Chapter 1: What is Autoresearch and why is it significant?
Andrej Karpathy, I mean, one of the godfathers of AI has just launched something called auto research and auto research is a huge deal and it's going viral on Twitter. And I just wanted to do an episode where I can explain to you in the clearest way possible. what it is, what are the use cases, how to make money from it, how to be more productive with it, how to create impact with it.
And by the end of this episode, I'm going to give you a bunch of different ideas, use cases for how to use auto research. I'm going to explain it to you in the most clear way possible. And at the end, I'm going to tell you how you can actually get started with it. So let's go right into it. So what is auto research?
Well, it's like having a super nerd robot intern that runs science experiments on AI models for you all night without you doing the boring stuff. I mean, sounds intriguing, right? So how do you actually... program it or get started with it? Well, the first thing is you've got to give it a goal. So you can say something like, make this small AI model smarter. That's the goal.
And then an AI agent will actually plan what to do, like different settings, code changes, edits the Python code for you, runs a short training experiment on a GPU, for about five minutes. It reads the results, and then it decides what to change next and to repeat the loop.
So in some ways, if you've seen my video on the Ralph loop, where it basically would do engineering 24-7 and you'd wake up to new stuff happening, in simplest terms, that's what Auto research is helping it do. You give it a goal. The AI agent does a thing. You tell the AI what better means. Cheaper leads, more clicks, higher sales, better model school. And then the AI keeps changing things.
testing them, and it only saves the changes that improve. So what's really cool about it is you wake up, you grab the best version, and then hopefully you turn it into something you charge for or you give it away. I saw this tweet by Toby, who's the CEO and co-founder of Shopify. Auto research works even better for optimizing any piece of software. Make an auto folder, add a program MD.
That's just a markdown file, which is really the foundation of how you're going to be using auto research, and a bench script, make a branch and let it rip. That's why I started paying attention to auto research. When Andre Karpathy, Legend, and Toby and more people started playing with it, I'm like, okay, I've got to pay attention.
I created this little visual for how to think about what auto research is. You set the goal, the AI plans an experiment, It edits and trains the code and settings. It runs a short training on a GPU. By the way, this is an important... I should mention that you need a...
a nvidia chip to actually run auto research or you can do it in the cloud i'll talk about this at the end of the episode but you you know you do need that you can't just run it on let's say you have a macbook m1 or something like that it reads metrics it says is it a better result if it's if it's not it's gonna log the attempt and it's gonna discard the config if it's yes it saves it to the config um and then just plans a different experiment and it just you know hopefully gets better on your goal whatever it is so uh
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Chapter 2: How does the Autoresearch loop function?
So for code experiments, maybe it's improve this model test score. For business, figure out the top five competitors for product XYZ and make a short report. Step two is you give the bot access to the code, a GPU for ML experiments. You obviously need to give it access to the internet and documents if you're doing reading tasks. The bot then runs a loop. So it plans, it acts,
Meaning it might run code or search, it reads results, it updates the plan, and then you just come back later. It could be 12 hours, 20 hours, six hours, and you see if it's logged everything, charts and metrics, and then it gives you a written summary in normal language.
So, you know, think of auto research as a research bot that runs experiments for you while you sleep, tries lots of ideas fast and keeps the winners. Quick break to invite you to something. Now, this isn't an ad. I just want to invite you to a free event because I think that you're going to get a lot out of it.
I wanted to take one hour of time where we just talk about building businesses in the age of AI. People say SaaS is dying. I actually believe the quite opposite. I think that SaaS is just evolving. I think right now is an incredible time to be building software startups that help you craft your dream life. And for all those reasons, I said, let's just book one hour of time.
It's going to be 11 a.m. March 12th. That's a Thursday where we can go and lock in and just talk about building businesses in the AJI. I'll include a link in the description and the show notes to join. And I can't wait to see you there. Okay, how do we use it? Here's some ideas for you. So the first idea for you I have is a niche agent in a box products. This can be multiple products.
And by the way, I put out these ideas. I want you to do these ideas. I think that even if they don't turn into businesses, you will learn about these tools and that is going to help you outperform 99.9% of people on this planet. So you package tiny auto research loops, tune for one painful niche.
So the example I think of is an Amazon listing experimenter, an email sequence tuner for realtors, a pricing optimizer for SaaS. Those are, you know, auto research loops and ideally in a niche that you understand well. And then you charge a monthly fee. So the value prop is this thing runs experiments for you 24-7 and just shows you the winner to click accept. How valuable is that?
And how many different niches are there that this plays into? The hard part is figuring out what's the pain points and then obviously you want to be quick to market, right? So here's a visual of it. Pick the painful niche. Design the tiny auto research loop. Run experiments automatically. See which setup works best. Turn best setup to a simple agent product.
