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Introducing Applied Labs, the world's first truly AI native CX platform. Enterprise CX companies have completely ignored the mid market, which is the hungriest buyer in software right now. They're overpaying for tools, understaffed, and losing customers to churn signals buried across systems. Until now. With Applied Labs, you... show more

Michael Woo

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384,468 次观看 • 3 个月前 •via X (Twitter)

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My friend applied to 450 tech job applications over three years. No MIT. No Stanford. Last week Anthropic offered him $750,000. I asked him how he broke in with zero background. He sent me the exact video that helped him to get in. Anthropic's 2 hour course on landing an AI career in 2026. Anthropic's core team breaks down exactly how to build AI agents from scratch. I watched it last night. Halfway through, I realized breaking into an AI lab takes weeks, not years. Bookmark this and read the article below. • 00:00 - building AI agents • 28:51 - AI agent workflow • 54:04 - memory for AI agents • 1:28:40 - production AI agent • 1:55:30 - anthropic hiring process

My friend applied to 450 tech job applications over three years. No MIT. No Stanford. Last week Anthropic offered him $750,000. I asked him how he broke in with zero background. He sent me the exact video that helped him to get in. Anthropic's 2 hour course on landing an AI career in 2026. Anthropic's core team breaks down exactly how to build AI agents from scratch. I watched it last night. Halfway through, I realized breaking into an AI lab takes weeks, not years. Bookmark this and read the article below. • 00:00 - building AI agents • 28:51 - AI agent workflow • 54:04 - memory for AI agents • 1:28:40 - production AI agent • 1:55:30 - anthropic hiring process

Roan

13,799 次观看 • 1 个月前

For 20+ years, we've stayed ahead of every major shift in technology. Today we take the next one: we're introducing the world's first AI-native tech services model. Most of the industry is adding AI to the way it already works. Like bolting a copilot onto old processes and calling it transformation because it's faster than before. That's not what enterprises actually need. works differently. It provides instant access to AI Pods (service units run by AI agents and supervised by Globant experts) that deliver tech services at machine speed, but with the rigor, the governance, and the quality that enterprise-grade work demands. It is a smarter model, running the right AI through parallel agents, loops, workflows, and deterministic processes. With organizations access AI services with transparent, output or consumption-linked pricing, not per hour or per seat, and they own everything they produce. We are bringing the speed AI promises, with the rigor and quality any business needs. Join the waitlist at

For 20+ years, we've stayed ahead of every major shift in technology. Today we take the next one: we're introducing the world's first AI-native tech services model. Most of the industry is adding AI to the way it already works. Like bolting a copilot onto old processes and calling it transformation because it's faster than before. That's not what enterprises actually need. works differently. It provides instant access to AI Pods (service units run by AI agents and supervised by Globant experts) that deliver tech services at machine speed, but with the rigor, the governance, and the quality that enterprise-grade work demands. It is a smarter model, running the right AI through parallel agents, loops, workflows, and deterministic processes. With organizations access AI services with transparent, output or consumption-linked pricing, not per hour or per seat, and they own everything they produce. We are bringing the speed AI promises, with the rigor and quality any business needs. Join the waitlist at

Martin Migoya

392,166 次观看 • 21 天前

This 1-hour Stanford lecture will teach you how to automate your entire daily work routine with AI better than 99% of "AI automation" content on YouTube No tools to sell you. No fluff. Just the raw science behind how AI agents think, plan, and execute tasks on their own Led by GitHub's Principal ML Researcher and recorded for FREE Most people spend 2-3 hours/day on repetitive work that AI can handle: emails, reports, scheduling, code reviews, data entry, status updates This lecture shows you exactly how the systems behind that automation actually work like reflection, planning, tool use, and decision-making Bookmark it. 1 hour now = hundreds of hours saved later

This 1-hour Stanford lecture will teach you how to automate your entire daily work routine with AI better than 99% of "AI automation" content on YouTube No tools to sell you. No fluff. Just the raw science behind how AI agents think, plan, and execute tasks on their own Led by GitHub's Principal ML Researcher and recorded for FREE Most people spend 2-3 hours/day on repetitive work that AI can handle: emails, reports, scheduling, code reviews, data entry, status updates This lecture shows you exactly how the systems behind that automation actually work like reflection, planning, tool use, and decision-making Bookmark it. 1 hour now = hundreds of hours saved later

