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Competitive analysis just got 10x easier with Firecrawl's new /search endpoint 🚀 We built a pipeline that automatically finds competitors, scrapes their site, then generates a report. All powered by a LangChain StateGraph which handles the entire workflow.

Caleb Peffer (Hiring!)

4,931 subscribers

16,541 görüntüleme • 1 yıl önce •via X (Twitter)

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Caleb Peffer (Hiring!) profil fotoğrafı

Caleb Peffer (Hiring!)1 yıl önce

Try it out yourself here, powered by @Replit: Support us on our PH launch today 🚀: And here are the search docs (launching today 🔥):

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RTTS2 yıl önce

API testing of interfaces is critical to determine if they meet requirements for functionality, reliability, performance, and security. Check out RTTS - the automated testing experts since 1996. #API #testautomation #integrationtest

Eric Ciarla (hiring) profil fotoğrafı

Eric Ciarla (hiring)1 yıl önce

@firecrawl_dev @LangChainAI Yo this is crazy!!!

Kevin Newman profil fotoğrafı

Kevin Newman1 yıl önce

@firecrawl_dev @LangChainAI @homeservicebase check it out

Edward Su profil fotoğrafı

Edward Su1 yıl önce

@firecrawl_dev @LangChainAI What's this application, it looks like you can run cmd and edit code at the same time.

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ANwTGrsNeqRyKIg : priv/acc1 yıl önce

@firecrawl_dev @LangChainAI super power 🤯

Benzer Videolar

Next week we're dropping Open Lovable v3 👀 With this new version you just drop in a URL and it extends your brand styles effortlessly in the web apps you build. This is all powered by Firecrawl's new branding format, which is now available through our /scrape endpoint 🔥

Developers Digest

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INSANE: Grok 3 + Replit Agent is a Superpower!! Using the pair, I built an AI agent that reviews my Pull Requests Here's the flow: • Grok 3 generates PR-reviewing agent code using Composio + LlamaIndex • Replit Agent automatically crafts the front-end interface • Get a ready-to-run workflow where you paste the url to your PR, and the agent generates a code review instantly with suggestions. Built with Grok Replit ⠕ Agent Powered by LlamaIndex 🦙 Groq Inc repl link:

INSANE: Grok 3 + Replit Agent is a Superpower!! Using the pair, I built an AI agent that reviews my Pull Requests Here's the flow: • Grok 3 generates PR-reviewing agent code using Composio + LlamaIndex • Replit Agent automatically crafts the front-end interface • Get a ready-to-run workflow where you paste the url to your PR, and the agent generates a code review instantly with suggestions. Built with Grok Replit ⠕ Agent Powered by LlamaIndex 🦙 Groq Inc repl link:

Karan Vaidya

1,684,869 görüntüleme • 1 yıl önce

We just cracked document editing without drawing boxes. We’re excited to launch Edit – a new endpoint that fills out any document automatically. Edit revolutionizes document automation by automatically finding all blank fields, tables, and checkboxes in forms, then intelligently filling them with your data. To try it, sign up for the waitlist at or see it in action down below 🧵

We just cracked document editing without drawing boxes. We’re excited to launch Edit – a new endpoint that fills out any document automatically. Edit revolutionizes document automation by automatically finding all blank fields, tables, and checkboxes in forms, then intelligently filling them with your data. To try it, sign up for the waitlist at or see it in action down below 🧵

Reducto

260,110 görüntüleme • 1 yıl önce

We all know adding media automatically boosts your posts on the algorithm So I built a tool that can generate any image with your tweets using Nano Banana. You can search for the right memes, create infographics and more with JUST text

We all know adding media automatically boosts your posts on the algorithm So I built a tool that can generate any image with your tweets using Nano Banana. You can search for the right memes, create infographics and more with JUST text

Andros

56,077 görüntüleme • 11 ay önce

We built a tool that lets Claude Code autonomously test your entire mobile app. It navigates your app, opens screens, reads the debug logs, finds performance problems, and hands you a structured report. All it takes is one prompt.

We built a tool that lets Claude Code autonomously test your entire mobile app. It navigates your app, opens screens, reads the debug logs, finds performance problems, and hands you a structured report. All it takes is one prompt.