And then you charge that monthly subscription. Number two. You're going to want to, you know, here's an idea. Print money using an A-B testing for marketing. So this is, it's very similar. But instead of, you know... Instead of doing it for realtors or whatever, you're doing it for ads and landing page experiments.
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Chapter 3: What is Karpathy's Agent Hub and how does it relate to Autoresearch?
Point an auto-research style agent at your CRM, like a Salesforce or something like that, and inbound leads. Let it test rules and messages to see which leads are most likely to buy, right? It auto-grades the leads, suggests next actions, and drafts follow-ups. So salespeople only focus on high-value deals, so it's more revenue per hour spent. Visual over here for you.
Connect to CRM, auto-research, test the leads, rank leads by likelihood to buy, draft follow-up messages, sales focus on best leads, revenue per sale increases. By the way, I can totally see someone starting this and this gets acquired by one of the large fintech companies or one of the large banks. Visual here, ingest invoices and expenses.
The auto research improves rules and prompts, matches invoice and detects exceptions. It generates clean expense reports, reduces manual finance work, and then you can sell it as a software or op service. Maybe you start as op service and then you evolve into the software. Two more for you. Number nine, an internal productivity lab for your own org. I thought this was interesting.
So treat your company like Karpathy's GPU lab. Define KPIs, so like response time, close rate, ticker resolution, and let agents iterate on workflows and templates and routing rules. So you just get fewer meetings, less manual grunt work, and then you personally touch only the high impact decisions when everyone else rides the improved process. So The goal here is defining the key metrics.
Auto research is testing the new workflows. It's improving templates and writing rules. You're cutting meetings and manual tasks. That's good. Team focus is a high impact work and then higher productivity and ideally higher profit. Last idea for you. Done for you, research or due diligence shop.
So you use the research loop to chew through docs, filings, product pages, and reviews and keep an evolving living memo for clients like investors, acquirers, execs. You make money by selling fast, well-structured briefs, and a monthly update pack instead of one-off manual reviews. research logs. The goal, get investor or acquire a question.
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Chapter 4: What are some innovative business ideas using Autoresearch?
This happens all the time. Auto research reads through docs and filings. It summarizes that product market and risks and maintains a living memo for the client. It delivers a brief and updates packs and the client pays for reports and ongoing access. I would pay for something like this. Hopefully someone builds it. All right, so those are a bunch of ideas for you.
I also saw a couple of interesting things this morning. My good friend Morgan Linton, who's been on the pod before, he says, Right now where my mind is going is medicine. It feels like in many ways clinical trial design is itself kind of like a hyperparameter search. I know right now trials cost tens of millions of dollars minimum.
It feels like an agent swarm could optimize treatment protocols on small proxy experiments, promote the most promising candidates and then move to humans to review. So humans still very much in the loop but later on and experimentation going much deeper, happening faster and for far less money. I think for me, while I'm not a doctor, he's an engineer.
What I'm the most excited about when it comes to AI is the impact it will have on human health and critical areas like disease treatment. It might be a crazy idea, so a real doctor can jump in the comments and slap me on the wrist here. I looked at the replies, I didn't see any doctors come in. But I don't know, I just can't stop thinking about how
What Karpathy has discovered here could have some pretty profound implications. So only halfway through my coffee though, but woke up this morning and this is what I'm thinking about, so thought I'd share. I agree, I think there's a lot of really interesting, not just like business profit ideas, but also just like medicine, science, research.
So I'm excited for people to take this and to continue with it. I also saw this tweet here. What's after auto research? It's Karpathy's new open source project, Agent Hub. So Karpathy also launched Agent Hub. What is Agent Hub? It's GitHub for humans. Sorry, GitHub is for humans, Agent Hub is for agents. So it's basically a GitHub for agents.
An agent swarm collaboration platform, a very promising direction. I'm watching him speed run a one man billion dollar project. If you look at the GitHub for Agent Hub, it says, first use cases for auto research, but it's a lot more general than that, exploratory project.
He says, agent first collaboration platform, a bare Git repo, a message board designed for a swarm of agents working on the same code base. Think of it like a stripped down GitHub where there's no main branch, no PRs, no merges, a sprawling dag of commits in every direction with a message board for agents to coordinate. I think this is really interesting.
Whenever Carpathy's up to something, I'm always paying attention. So I had to put that one in there as well. So maybe you've gotten to the end of this episode and you're kind of like, okay, I think I understand what auto research is. I think I know what Carpathy's a G, Toby's a G, all these smart people are playing with it. How do I get started? Well, to get started, I'd recommend...
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