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An intern at a YC startup needed to extract SEC filings + earnings data for all Fortune 100 companies. He shipped it in 2 days using GPT-4.1 — and got a return offer. The agent: - Scrapes each company’s investor relations page - Pulls 10-Ks, 10-Qs, earnings slides, and... show more

Srijan Subedi

1,360 subscribers

502,024 görüntüleme • 1 yıl önce •via X (Twitter)

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Srijan Subedi profil fotoğrafı

Srijan Subedi1 yıl önce

Sign up at to build your own scrapers

Myles Shedden profil fotoğrafı

Myles Shedden1 yıl önce

Well, you’ve been able to do this with bloomberg and factset for around 20 years. To be clear, I’m not saying AI isn’t useful and going to have a huge (largest in history?) impact, just that this isn’t a good example of it’s capabilities.

Srijan Subedi profil fotoğrafı

Srijan Subedi1 yıl önce

That’s a good point! They were likely using some form of scraping themselves, and that process was probably manual and difficult. A platform like this would make it much easier. I also agree there are even higher-impact problems AI scraping can help solve.

bitzuist profil fotoğrafı

bitzuist1 yıl önce

SEC has free api

Srijan Subedi profil fotoğrafı

Srijan Subedi1 yıl önce

It usually has less information than the company’s investor relations page.

Jared Scheel profil fotoğrafı

Jared Scheel1 yıl önce

I’m not following… it took teams of analysts to do some simple scraping? Or is there also some actual analysis of the data that was happening too?

Srijan Subedi profil fotoğrafı

Srijan Subedi1 yıl önce

Building and fixing scrapers as sites changed and bypassing anti-bot measures took them a lot of time. Scraping a few sites is easy, but it becomes a headache at scale.

Vivek Girotra profil fotoğrafı

Vivek Girotra1 yıl önce

Did web scrapers not exist before GPT? C’mon now.

Srijan Subedi profil fotoğrafı

Srijan Subedi1 yıl önce

It did, but someone had to write the scrapers manually which is time-consuming and difficult across hundreds of sites. This makes it 10x faster and easier by automatically generating the code.

Sumit profil fotoğrafı

Sumit1 yıl önce

Yup, that’s true. The bar hasn’t just risen; it has completely changed. Now, a high-agency, high-intellect person can replace an entire team. This is the era of high-agency people. Those with high agency are going to become ultra-successful in this new age of AI. Exciting times to be alive.

Srijan Subedi profil fotoğrafı

Srijan Subedi1 yıl önce

💯 💯

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hedge funds pay $50,000/year for data that's been free on SEC. gov since 2003 Form 4 filings every stock purchase a CEO makes, every share a CFO sells, filed within 48 hours and sitting there searchable for free nobody built a screener around it for two decades one guy did it in a Python script over a weekend. tracked every insider purchase above $500k in the 30 days before earnings signal held up: when a CEO buys his own stock right before earnings, it beats the market by an average of 11% over the next 60 days backtested across 7,400 trades since 2010, sharpe of 1.8, max drawdown under 15% he wasn't smarter than hedge funds. he just thought to look at a URL they were paying $50k to access behind a paywall Bookmark this before it get buried SEC made the disclosure public to protect retail investors it ended up being the only real edge retail investors ever had most people watch earnings calls. this guy just read filings same market, completely different game

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GREG ISENBERG

135,254 görüntüleme • 5 ay önce

WHAT A SCAM Investigation finds a banking app used by millions of Americans backed by investors like Mark Cuban, Larry Ellison and “They've got Democratic lawmakers support and lobbyists” are taking in 10s of million of dollars in donations per year and pocketing 90% of it - Every time you make a transaction/ withdraw it asks if you want to tip - The data shows that the apps receive tips 73% of the time. “This is because they're very manipulative. At one point, Ernan made you click 13 times to opt out of tipping” - An FTC investigation found that for each percentage point of a tip, they only donate 10 cents. So if I tip 10% on $100 advance, my tip is $10, but only $1 of that is going towards feeding hungry kids - In SEC filings, they reported making $68 million from tips last year

WHAT A SCAM Investigation finds a banking app used by millions of Americans backed by investors like Mark Cuban, Larry Ellison and “They've got Democratic lawmakers support and lobbyists” are taking in 10s of million of dollars in donations per year and pocketing 90% of it - Every time you make a transaction/ withdraw it asks if you want to tip - The data shows that the apps receive tips 73% of the time. “This is because they're very manipulative. At one point, Ernan made you click 13 times to opt out of tipping” - An FTC investigation found that for each percentage point of a tip, they only donate 10 cents. So if I tip 10% on $100 advance, my tip is $10, but only $1 of that is going towards feeding hungry kids - In SEC filings, they reported making $68 million from tips last year

Wall Street Apes

40,445 görüntüleme • 1 yıl önce

I built a stock market API in 42 days. All during buildspace s5. What is the API? Today, it lets you pull financials for 16,000 tickers going back 30+ years. Why did I build the API? Because the big providers have: • poor API design • poor documentation • expensive sales contracts • strict data retention policies How did I build it? I started building the API from scratch at the start of s5 in early June. I got deep into the SEC Edgar API and cracked how to scrape at scale. Sonnet 3.5 from Anthropic was a godsend for this. I hacked early mornings, late nights, and weekends, with a full-time job. Day by day. Code by code. I set weekly goals and hit each one. End result: I’m excited to see where this API goes. It may go nowhere, but I’ll always know that I can set goals and crush them.

