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Karpathy's "autoresearch" broke the internet
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Karpathy's "autoresearch" broke the internet

What is Auto Research?

Introduction to Auto Research

  • Andre Carpathy has launched a new tool called auto research, which is gaining significant attention on Twitter.
  • The episode aims to clarify what auto research is, its use cases, and how it can enhance productivity and profitability.

Understanding Auto Research

  • Auto research functions like an AI intern that conducts scientific experiments on models autonomously.
  • Users set a goal for the AI (e.g., improving an AI model), and the agent plans experiments, modifies code, and runs training sessions.
  • The process involves continuous testing where only successful changes are retained, allowing users to wake up to improved results.

How Does Auto Research Work?

Experimentation Process

  • Users define what "better" means (e.g., cheaper leads or higher sales), guiding the AI's modifications.
  • A visual representation of auto research shows the cycle: setting goals → planning experiments → running tests → analyzing results.

Technical Requirements

  • To run auto research effectively, users need access to a GPU (preferably Nvidia), either locally or via cloud services.

Practical Applications of Auto Research

Mental Model for Using Auto Research

  • Think of auto research as a capable assistant that executes tasks while you rest; it can handle both coding and business analysis tasks.
  • The bot requires access to necessary resources (codebase, internet documents), then operates in loops to refine its outputs based on logged metrics.

Opportunities with Auto Research

Business Ideas Utilizing Auto Research

  • An invitation is extended for a free event discussing building businesses in the age of AI, emphasizing that SaaS is evolving rather than dying.

Niche Applications

  • One suggested application includes creating specialized agents tailored for specific niches (e.g., optimizing Amazon listings or email sequences).
  • These niche products could operate continuously, providing insights and solutions while charging users a subscription fee.

How to Leverage Auto Research for Business Growth

Identifying Pain Points and Quick Market Entry

  • The importance of identifying painful niches is emphasized, as understanding pain points can lead to valuable market opportunities.
  • A visual representation suggests a process: select a painful niche, design an automated research loop, and run experiments to find the best setup.

Monetizing Through AB Testing

  • One strategy involves using AB testing for marketing purposes, particularly in creating effective ads and landing pages.
  • Agents create variants of headlines and layouts for landing pages, measuring which versions convert better through iterative testing.

Conversion Rate Optimization Techniques

  • Tools like Optimizely are referenced as examples of successful conversion rate optimization platforms that utilize auto research for landing pages and ad creatives.
  • Businesses can profit by either applying these techniques internally or offering them as a retainer service to clients at a monthly fee.

Research as a Service Model

  • The concept of "research as a service" is introduced, where auto research continuously updates reports on market trends, competitor analysis, and pricing strategies.
  • This model allows businesses to charge per report or offer subscription services for ongoing insights into compliance tracking across various industries.

Enhancing Existing Products with Auto Research Features

  • Companies with existing SaaS products can embed an auto research feature that allows users to optimize settings easily with the press of a button.
  • This feature could be marketed as part of higher-tier plans or used strategically to upsell premium offerings.

Establishing an Optimization Agency

  • An agency model is proposed where businesses leverage auto research capabilities to conduct numerous tests more efficiently than competitors.
  • Clients would pay monthly retainers plus performance bonuses based on key performance indicator (KPI) improvements achieved through extensive testing.

Utilizing Auto Research in Trading Strategies

  • The discussion concludes with the potential application of auto research in trading by running quick backtests on simple trading rules using LLM-based factor screens.

Auto Research and Its Implications in Finance and Business

The Future of Trading Strategies

  • Auto research allows for backtesting multiple trading strategies overnight, enabling traders to identify promising options for personal trading or selling as digital products.
  • The finance landscape is evolving with auto research tools providing an unfair advantage, leading to more individuals trading their own capital rather than relying on financial advisors.
  • Caution is advised as many may blindly trust auto research without proper oversight, risking significant losses if not managed correctly.

Enhancing Sales Processes

  • Implementing auto research agents in CRM systems can optimize lead qualification by testing rules and messages to identify high-potential leads.
  • This approach allows sales teams to focus on high-value deals, increasing revenue per hour spent through better lead management.

Streamlining Financial Operations

  • Businesses can utilize auto research for automating invoice matching and expense report generation, significantly reducing manual finance work.
  • Such services could be marketed either as software solutions or operational services that enhance efficiency in financial operations.

Internal Productivity Improvements

  • Companies should treat their internal processes like a productivity lab, defining KPIs and allowing agents to iterate on workflows for improved efficiency.
  • By focusing on key metrics and reducing unnecessary meetings, organizations can enhance productivity while concentrating on high-impact decisions.