Ronin

62,264 次观看 • 4 个月前

Gokul explains why outcome-based software companies like Zendesk are more exposed to AI than systems of record like NetSuite, and why public markets are not distinguishing between the two. He argues that the only way AI-native startups can disrupt systems of record is by spending 1-2 years building migration tools to get data off of incumbent platforms. "The software companies that should be the most worried right now is where they are pricing the product based on utility. Zendesk is a good example. Instead of paying for 50 Zendesk seats, you can pay for 20 and I can have 30 AI agents sitting next to Zendesk. For these companies you need to change your pricing model to be based on outcome. It's going to be hard for them to stay public. The companies that are less exposed are ones based on data that has been collected and captured over a period of time. ERP is a great example. There is no compelling reason for someone to put their career at stake by ripping out NetSuite. NetSuite has more time to build AI agents on top of it because they have the data, they can train the AI agent on top of it and bundle it. I think the public markets do not distinguish between these two types of companies."

Gokul explains why outcome-based software companies like Zendesk are more exposed to AI than systems of record like NetSuite, and why public markets are not distinguishing between the two. He argues that the only way AI-native startups can disrupt systems of record is by spending 1-2 years building migration tools to get data off of incumbent platforms. "The software companies that should be the most worried right now is where they are pricing the product based on utility. Zendesk is a good example. Instead of paying for 50 Zendesk seats, you can pay for 20 and I can have 30 AI agents sitting next to Zendesk. For these companies you need to change your pricing model to be based on outcome. It's going to be hard for them to stay public. The companies that are less exposed are ones based on data that has been collected and captured over a period of time. ERP is a great example. There is no compelling reason for someone to put their career at stake by ripping out NetSuite. NetSuite has more time to build AI agents on top of it because they have the data, they can train the AI agent on top of it and bundle it. I think the public markets do not distinguish between these two types of companies."

Patrick OShaughnessy

394,051 次观看 • 7 个月前

$This is the biggest irony in tech history. Microsoft beat revenue estimates. Stock plunged 11%, wiped out $400 BILLION in market cap. Salesforce reported growth. Stock fell 5.6%. ServiceNow beat earnings. Stock crashed 11%. SAP beat projections. Stock dropped 16%. Entire software sector entered bear market territory. Down 22% from peak. These are the companies everyone said would WIN from AI. They spent billions BUYING AI companies. ServiceNow: $7.75 billion for Armis. Salesforce: $8 billion for Informatica. They launched AI products. Built AI workflows. Hired AI teams. And the market said: You're all dead. Because investors just realized something nobody wanted to admit: AI doesn't make software companies stronger. AI makes software companies OBSOLETE. Morgan Stanley: "In an environment of heightened investor skepticism, stable growth falls short of shifting the narrative." Good earnings aren't enough anymore. The market is pricing in a world where AI replaces the software these companies sell. ServiceNow CEO tried defending on the earnings call: "AI needs workflow orchestration. ServiceNow is the gateway to this shift." Market response: 11% crash. Because here's what he didn't say: If AI can write code, automate workflows, and generate apps at a fraction of the cost, why would anyone pay $50,000 per year for enterprise software licenses? The per-seat pricing model that made SaaS companies rich is getting murdered by AI efficiency. One AI agent replaces 10 seats. One prompt replaces months of custom development. One LLM call replaces entire software categories. Klarna already proved it. CEO said they pulled Salesforce out of their stack. Built everything themselves using AI. And that's just the beginning. The software apocalypse hit hardest on companies that INVESTED IN AI: Atlassian: down 12.6% Intuit: down 7.8% HubSpot: down 11.5% Zscaler: down 6.3% Meanwhile, the companies ENABLING AI made money: Nvidia: up Semiconductor stocks: surging Memory firms: rallying The divide is brutal. Hardware companies print cash. Software companies get destroyed. Because in an AI-first world, you need GPUs to build the models. But you don't need software subscriptions when the AI builds the software for you. Jim Cramer called it the "P/E multiple compression crisis." Translation: Investors don't care about earnings anymore. They care about whether your business model survives the next 5 years. And right now software business models look doomed. They're literally stuck: If they DON'T invest in AI, they fall behind. If they DO invest in AI, they cannibalize their own products. It's a death spiral with no exit. ServiceNow spent $12 BILLION on acquisitions in 2025 alone. Trying to buy their way into relevance. And yesterday the market cooked them. The craziest thing to me tho... Most software companies beat earnings. Revenue was solid. Growth was fine. But it didn't matter. Because the market stopped pricing software on what it earns TODAY. It's pricing software on what it's worth in a world where AI does the job for free. And in that world these companies are worth nothing. This is the biggest sector repricing since 2008. $500 billion in market value gone in ONE DAY. And it's not stopping. Because every company watching this is thinking the same thing: "If I can replace ServiceNow with 3 AI agents and save $10 million per year, why wouldn't I?" The answer used to be: "Because you need enterprise-grade reliability." But now? AI agents are getting reliable. Fast. Software companies just realized they're competing with open-source models that cost $0.02 per 1,000 tokens. You can't win a pricing war against free. The companies that spent BILLIONS preparing for AI are getting killed BY AI. What an irony.$