I built a stock market API in 42 days. All during buildspace s5. What is the API? Today, it lets you pull financials for 16,000 tickers going back 30+ years. Why did I build the API? Because the big providers have: • poor API design • poor documentation • expensive sales contracts • strict data retention policies How did I build it? I started building the API from scratch at the start of s5 in early June. I got deep into the SEC Edgar API and cracked how to scrape at scale. Sonnet 3.5 from Anthropic was a godsend for this. I hacked early mornings, late nights, and weekends, with a full-time job. Day by day. Code by code. I set weekly goals and hit each one. End result: I’m excited to see where this API goes. It may go nowhere, but I’ll always know that I can set goals and crush them.

Virat Singh

236,540 görüntüleme • 2 yıl önce

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:

Andrew Ng

105,343 görüntüleme • 1 yıl önce

karpathy just broke the internet with something called auto research it’s basically an ai research agent that runs experiments for you 24/7 you give it a goal like “make this model better” “find a higher converting landing page” “lower customer acquisition cost” then it runs a loop: 1) plan an experiment 2) edit the code or config 3) run a short test on a gpu 4) read the metrics 5) keep the winner 6) try again over and over while you sleep by the morning you wake up to the best version actual tested improvements think of it like a robot research intern that runs hundreds of experiments and only keeps the winners this is link to his repo for your to mess around with it in the latest episode of The Startup Ideas Podcast (SIP) 🧃 i break down: • what auto research actually is • how it works step by step • 10 business ideas you can build with it • how to install it and start using it this one is saucy because tools like this change how startups get built watch

karpathy just broke the internet with something called auto research it’s basically an ai research agent that runs experiments for you 24/7 you give it a goal like “make this model better” “find a higher converting landing page” “lower customer acquisition cost” then it runs a loop: 1) plan an experiment 2) edit the code or config 3) run a short test on a gpu 4) read the metrics 5) keep the winner 6) try again over and over while you sleep by the morning you wake up to the best version actual tested improvements think of it like a robot research intern that runs hundreds of experiments and only keeps the winners this is link to his repo for your to mess around with it in the latest episode of The Startup Ideas Podcast (SIP) 🧃 i break down: • what auto research actually is • how it works step by step • 10 business ideas you can build with it • how to install it and start using it this one is saucy because tools like this change how startups get built watch

GREG ISENBERG

436,897 görüntüleme • 5 ay önce

A GUY GAVE A HERMES AI AGENT ONE GOAL AND IT GENERATED $22,000 IN LEADS FOR A STRANGER'S BUSINESS IN 24 HOURS On stage at a conference, he picked a random small business from a LinkedIn post in the audience. A web design studio in Carlisle, Cumbria. He gave Hermes Agent – open source, runs on any LLM – one goal: "Find companies in the area. Take screenshots of their current websites. Redesign every single one. If they don't have a website, build one. Email each business owner offering the redesign for £2,000." The agent went off and did it autonomously. Hundreds of full website redesigns. Real ones. Not AI slop – actual professional-looking sites. It could only send 50 emails a day to avoid looking like spam. 100 emails sent. 11 responses. Roughly $22,000 in leads sitting in one inbox. From one prompt. For a business that didn't even know this was happening. The agent didn't need a team, a sales department, or weeks of outreach. It needed one goal and permission to keep going. Bookmark this post. Full demo in the video below.

A GUY GAVE A HERMES AI AGENT ONE GOAL AND IT GENERATED $22,000 IN LEADS FOR A STRANGER'S BUSINESS IN 24 HOURS On stage at a conference, he picked a random small business from a LinkedIn post in the audience. A web design studio in Carlisle, Cumbria. He gave Hermes Agent – open source, runs on any LLM – one goal: "Find companies in the area. Take screenshots of their current websites. Redesign every single one. If they don't have a website, build one. Email each business owner offering the redesign for £2,000." The agent went off and did it autonomously. Hundreds of full website redesigns. Real ones. Not AI slop – actual professional-looking sites. It could only send 50 emails a day to avoid looking like spam. 100 emails sent. 11 responses. Roughly $22,000 in leads sitting in one inbox. From one prompt. For a business that didn't even know this was happening. The agent didn't need a team, a sales department, or weeks of outreach. It needed one goal and permission to keep going. Bookmark this post. Full demo in the video below.

