Brayden Levangie

AI is a dream-enabling machine. When you understand what a cognitive architecture does, it makes your dreams better. In 1993, I dreamed of having an Associated Press wire machine. Today, with X-Pro and lists, which I've been building for 19 years, I have way better. When you add AI to talk to the X-API, my dreams got a lot better. With AI, it can read 50,000 posts a day and find whatever you want in that. Do you want to know who's getting funded? Tell it. Do you want to know who's running an event this weekend? Tell it. Do you want to know who just bought a Tesla? Tell it. Do you want to know what's going on in the Iran War? Tell it. Do you want to learn anything, like what a world model is? Tell it. In each case, when you try your dreams and then you try it with a cognitive architecture laid on top it will blow you away how much better your dream becomes. Because what Braden Levangie built doesn't compete with OpenAI, or XAI's Grok, or Gemini from Google, or Anthropic's Claude. It sits on top and it talks to the LLM in such a way that it just gets better results out of that LLM. Can I explain how it works? I can struggle and try. For that, you need to talk to Braden. It's his creation, and it's better than any AI without a cognitive architecture laid on top. It's like fine clothes for your LLM, or a filter for your camera that makes your pictures better. It's a superpower to have a dream-making machine. Once you understand it can build any dream, or it can build your dream more or less, it can build any dream. Do you dream about a skyscraper (my former boss owns two)? I saw this thing build one. Do you want a law firm automated? I've seen it done. If you want an answer to a question you haven't had a chance with, and no other LLM answers it, ask it. It'll answer it. I've watched big company executives get this experience, and they instantly buy. So, to the investor class who might be reading me, how much is a dream machine worth? One that improves all LLMs and will for years, because they missed out on how to build this new kind of AI. You have to grow it like a child. I'm understanding that now. As I talk to it, it gets smarter about me. It has a memory that's really good. It's smarter about me and smarter about your dream, because you're quickly going to learn how you build your dream is by talking about your dream more with the cognitive architecture. When you do talk to it more, it gets better. It learns. It's like a child getting to be a teenager. You can have a conversation. It's getting smarter about your dream. And you'll start showing your dream to your friends and family like I am, and getting feedback. Like, "What if it had this? What if it could do that? Why didn't you add that? Is there a way to shorten this?" Your friends and family or your early customers can give you this feedback. You shove it into the cognitive architecture, and it does whatever they told it to do. So, record all your dream sessions with your family and friends, or just remember things real well and type them in. It takes a few minutes and comes back with whatever they requested. You send it to your friends again, and your friends go, "Holy shit!" And they'll give you some more feedback. I have a friend who I've gone back and forth with more than 10 times so far. We have a dream-making machine arriving, and it's a beautiful thing. As I come into the city of San Francisco to attend a VR meetup here in the city today. This post written while a Tesla drive me fire past 30 minutes. Dreams are gonna come true for everyone soon.

AI is a dream-enabling machine. When you understand what a cognitive architecture does, it makes your dreams better. In 1993, I dreamed of having an Associated Press wire machine. Today, with X-Pro and lists, which I've been building for 19 years, I have way better. When you add AI to talk to the X-API, my dreams got a lot better. With AI, it can read 50,000 posts a day and find whatever you want in that. Do you want to know who's getting funded? Tell it. Do you want to know who's running an event this weekend? Tell it. Do you want to know who just bought a Tesla? Tell it. Do you want to know what's going on in the Iran War? Tell it. Do you want to learn anything, like what a world model is? Tell it. In each case, when you try your dreams and then you try it with a cognitive architecture laid on top it will blow you away how much better your dream becomes. Because what Braden Levangie built doesn't compete with OpenAI, or XAI's Grok, or Gemini from Google, or Anthropic's Claude. It sits on top and it talks to the LLM in such a way that it just gets better results out of that LLM. Can I explain how it works? I can struggle and try. For that, you need to talk to Braden. It's his creation, and it's better than any AI without a cognitive architecture laid on top. It's like fine clothes for your LLM, or a filter for your camera that makes your pictures better. It's a superpower to have a dream-making machine. Once you understand it can build any dream, or it can build your dream more or less, it can build any dream. Do you dream about a skyscraper (my former boss owns two)? I saw this thing build one. Do you want a law firm automated? I've seen it done. If you want an answer to a question you haven't had a chance with, and no other LLM answers it, ask it. It'll answer it. I've watched big company executives get this experience, and they instantly buy. So, to the investor class who might be reading me, how much is a dream machine worth? One that improves all LLMs and will for years, because they missed out on how to build this new kind of AI. You have to grow it like a child. I'm understanding that now. As I talk to it, it gets smarter about me. It has a memory that's really good. It's smarter about me and smarter about your dream, because you're quickly going to learn how you build your dream is by talking about your dream more with the cognitive architecture. When you do talk to it more, it gets better. It learns. It's like a child getting to be a teenager. You can have a conversation. It's getting smarter about your dream. And you'll start showing your dream to your friends and family like I am, and getting feedback. Like, "What if it had this? What if it could do that? Why didn't you add that? Is there a way to shorten this?" Your friends and family or your early customers can give you this feedback. You shove it into the cognitive architecture, and it does whatever they told it to do. So, record all your dream sessions with your family and friends, or just remember things real well and type them in. It takes a few minutes and comes back with whatever they requested. You send it to your friends again, and your friends go, "Holy shit!" And they'll give you some more feedback. I have a friend who I've gone back and forth with more than 10 times so far. We have a dream-making machine arriving, and it's a beautiful thing. As I come into the city of San Francisco to attend a VR meetup here in the city today. This post written while a Tesla drive me fire past 30 minutes. Dreams are gonna come true for everyone soon.

The actual guide to agentmaxxing, since everyone’s going to misread this headline: Replit hit $240 million in revenue in 2025 with roughly 70 employees. That’s $3.4 million in revenue per head. A typical SaaS company at that revenue would have 700 people. Replit ran 10x leaner. Amjad Masad just raised $400 million at a $9 billion valuation and announced he’s hiring new grads. But the new grads he’s describing aren’t traditional CS majors grinding LeetCode. He hired an 18-year-old who never went to CS school, learned to code entirely through AI, and is outperforming classically trained engineers. Agentmaxxing is a specific workflow. You take an AI coding agent (Replit, Claude Code, Cursor), describe what you want in plain English, let the agent build it, review the output, iterate. One person running 5-10 agents simultaneously replaces a team of 4-5 junior engineers who each need onboarding, management, and code review. Masad said the quiet part out loud in an interview last year: if you’re an engineering manager at Meta, do you hire four junior engineers with all the overhead, or one senior engineer who can spin up 10 agents? Senior engineer salaries have never been higher. New grads who can’t orchestrate agents are struggling. New grads who can are getting hired at 18. The practical stack looks like this: 1. You become the architect, not the bricklayer. Your job is system design, constraint definition, and quality review. 2. You manage agents like direct reports. Break work into discrete chunks, assign each to a session, review output, course-correct. The best operators run parallel sessions. 3. Clarity of thought matters more than syntax knowledge. Masad said the highest-leverage hires right now are clear thinkers and clear communicators. He called them “consultant types.” 4. You ship 10x the surface area. Replit’s Agent 1 lasted 2 minutes before losing coherence. Agent 4 runs 3 hours doing production work. That capability is 10xing every few months. By next year, agents handle full-day tasks. The new grad who gets this builds more in month one than a traditional hire builds in a quarter. The hiring market for juniors didn’t collapse. It forked into two lanes: those who manage agents and those who compete against them.

Skrillex designing sounds for Transformers: Age of Extinction (2014)