This is the biggest irony in tech history. Microsoft beat revenue estimates. Stock plunged 11%, wiped out $400 BILLION in market cap. Salesforce reported growth. Stock fell 5.6%. ServiceNow beat earnings. Stock crashed 11%. SAP beat projections. Stock dropped 16%. Entire software sector entered bear market territory. Down 22% from peak. These are the companies everyone said would WIN from AI. They spent billions BUYING AI companies. ServiceNow: $7.75 billion for Armis. Salesforce: $8 billion for Informatica. They launched AI products. Built AI workflows. Hired AI teams. And the market said: You're all dead. Because investors just realized something nobody wanted to admit: AI doesn't make software companies stronger. AI makes software companies OBSOLETE. Morgan Stanley: "In an environment of heightened investor skepticism, stable growth falls short of shifting the narrative." Good earnings aren't enough anymore. The market is pricing in a world where AI replaces the software these companies sell. ServiceNow CEO tried defending on the earnings call: "AI needs workflow orchestration. ServiceNow is the gateway to this shift." Market response: 11% crash. Because here's what he didn't say: If AI can write code, automate workflows, and generate apps at a fraction of the cost, why would anyone pay $50,000 per year for enterprise software licenses? The per-seat pricing model that made SaaS companies rich is getting murdered by AI efficiency. One AI agent replaces 10 seats. One prompt replaces months of custom development. One LLM call replaces entire software categories. Klarna already proved it. CEO said they pulled Salesforce out of their stack. Built everything themselves using AI. And that's just the beginning. The software apocalypse hit hardest on companies that INVESTED IN AI: Atlassian: down 12.6% Intuit: down 7.8% HubSpot: down 11.5% Zscaler: down 6.3% Meanwhile, the companies ENABLING AI made money: Nvidia: up Semiconductor stocks: surging Memory firms: rallying The divide is brutal. Hardware companies print cash. Software companies get destroyed. Because in an AI-first world, you need GPUs to build the models. But you don't need software subscriptions when the AI builds the software for you. Jim Cramer called it the "P/E multiple compression crisis." Translation: Investors don't care about earnings anymore. They care about whether your business model survives the next 5 years. And right now software business models look doomed. They're literally stuck: If they DON'T invest in AI, they fall behind. If they DO invest in AI, they cannibalize their own products. It's a death spiral with no exit. ServiceNow spent $12 BILLION on acquisitions in 2025 alone. Trying to buy their way into relevance. And yesterday the market cooked them. The craziest thing to me tho... Most software companies beat earnings. Revenue was solid. Growth was fine. But it didn't matter. Because the market stopped pricing software on what it earns TODAY. It's pricing software on what it's worth in a world where AI does the job for free. And in that world these companies are worth nothing. This is the biggest sector repricing since 2008. $500 billion in market value gone in ONE DAY. And it's not stopping. Because every company watching this is thinking the same thing: "If I can replace ServiceNow with 3 AI agents and save $10 million per year, why wouldn't I?" The answer used to be: "Because you need enterprise-grade reliability." But now? AI agents are getting reliable. Fast. Software companies just realized they're competing with open-source models that cost $0.02 per 1,000 tokens. You can't win a pricing war against free. The companies that spent BILLIONS preparing for AI are getting killed BY AI. What an irony.

