up on building agent-first infrastructure that goes way deep into the practical side. And if you want the actual playbooks I use for building with agents, go and check out the Switch Dimension loller and community. They are linked below. I've also linked to Karpathy's full talk down below. I'm supposed to link one of my own videos, so you go there and watch one of those next, but I highly recommend checking it out. And I've also got a ton of other videos on this topic on the channel.