Software Mansion

49,704 görüntüleme • 2 ay önce

Found a way to make nano-banana-pro insanely cost-effective on fal I built a workflow that generates 9 4K images for a total of $0.21. That’s just $0.023 per image. That is a ~92% cost reduction. The key is grid generation. I added a 'Crop Node' as a workflow utility specifically for this. It takes the grid output, splits it, and then we upscale everything using SeedVR

Found a way to make nano-banana-pro insanely cost-effective on fal I built a workflow that generates 9 4K images for a total of $0.21. That’s just $0.023 per image. That is a ~92% cost reduction. The key is grid generation. I added a 'Crop Node' as a workflow utility specifically for this. It takes the grid output, splits it, and then we upscale everything using SeedVR

ilker

148,367 görüntüleme • 8 ay önce

Excited to announce our new preprint! We developed a method to automatically extract standard 2D views from 3D echocardiography volumes. This method allows for novel approach to echo acquisition: Instead of moving the probe across patients chest in the search of standard views, a sonographer would only have to place the probe in the apical position to capture the whole snapshot of the heart, which is then decomposed into all standard views with the similar quality to the views obtained in the traditional pipeline. That way we benefit from the speed of 3D acquisition while allowing clinicians to preserve their familiar 2D interpretation workflow.

Excited to announce our new preprint! We developed a method to automatically extract standard 2D views from 3D echocardiography volumes. This method allows for novel approach to echo acquisition: Instead of moving the probe across patients chest in the search of standard views, a sonographer would only have to place the probe in the apical position to capture the whole snapshot of the heart, which is then decomposed into all standard views with the similar quality to the views obtained in the traditional pipeline. That way we benefit from the speed of 3D acquisition while allowing clinicians to preserve their familiar 2D interpretation workflow.

Milos Vukadinovic

11,193 görüntüleme • 5 ay önce

New Cardano Roadmap just dropped! 🚀 After the majority of Input Output's proposals got funded, let's take a look at - what's actually being built - & which new features we can expect over the coming year and beyond

New Cardano Roadmap just dropped! 🚀 After the majority of Input Output's proposals got funded, let's take a look at - what's actually being built - & which new features we can expect over the coming year and beyond

Linda

15,311 görüntüleme • 2 ay önce

HERMES AGENT BUILT A SKILL THAT AUTOMATED AN 8-HOUR WORKFLOW INTO 80 MINUTES. THE AGENT BUILT IT FROM ITS OWN COMPLETED SESSIONS. one user ran their customer pipeline through Hermes repeatedly: meetings → recordings → product requirements → technical specs → development → delivery. after enough runs, Hermes identified the pattern and created a skill that handles the full pipeline: → takes meeting recordings → extracts requirements automatically → runs research on the extracted data → generates product requirement documents → generates technical specifications → delegates the build to a coding agent → sends a link to the finished product what Hermes skills contain: → when to use (trigger conditions) → step-by-step procedure → known pitfalls to avoid → verification steps (how to confirm it worked) stored as markdown in ~/.hermes/skills/. readable, editable, permanent. agents with 20+ self-created skills finish similar future tasks ~40% faster. month 1 you explain everything. month 3 the agent runs your core workflows from the skills it built along the way. full breakdown of Hermes as a Personal AI OS in the article 👇

HERMES AGENT BUILT A SKILL THAT AUTOMATED AN 8-HOUR WORKFLOW INTO 80 MINUTES. THE AGENT BUILT IT FROM ITS OWN COMPLETED SESSIONS. one user ran their customer pipeline through Hermes repeatedly: meetings → recordings → product requirements → technical specs → development → delivery. after enough runs, Hermes identified the pattern and created a skill that handles the full pipeline: → takes meeting recordings → extracts requirements automatically → runs research on the extracted data → generates product requirement documents → generates technical specifications → delegates the build to a coding agent → sends a link to the finished product what Hermes skills contain: → when to use (trigger conditions) → step-by-step procedure → known pitfalls to avoid → verification steps (how to confirm it worked) stored as markdown in ~/.hermes/skills/. readable, editable, permanent. agents with 20+ self-created skills finish similar future tasks ~40% faster. month 1 you explain everything. month 3 the agent runs your core workflows from the skills it built along the way. full breakdown of Hermes as a Personal AI OS in the article 👇

YanXbt

29,819 görüntüleme • 2 ay önce

Travel planning just got easier in the Expedia app, thanks to the iOS beta launch of a new experience powered by #ChatGPT. See how Expedia members can start an open-ended conversation to get inspired for their next trip:

Travel planning just got easier in the Expedia app, thanks to the iOS beta launch of a new experience powered by #ChatGPT. See how Expedia members can start an open-ended conversation to get inspired for their next trip:

Expedia Group

23,612 görüntüleme • 3 yıl önce

I just built RalphBlaster™ 😋 and it's kind of absurd. My entire dev workflow is now: - create a ticket - click to generate a PRD - approve it - Ralph handles the rest in an isolated worktree I get pinged when it's done. Files clean up automatically. I don't touch an editor, terminal, or Claude Code. It's a new world. Huge shoutout to Ryan Carson for being my go-to source on all this, and for his invaluable repos.