Ricardo

1,815,638 次观看 • 6 个月前

What does it actually mean to be AI native? There was no clear guide on the internet for how to become AI native so we built the definitive one (60 min masterclass): 1. An AI native org has 3 layers: people for strategy and taste, agents for execution, and a shared context layer that makes the entire company readable to agents. 2. AI eats the middle of your work. You used to spend 80% of your day on execution. Now agents do that. Your job is the bookends: deciding what to do and judging whether it's good enough. 3. Everyone is a manager now. Your output is the output of your agents. If your agents produce garbage, that's on you. You set them up wrong. 4. Using ChatGPT doesn't make you AI native. That's like having a website and calling yourself a tech company lol. 5. No AI native org without AI native people. Most companies skip straight to the tools. That's why it fails. If your people don't understand how to manage agents, the tech doesn't matter. 6. Making your company "readable" to agents is the real work. Every process, every decision, every piece of knowledge needs to exist in a format an agent can consume. Most companies are nowhere close. 7. Speed without signal is just expensive chaos. You need the system to move fast AND know if you're moving in the right direction. 8. The skill chain is how agents get good at your specific workflows. Skills build on skills. The more you invest in them, the more your company compounds. 9. The moat is the system. People managing agents, agents reading from rich context, the whole thing getting smarter every week. That compounds. Your competitor can copy your tools. They can't copy your system. Full episode with Theo Tabah from LCA on The Startup Ideas Podcast (SIP) 🧃. This is the stuff we normally keep internal but all the sauce is yours. Theo Tabah is the brains behind advising the world's biggest companies on AI and building AI products. Your fav CEO's first call for figuring out AI. You are in for a treat Become AI native in under 60 minutes Watch

What does it actually mean to be AI native? There was no clear guide on the internet for how to become AI native so we built the definitive one (60 min masterclass): 1. An AI native org has 3 layers: people for strategy and taste, agents for execution, and a shared context layer that makes the entire company readable to agents. 2. AI eats the middle of your work. You used to spend 80% of your day on execution. Now agents do that. Your job is the bookends: deciding what to do and judging whether it's good enough. 3. Everyone is a manager now. Your output is the output of your agents. If your agents produce garbage, that's on you. You set them up wrong. 4. Using ChatGPT doesn't make you AI native. That's like having a website and calling yourself a tech company lol. 5. No AI native org without AI native people. Most companies skip straight to the tools. That's why it fails. If your people don't understand how to manage agents, the tech doesn't matter. 6. Making your company "readable" to agents is the real work. Every process, every decision, every piece of knowledge needs to exist in a format an agent can consume. Most companies are nowhere close. 7. Speed without signal is just expensive chaos. You need the system to move fast AND know if you're moving in the right direction. 8. The skill chain is how agents get good at your specific workflows. Skills build on skills. The more you invest in them, the more your company compounds. 9. The moat is the system. People managing agents, agents reading from rich context, the whole thing getting smarter every week. That compounds. Your competitor can copy your tools. They can't copy your system. Full episode with Theo Tabah from LCA on The Startup Ideas Podcast (SIP) 🧃. This is the stuff we normally keep internal but all the sauce is yours. Theo Tabah is the brains behind advising the world's biggest companies on AI and building AI products. Your fav CEO's first call for figuring out AI. You are in for a treat Become AI native in under 60 minutes Watch

GREG ISENBERG

84,638 次观看 • 2 个月前

Google just released a free 2-hour+ course on full agent engineering. How to go from one prompt to a system that runs while you sleep: 38:46 - Build your first AI agent 54:46 - Connect MCP tools 1:12:43 - Run agents with four loop patterns 1:20:57 - Turn agent loops into graphs 2:22:31 - Build the complete autonomous system Most people are still building one agent and stopping there. Google is already teaching the full stack: Agents → Tools → Loops → Graphs → Autonomous Systems Single agents are the old workflow. Systems that run without you are the new one. This course is worth more than most paid agent engineering bootcamps. Bookmark and watch it today Then read the full graph engineering playbook below

Google just released a free 2-hour+ course on full agent engineering. How to go from one prompt to a system that runs while you sleep: 38:46 - Build your first AI agent 54:46 - Connect MCP tools 1:12:43 - Run agents with four loop patterns 1:20:57 - Turn agent loops into graphs 2:22:31 - Build the complete autonomous system Most people are still building one agent and stopping there. Google is already teaching the full stack: Agents → Tools → Loops → Graphs → Autonomous Systems Single agents are the old workflow. Systems that run without you are the new one. This course is worth more than most paid agent engineering bootcamps. Bookmark and watch it today Then read the full graph engineering playbook below

Lunar

197,100 次观看 • 28 天前

Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.

Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.