SCOTTY BEAM

18,877 görüntüleme • 2 ay önce

This YouTube AI Agent is f*cking wild 🤯 This n8n agent scrapes top-performing YouTube videos in any niche... Pulls full transcripts... And extracts every hook, angle, and theme automatically. All inside n8n + Airtable. Perfect for DTC brands & agencies who want to know what's working on YouTube before creating a single ad. Here's the problem: You're spending hours "researching" YouTube. Watching video after video. Scribbling notes. Trying to reverse-engineer why that one video blew up. By the time you've pulled anything useful, half your day is gone. This n8n agent does it in minutes: → Enter any keyword (e.g., "rucking", "cold plunge", "protein powder") → Scrapes top YouTube videos with full transcripts → Logs everything to Airtable—views, likes, publish date → Gemini analyzes each transcript automatically → Extracts hooks, angles, and themes from every video No watching hours of content. No manual note-taking. No "let me rewatch that part" loops. What lands in your Airtable: - Video URL, title, channel, and performance metrics - AI-extracted hooks (what grabbed attention in the first 10 seconds) - Angles (the unique claim or perspective that worked) - Themes (the narrative structure driving the video) - Full transcripts for deeper research Built 100% in n8n. Want the complete n8n workflow + Airtable base? > Comment "YT" > Like this post And I'll send it over (must be following so I can DM)

This YouTube AI Agent is f*cking wild 🤯 This n8n agent scrapes top-performing YouTube videos in any niche... Pulls full transcripts... And extracts every hook, angle, and theme automatically. All inside n8n + Airtable. Perfect for DTC brands & agencies who want to know what's working on YouTube before creating a single ad. Here's the problem: You're spending hours "researching" YouTube. Watching video after video. Scribbling notes. Trying to reverse-engineer why that one video blew up. By the time you've pulled anything useful, half your day is gone. This n8n agent does it in minutes: → Enter any keyword (e.g., "rucking", "cold plunge", "protein powder") → Scrapes top YouTube videos with full transcripts → Logs everything to Airtable—views, likes, publish date → Gemini analyzes each transcript automatically → Extracts hooks, angles, and themes from every video No watching hours of content. No manual note-taking. No "let me rewatch that part" loops. What lands in your Airtable: - Video URL, title, channel, and performance metrics - AI-extracted hooks (what grabbed attention in the first 10 seconds) - Angles (the unique claim or perspective that worked) - Themes (the narrative structure driving the video) - Full transcripts for deeper research Built 100% in n8n. Want the complete n8n workflow + Airtable base? > Comment "YT" > Like this post And I'll send it over (must be following so I can DM)

Mike Futia

159,322 görüntüleme • 8 ay önce

This tool is for public companies: Sentinel Very interesting and enlightening video from our CEO/Founder Krishan Arora. Def worth a listen! These days 37% of all new stock market buys come from retail investors vs 7% a mere 10 years ago. Sentinel ( tells you what social media (retail) is saying about your stock, and (if needed) writes a press release for you in less than one second! One famous public company we onboarded—that everyone knows the name of—has 1,300 individual conversation points over the last 30 days across X, Reddit, Discord, YouTube and Google News. We analyze all 1300 conversations, both bullish and bearish; we categorize them all and send the company to their 1 page website (check the video) We have been in business for 60 days and have onboarded $40B worth of public companies, a few in the Fortune 500! We can help EVERY single public company—we are the only solution—manage their “Social Media Reputation” #POSITIVITY

This tool is for public companies: Sentinel Very interesting and enlightening video from our CEO/Founder Krishan Arora. Def worth a listen! These days 37% of all new stock market buys come from retail investors vs 7% a mere 10 years ago. Sentinel ( tells you what social media (retail) is saying about your stock, and (if needed) writes a press release for you in less than one second! One famous public company we onboarded—that everyone knows the name of—has 1,300 individual conversation points over the last 30 days across X, Reddit, Discord, YouTube and Google News. We analyze all 1300 conversations, both bullish and bearish; we categorize them all and send the company to their 1 page website (check the video) We have been in business for 60 days and have onboarded $40B worth of public companies, a few in the Fortune 500! We can help EVERY single public company—we are the only solution—manage their “Social Media Reputation” #POSITIVITY

phil_hellmuth

10,549 görüntüleme • 1 ay önce

Mamdani and his team are defining the new rules of politics, in my view. His win is a demonstration of data science. He did a spectacular job in making sure none of his competitors got near him in the vote by using social media. So, he is in fact forming a new form of leadership for the Democratic Party, but above all, for all politicians going into the midterms, they have to look at his model. He did it in a way that no one has ever done it before. He knew every algorithm on every platform, how to keep every engagement in the top quartile. That's how it's done.

Mamdani and his team are defining the new rules of politics, in my view. His win is a demonstration of data science. He did a spectacular job in making sure none of his competitors got near him in the vote by using social media. So, he is in fact forming a new form of leadership for the Democratic Party, but above all, for all politicians going into the midterms, they have to look at his model. He did it in a way that no one has ever done it before. He knew every algorithm on every platform, how to keep every engagement in the top quartile. That's how it's done.

Kevin O'Leary aka Mr. Wonderful

57,411 görüntüleme • 8 ay önce