I just built RalphBlaster™ 😋 and it's kind of absurd. My entire dev workflow is now: - create a ticket - click to generate a PRD - approve it - Ralph handles the rest in an isolated worktree I get pinged when it's done. Files clean up automatically. I don't touch an editor, terminal, or Claude Code. It's a new world. Huge shoutout to Ryan Carson for being my go-to source on all this, and for his invaluable repos.

Mac Martine

226,746 görüntüleme • 7 ay önce

I built a system that automatically filters 600+ coins and finds the ones already trending across multiple timeframes. Instead of scanning everything manually, we can focus on the setups with real breakout potential. All of my Discord members get access to it.

I built a system that automatically filters 600+ coins and finds the ones already trending across multiple timeframes. Instead of scanning everything manually, we can focus on the setups with real breakout potential. All of my Discord members get access to it.

Philakone

16,316 görüntüleme • 23 gün önce

Preview of our DeepResearchSwarm™ It's incomprehensibly fast as it leverages a multi-agent architecture instead of just one agent. It utilizes a joint hierarchical-parallel architecture that creates a plan and then concurrently executes the plan with multiple search agents. Workflow: Task → Research Director → multiple search agents → final summary by summarization agent. Stay tuned for the release ↓

Preview of our DeepResearchSwarm™ It's incomprehensibly fast as it leverages a multi-agent architecture instead of just one agent. It utilizes a joint hierarchical-parallel architecture that creates a plan and then concurrently executes the plan with multiple search agents. Workflow: Task → Research Director → multiple search agents → final summary by summarization agent. Stay tuned for the release ↓

swarms

17,732 görüntüleme • 1 yıl önce

Most SEO teams aren't losing because of poor content. They're losing because they don't know what content is missing. I recently used Kuse to analyze a website against its competitors and uncover content opportunities that would have taken hours to find manually. The workflow helped: - Compare a site against competing websites - Surface content gaps across important topics - Identify missing pages and content opportunities - Reveal areas where competitors have stronger coverage - Organize findings into a clear report What normally requires jumping between multiple tools, spreadsheets, and browser tabs became a structured workflow that ran automatically. The interesting part wasn't just the analysis. It was how easy it was to adapt the workflow. Kuse provides workflow templates that can be customized for different use cases, so instead of building automations from scratch, you can start with an existing workflow and tailor it to your needs. And because Kuse connects with thousands of popular tools, the insights can flow directly into the systems your team already uses. AI workflows are most valuable when they help teams spend less time collecting information and more time acting on it. This was a good example of that. If competitor research, SEO analysis, or repetitive reporting is part of your workflow, Kuse is worth exploring. Check it out:

Most SEO teams aren't losing because of poor content. They're losing because they don't know what content is missing. I recently used Kuse to analyze a website against its competitors and uncover content opportunities that would have taken hours to find manually. The workflow helped: - Compare a site against competing websites - Surface content gaps across important topics - Identify missing pages and content opportunities - Reveal areas where competitors have stronger coverage - Organize findings into a clear report What normally requires jumping between multiple tools, spreadsheets, and browser tabs became a structured workflow that ran automatically. The interesting part wasn't just the analysis. It was how easy it was to adapt the workflow. Kuse provides workflow templates that can be customized for different use cases, so instead of building automations from scratch, you can start with an existing workflow and tailor it to your needs. And because Kuse connects with thousands of popular tools, the insights can flow directly into the systems your team already uses. AI workflows are most valuable when they help teams spend less time collecting information and more time acting on it. This was a good example of that. If competitor research, SEO analysis, or repetitive reporting is part of your workflow, Kuse is worth exploring. Check it out:

Utkarsh Sharma

26,361 görüntüleme • 2 ay önce

Agents Are Replacing SaaS 🟢 And We’re Living It At Assisterr, we don’t just build AI agents - we use them Our own infrastructure has already replaced most traditional SaaS tools with custom-built AI agents that handle everything from analytics and reporting to workflow automation Need deep product insights? Our Analytics Assistant tracks real-time data, generates reports, and delivers actionable insights—automatically 🚀 Need a new tool? We don’t waste time looking for SaaS alternatives - we just build a custom agent. No code, no hassle, just instant automation We’re committed to making this accessible to everyone—so anyone can create, customize, and deploy AI agents tailored to their needs The future isn’t SaaS. The future is agents. And with Assisterr, it’s already here