Aaron Levie

91,863 次观看 • 11 个月前

My friend applied to 200 tech jobs in two years. No MIT. No Stanford. Last month Anthropic offered him $750,000. I asked him how he broke in from zero. He sent me the exact video that got him in. Anthropic's 2 hour course on "How to become an AI engineer in 2026" Their core team shows exactly how to architect & build AI agents from scratch. I watched it last night. Halfway through, I realized I could break into an AI lab in weeks, not years. Bookmark this and read the article below. • 00:00 - AI agents with graph engineering • 06:41 - AI agent architecture • 14:31 - building AI agent loops live • 1:15:24 - AI agentic RAG • 2:20:42 - Anthropic interview process

My friend applied to 200 tech jobs in two years. No MIT. No Stanford. Last month Anthropic offered him $750,000. I asked him how he broke in from zero. He sent me the exact video that got him in. Anthropic's 2 hour course on "How to become an AI engineer in 2026" Their core team shows exactly how to architect & build AI agents from scratch. I watched it last night. Halfway through, I realized I could break into an AI lab in weeks, not years. Bookmark this and read the article below. • 00:00 - AI agents with graph engineering • 06:41 - AI agent architecture • 14:31 - building AI agent loops live • 1:15:24 - AI agentic RAG • 2:20:42 - Anthropic interview process

Roan

141,080 次观看 • 28 天前

Andrew Ng just dropped a free 2-hour course On turning one prompt into 100 self-improving agents: 09:14 - Build your first AI agent 33:11 - Run agents inside feedback loops 1:02:46 - Connect agent loops into graphs 1:30:15 - Build agents that rewrite themselves 1:49:05 - Run the entire graph without you Most people build one agent and call it finished Andrew Ng is already teaching everything that comes next: Prompt → Agents → Loops → Graphs → Self-Improving Systems Single agents are the old workflow Systems that improve and run without you are the new one This free 2-hour course is worth more than most $500 agent engineering programs Bookmark and watch it before everyone catches up Then read how to run 1,000 agents from one prompt below ↓

Andrew Ng just dropped a free 2-hour course On turning one prompt into 100 self-improving agents: 09:14 - Build your first AI agent 33:11 - Run agents inside feedback loops 1:02:46 - Connect agent loops into graphs 1:30:15 - Build agents that rewrite themselves 1:49:05 - Run the entire graph without you Most people build one agent and call it finished Andrew Ng is already teaching everything that comes next: Prompt → Agents → Loops → Graphs → Self-Improving Systems Single agents are the old workflow Systems that improve and run without you are the new one This free 2-hour course is worth more than most $500 agent engineering programs Bookmark and watch it before everyone catches up Then read how to run 1,000 agents from one prompt below ↓

rari

44,517 次观看 • 16 天前

🚨We’re excited to Introduce AI HQ — your home for building, activating, and supervising AI agents across your enterprise 🚨 We’re giving IT and business teams an end-to-end platform to co-create AI agents that don’t just assist. They act. These agents are fully integrated, grounded in company data, and built to execute high-impact business processes autonomously. New capabilities in AI HQ include: ⚡ Agent Builder (Beta): Your shared development environment where IT and business teams collaboratively build AI agents. Low-code tools make it easy to map out logic with reusable blocks, connect to systems and data, design interfaces with drag-and-drop simplicity, and more. 🏠 Writer Home: Your personalized AI workspace with 100+ prebuilt agents for every function - from support to sales to HR - ready to go and accessible via desktop, browser, or extensions. It’s your new front door to real AI-powered work. 🛡️ Observability Tools (Beta): Gain full control and visibility into every agent with enterprise-grade observability: monitor activity activity, detect anomalies, and resolve issues before they escalate. It’s how AI moves from experimental to operational. Companies like Uber Commvault and Franklin Templeton (Franklin Templeton) are already using Writer AI agents to reinvent knowledge management, accelerate revenue workflows, and deliver smarter client experiences. This isn’t hype. It’s happening now. 👀 Dive into today’s announcement:

🚨We’re excited to Introduce AI HQ — your home for building, activating, and supervising AI agents across your enterprise 🚨 We’re giving IT and business teams an end-to-end platform to co-create AI agents that don’t just assist. They act. These agents are fully integrated, grounded in company data, and built to execute high-impact business processes autonomously. New capabilities in AI HQ include: ⚡ Agent Builder (Beta): Your shared development environment where IT and business teams collaboratively build AI agents. Low-code tools make it easy to map out logic with reusable blocks, connect to systems and data, design interfaces with drag-and-drop simplicity, and more. 🏠 Writer Home: Your personalized AI workspace with 100+ prebuilt agents for every function - from support to sales to HR - ready to go and accessible via desktop, browser, or extensions. It’s your new front door to real AI-powered work. 🛡️ Observability Tools (Beta): Gain full control and visibility into every agent with enterprise-grade observability: monitor activity activity, detect anomalies, and resolve issues before they escalate. It’s how AI moves from experimental to operational. Companies like Uber Commvault and Franklin Templeton (Franklin Templeton) are already using Writer AI agents to reinvent knowledge management, accelerate revenue workflows, and deliver smarter client experiences. This isn’t hype. It’s happening now. 👀 Dive into today’s announcement:

WRITER

10,837 次观看 • 1 年前

Introducing 𝗔𝗜 𝗧𝗿𝗮𝗳𝗳𝗶𝗰 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 - ChatGPT, Gemini, and other AI systems crawl your site daily, yet Google Analytics shows NOTHING. We reveal this invisible traffic, showing exactly which AI systems visit your content, which pages they value most, and how to optimize for those. 100% Free. 𝗧𝗵𝗲 𝗣𝗿𝗼𝗯𝗹𝗲𝗺: Your current analytics is blind to AI: - ChatGPT, gemini, Claude, etc crawl your site daily — Google Analytics shows NOTHING - Your content gets used in AI responses with zero attribution 𝗧𝗵𝗲 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻 - Server-Side Tracking: 1. Complete AI Crawler Visibility: Track visits from all major AI platforms 2. Content Performance Analysis: Identify which pages AI systems value most 𝗪𝗵𝗮𝘁 𝗺𝗮𝗸𝗲𝘀 𝗶𝘁 𝗽𝗼𝘄𝗲𝗿𝗳𝘂𝗹? - Works at the server level - captures AI visits that JavaScript-based analytics miss completely - Distinguishes between platforms - knows exactly which AI system is accessing your content - Zero performance impact - no code changes to your pages, no site slowdowns This is Free. Link is in the comments.

Introducing 𝗔𝗜 𝗧𝗿𝗮𝗳𝗳𝗶𝗰 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 - ChatGPT, Gemini, and other AI systems crawl your site daily, yet Google Analytics shows NOTHING. We reveal this invisible traffic, showing exactly which AI systems visit your content, which pages they value most, and how to optimize for those. 100% Free. 𝗧𝗵𝗲 𝗣𝗿𝗼𝗯𝗹𝗲𝗺: Your current analytics is blind to AI: - ChatGPT, gemini, Claude, etc crawl your site daily — Google Analytics shows NOTHING - Your content gets used in AI responses with zero attribution 𝗧𝗵𝗲 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻 - Server-Side Tracking: 1. Complete AI Crawler Visibility: Track visits from all major AI platforms 2. Content Performance Analysis: Identify which pages AI systems value most 𝗪𝗵𝗮𝘁 𝗺𝗮𝗸𝗲𝘀 𝗶𝘁 𝗽𝗼𝘄𝗲𝗿𝗳𝘂𝗹? - Works at the server level - captures AI visits that JavaScript-based analytics miss completely - Distinguishes between platforms - knows exactly which AI system is accessing your content - Zero performance impact - no code changes to your pages, no site slowdowns This is Free. Link is in the comments.

Samanyou Garg

975,297 次观看 • 1 年前

Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside one graph: 17:44 - Build your first AI agent 39:30 - Run agents with loop engineering 1:12:38 - Turn agent loops into graphs 1:34:26 - Build agents that throttle themselves 1:55:05 - Orchestrate the full multi-agent system Most people build one agent and stop there. Google is teaching the full stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the new one. This 2-hour watch is worth more than most paid agent engineering courses. Bookmark and watch it today Then read the full architecture below ↓

Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside one graph: 17:44 - Build your first AI agent 39:30 - Run agents with loop engineering 1:12:38 - Turn agent loops into graphs 1:34:26 - Build agents that throttle themselves 1:55:05 - Orchestrate the full multi-agent system Most people build one agent and stop there. Google is teaching the full stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the new one. This 2-hour watch is worth more than most paid agent engineering courses. Bookmark and watch it today Then read the full architecture below ↓