Research Automation Services

  • A potential business model involves creating a due diligence shop that uses auto research to analyze documents and maintain updated memos for clients such as investors or executives.
  • This service would provide structured briefs and ongoing updates instead of one-off reports, catering to the need for timely information in investment decisions.

Broader Implications of Auto Research

  • The speaker reflects on the transformative potential of auto research beyond finance into areas like medicine, particularly in optimizing clinical trial designs through AI-driven protocols.
  • There’s excitement about how advancements from figures like Carpathy could revolutionize health care by making treatments more efficient and cost-effective.

What is AgentHub and How to Get Started with Auto Research?

Introduction to AgentHub

  • The speaker introduces AgentHub, a new open-source project by Carpathy, describing it as "GitHub for agents," emphasizing its role as a collaboration platform for agent swarms.
  • AgentHub's first use case focuses on auto research but is intended for broader applications, indicating its exploratory nature.

Features of AgentHub

  • Described as an "agent-first collaboration platform," it features a bare Git repository and a message board designed for multiple agents working on the same codebase.
  • Unlike traditional Git platforms, it lacks main branches, pull requests (PRs), or merges, instead offering a sprawling directed acyclic graph (DAG) of commits.

Getting Started with Auto Research

  • To begin using auto research, the speaker suggests utilizing Claude Code to assist in installation. The GitHub repo has gained significant traction with 25,000 stars.
  • Installation requirements include an Nvidia GPU (tested on H100), and users must install the UV package manager along with cloning the repository and preparing data.

Alternatives for Non-GPU Users

  • For those without an Nvidia GPU, options include renting cloud GPUs from services like Lambda Labs or Google Collab; some offer free tiers which are recommended for beginners.
  • The speaker personally prefers Google Collab due to familiarity and trust in Google's services.

Steps to Use Google Collab

  • Users can create a new notebook in Google Collab, change the runtime to T4 GPU, and follow commands provided by Claude Code for setup.
  • The process is simplified through clear instructions from Claude Code that guide users step-by-step in getting started with auto research.

Conclusion and Future Insights

  • The speaker expresses excitement about exploring auto research further while encouraging listeners to engage with comments and feedback regarding solo podcast formats.
  • Emphasizing the early stage of this technology, he encourages experimentation and tinkering as potential opportunities arise within this evolving field.
Video description

I break down Andrej Karpathy's new open-source project, Autoresearch: what it is, how it works, and why some of the smartest people in tech are losing their minds over it. I walk through 10 concrete business ideas you can build on top of Autoresearch loops, from niche agent-in-a-box products to always-on A/B testing agencies. I also cover Karpathy's companion launch, Agent Hub, share community reactions, and show you step by step how to get started using Claude Code and a Colab GPU. I'm hosting a free workshop so you can build your business in the age of AI. Sign up here: https://startup-ideas-pod.link/build-with-ai-2026 Links Mentioned: Autoresearch Github: https://startup-ideas-pod.link/autoresearch Timestamps 00:00 – Intro 00:45 – How Autoresearch Actually Works 02:40 – Visual Walkthrough of the Autoresearch Loop 03:37 – Mental Model: Your Research Bot That Runs While You Sleep 05:26 – Idea 1: Niche Agent-in-a-Box Products 06:48 – Idea 2: A/B Testing for Marketing (Landing Pages & Ads) 08:45 – Idea 3: Research as a Service 09:43 – Idea 4: Power Tool Inside Your Own SaaS 10:49 – Idea 5: Agency That Runs 100× More Tests 12:05 – Idea 6: Auto Quant for Trading Ideas 13:44 – Idea 7: Always-On Lead Qualification & Follow-Up 14:21 – Idea 8: Finance Ops Autopilot for Businesses 15:09 – Idea 9: Internal Productivity Lab for Your Org 15:53 – Idea 10: Done-for-You Research & Due Diligence Shop 16:41 – Non business use cases 18:27 – Karpathy's Agent Hub Announcement 19:50 – How to Get Started with Autoresearch 22:21 – Final Thoughts Key Points * Autoresearch is an open-source AI agent that sets a goal, runs experiments in a loop on a GPU, keeps the winners, and discards the rest — all while you sleep. * You need an NVIDIA GPU to run it (tested on H100), but you can rent one cheaply through Lambda Labs, Vast AI, RunPod, Google Cloud, or Google Colab. * The fastest way to get started is to use Claude Code to walk you through installation, then run it on Google Colab with a T4 GPU runtime. * Ten business ideas built on Autoresearch span niches like SaaS optimization, A/B testing agencies, trading backtests, CRM lead scoring, and done-for-you due diligence. * Karpathy also launched Agent Hub — essentially a GitHub designed for agent swarms to collaborate on the same codebase. * The project already has 25,000+ GitHub stars and is growing fast; early movers who tinker now build an unfair advantage. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com/ LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/