Agents Are Replacing SaaS 🟢 And We’re Living It At Assisterr, we don’t just build AI agents - we use them Our own infrastructure has already replaced most traditional SaaS tools with custom-built AI agents that handle everything from analytics and reporting to workflow automation Need deep product insights? Our Analytics Assistant tracks real-time data, generates reports, and delivers actionable insights—automatically 🚀 Need a new tool? We don’t waste time looking for SaaS alternatives - we just build a custom agent. No code, no hassle, just instant automation We’re committed to making this accessible to everyone—so anyone can create, customize, and deploy AI agents tailored to their needs The future isn’t SaaS. The future is agents. And with Assisterr, it’s already here

assisterr

28,822 görüntüleme • 1 yıl önce

NEW: Perplexity just released pplx-embed, a series of powerful embedding models. Inspired by their logo, I built a small semantic search demo: enter a query and the model retrieves the most relevant page. Everything runs locally in your browser with Transformers.js and Three.js

Xenova

11,092 görüntüleme • 5 ay önce

THIS GUY BUILT A SYSTEM THAT GETS SMARTER EVERY TIME HE USES IT AND IT LOOKS LIKE A GALAXY he types one command into Claude Code it finds sources, runs analysis through NotebookLM, saves everything to Obsidian automatically graph in the background is every idea he's ever researched - all linked together system handles the research so he only has to think about what to do with it most people are still copy-pasting into Notion and losing everything by next week full setup in the article

THIS GUY BUILT A SYSTEM THAT GETS SMARTER EVERY TIME HE USES IT AND IT LOOKS LIKE A GALAXY he types one command into Claude Code it finds sources, runs analysis through NotebookLM, saves everything to Obsidian automatically graph in the background is every idea he's ever researched - all linked together system handles the research so he only has to think about what to do with it most people are still copy-pasting into Notion and losing everything by next week full setup in the article

monokern

45,188 görüntüleme • 2 ay önce

NEW: A stunning new project from Lawfare's Katherine Pompilio finds that 97 Jan. 6ers who received clemency for their role in the Capitol riot then got arrested, charged, and/or convicted with subsequent crimes—a number much higher than previously reported.

NEW: A stunning new project from Lawfare's Katherine Pompilio finds that 97 Jan. 6ers who received clemency for their role in the Capitol riot then got arrested, charged, and/or convicted with subsequent crimes—a number much higher than previously reported.

Tyler McBrien

280,726 görüntüleme • 2 ay önce

A synthetic biologist just designed an RNA vaccine for canine cancer with just $100 in AI credits. His tech stack: an OpenClaw agent running Claude Sonnet 4.6 as the workhorse. BIOS by Bio Protocol as the AI scientist for literature search and data analysis. A minimal cloud setup with no GPUs and no model training. His words: "Could this design really work? Did we actually design a medicine which usually takes many years and many millions of dollars in three days and with a hundred dollars in AI credits?" The answer is closer than you'd think. He ran a full bioinformatics workflow and came away with what he calls a "bonafide, totally plausible neoantigen vaccine candidate." He also said something that matters more than the result: "If we fuck this up, people can die. So I need to say that in all humility. There is no way that I got this perfect. There is a mistake in here for sure." That's the difference between someone doing real science with AI tools and someone doing a demo. He knows where the limits are because he has the domain expertise to see them. This is what BIOS was built for. A callable AI scientist that any agent or researcher can plug into their workflow for deep literature search and analysis. Jake Wintermute 🧬/acc used it alongside OpenClaw and got from hypothesis to vaccine design in a weekend. Three days. One hundred dollars. One real candidate.

A synthetic biologist just designed an RNA vaccine for canine cancer with just $100 in AI credits. His tech stack: an OpenClaw agent running Claude Sonnet 4.6 as the workhorse. BIOS by Bio Protocol as the AI scientist for literature search and data analysis. A minimal cloud setup with no GPUs and no model training. His words: "Could this design really work? Did we actually design a medicine which usually takes many years and many millions of dollars in three days and with a hundred dollars in AI credits?" The answer is closer than you'd think. He ran a full bioinformatics workflow and came away with what he calls a "bonafide, totally plausible neoantigen vaccine candidate." He also said something that matters more than the result: "If we fuck this up, people can die. So I need to say that in all humility. There is no way that I got this perfect. There is a mistake in here for sure." That's the difference between someone doing real science with AI tools and someone doing a demo. He knows where the limits are because he has the domain expertise to see them. This is what BIOS was built for. A callable AI scientist that any agent or researcher can plug into their workflow for deep literature search and analysis. Jake Wintermute 🧬/acc used it alongside OpenClaw and got from hypothesis to vaccine design in a weekend. Three days. One hundred dollars. One real candidate.

Bio Protocol

10,742 görüntüleme • 4 ay önce