Lunar

399,667 次观看 • 21 天前

This guy used Claude to build a Quant Bot and made +$589,139 on Polymarket. 25,388 predictions with a 63% win rate in 77 days. That comes out to roughly $7,651 in profit per day and almost 14 trades per hour. With $217K in deposits, he is now up 2.7x. About +271.5% ROI. The bot strategy is simple: It finds markets where the pricing is still off. Gets in before the odds fully catch up. Repeats the same setup again and again across many entries. The edge on each trade is small. But scale and repetition turn it into a massive result. Most profitable trades: $17,839 → $36,318 (+$18,478, +103.58%) $3,112 → $15,011 (+$11,898, +382.22%) $10,676 → $22,178 (+$11,502, +107.74%) What makes it work is not one huge trade. It is the same small advantage, applied fast, applied often, and repeated until the pricing gap is gone. I reverse-engineered it. Had Claude rebuild the same logic. One prompt. 90 minutes. Fully deployed. You only need: Claude + a device + 1 hour per day. Giving this free for 24 hours. To get it: 1. Comment the word PROFIT 2. Like and retweet this 3. Follow me Himanshu Kumar so I can DM you

This guy used Claude to build a Quant Bot and made +$589,139 on Polymarket. 25,388 predictions with a 63% win rate in 77 days. That comes out to roughly $7,651 in profit per day and almost 14 trades per hour. With $217K in deposits, he is now up 2.7x. About +271.5% ROI. The bot strategy is simple: It finds markets where the pricing is still off. Gets in before the odds fully catch up. Repeats the same setup again and again across many entries. The edge on each trade is small. But scale and repetition turn it into a massive result. Most profitable trades: $17,839 → $36,318 (+$18,478, +103.58%) $3,112 → $15,011 (+$11,898, +382.22%) $10,676 → $22,178 (+$11,502, +107.74%) What makes it work is not one huge trade. It is the same small advantage, applied fast, applied often, and repeated until the pricing gap is gone. I reverse-engineered it. Had Claude rebuild the same logic. One prompt. 90 minutes. Fully deployed. You only need: Claude + a device + 1 hour per day. Giving this free for 24 hours. To get it: 1. Comment the word PROFIT 2. Like and retweet this 3. Follow me Himanshu Kumar so I can DM you

Himanshu Kumar

85,657 次观看 • 2 个月前

Everyone else is making money with AI — are you still just using it to get things done faster? In the first episode of our three-part series(1/3), we walk through EdgeOne Makers and how AI Agents are evolving from productivity tools into real products that generate revenue. 💡 What you'll see: • The next wave of AI — products, not just productivity • Two paths to monetization: existing business + Agent, or idea → MVP • One-click deployment, hosting, and global delivery with EdgeOne Makers Check the comments for event perks — join now and get up to 50M Tokens!

Everyone else is making money with AI — are you still just using it to get things done faster? In the first episode of our three-part series(1/3), we walk through EdgeOne Makers and how AI Agents are evolving from productivity tools into real products that generate revenue. 💡 What you'll see: • The next wave of AI — products, not just productivity • Two paths to monetization: existing business + Agent, or idea → MVP • One-click deployment, hosting, and global delivery with EdgeOne Makers Check the comments for event perks — join now and get up to 50M Tokens!

Tencent EdgeOne

1,641,482 次观看 • 1 个月前

Andrew Ng just released a 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents that loop, rewrite themselves, and run without you: 09:14 - Build your first AI agent 33:11 - Run agents with loop engineering 1:02:46 - Turn agent loops into graphs 1:30:15 - Build agents that rewrite themselves 1:49:05 - Run the full graph system without you Most people are still building one agent and calling it done. Andrew Ng is already teaching everything after: Prompt → Agents → Loops → Graphs → Self-Improving Systems Single agents are the old workflow. Systems that improve and run without you are the new one. This 2-hour watch is worth more than most $500 agent engineering courses. Bookmark and watch it before everyone catches up. Then read how to run 1,000 agents from one prompt below ↓

Andrew Ng just released a 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents that loop, rewrite themselves, and run without you: 09:14 - Build your first AI agent 33:11 - Run agents with loop engineering 1:02:46 - Turn agent loops into graphs 1:30:15 - Build agents that rewrite themselves 1:49:05 - Run the full graph system without you Most people are still building one agent and calling it done. Andrew Ng is already teaching everything after: Prompt → Agents → Loops → Graphs → Self-Improving Systems Single agents are the old workflow. Systems that improve and run without you are the new one. This 2-hour watch is worth more than most $500 agent engineering courses. Bookmark and watch it before everyone catches up. Then read how to run 1,000 agents from one prompt below ↓

Lunar

224,517 次观看 • 17 天前

At Notion, we believe every business deserves powerful & beautiful tools. AI is the most important technology of this era. It shouldn't only belong to companies that have AI teams or can afford forward deployed engineers. Today we're launching Custom Agents: — The first multiplayer agents built for business. — No coding. Minutes to set up. Hosted in the cloud. — Run autonomously 24/7 with all your business apps. — Switch between the best LLMs (usually the same day they're released). — One person builds it, the whole company benefits. Rolling out for Business and Enterprise customers today. The AI era should leave no one behind 👌

At Notion, we believe every business deserves powerful & beautiful tools. AI is the most important technology of this era. It shouldn't only belong to companies that have AI teams or can afford forward deployed engineers. Today we're launching Custom Agents: — The first multiplayer agents built for business. — No coding. Minutes to set up. Hosted in the cloud. — Run autonomously 24/7 with all your business apps. — Switch between the best LLMs (usually the same day they're released). — One person builds it, the whole company benefits. Rolling out for Business and Enterprise customers today. The AI era should leave no one behind 👌

Ivan Zhao

148,301 次观看 • 6 个月前

There's a free 120 billion parameter AI you can run on your own computer. Zero internet. Zero API costs. Zero monthly fees. It's called Nvidia Nemotron 3 Super. And it just changed what solopreneurs can do with AI agents. Here's the setup: → Download Ollama. Copy one command into your terminal. → Connect it to OpenClaw in under 10 minutes. → Your AI agent now runs 24/7 on WhatsApp, Discord, or Telegram. → It answers customers, runs tasks, and manages workflows while you sleep. → 256,000 token context window. It reads entire documents without forgetting. No subscriptions. No cloud. No one else touching your data. A full AI employee stack for $0. Save this. Set it up this weekend.

There's a free 120 billion parameter AI you can run on your own computer. Zero internet. Zero API costs. Zero monthly fees. It's called Nvidia Nemotron 3 Super. And it just changed what solopreneurs can do with AI agents. Here's the setup: → Download Ollama. Copy one command into your terminal. → Connect it to OpenClaw in under 10 minutes. → Your AI agent now runs 24/7 on WhatsApp, Discord, or Telegram. → It answers customers, runs tasks, and manages workflows while you sleep. → 256,000 token context window. It reads entire documents without forgetting. No subscriptions. No cloud. No one else touching your data. A full AI employee stack for $0. Save this. Set it up this weekend.

Julian Goldie SEO

29,325 次观看 • 5 个月前

🚀Introducing Flockx by Fetch.ai your No-Code Business & Personal Agents 👇 Starting today FlockX by enables businesses of all sizes to launch dedicated AI Agents—intelligent, autonomous representatives designed to drive measurable growth in revenue, customer retention, and operational efficiency. ✅Key Features: Zero-Code Agent Creation: Deploy your AI Agent in minutes using FlockX’s intuitive platform. No technical expertise required. Global Reach via Businesses gain instant access to a global audience, while users unlock seamless connections to enterprises worldwide—mutually empowering growth. Engage clients, resolve queries, and capture global opportunities as users interact seamlessly with your business through the platform. Proven Business Impact: Effortlessly automate critical workflows, from lead generation to loyalty management, with precision and scalability. Seamless community integration: Understand and engage your audience by connecting your AI Agent to Discord and Telegram Messenger, with tools like calendars, information dashboards, and embedded chat widgets streamlining communication. Built with the trusted uAgents framework: and hosted securely on these Agents integrate directly into your existing systems while adapting to evolving demands. 🔗Next Steps: Create your AI Agent: Claim pre-registered access: Over 1 million businesses have already been onboarded—verify if your Agent is ready for activation. The AI-driven economy demands agility. Equip your business with the tools to compete—and lead. Learn how to deploy your Agent in one minute or less.

🚀Introducing Flockx by Fetch.ai your No-Code Business & Personal Agents 👇 Starting today FlockX by enables businesses of all sizes to launch dedicated AI Agents—intelligent, autonomous representatives designed to drive measurable growth in revenue, customer retention, and operational efficiency. ✅Key Features: Zero-Code Agent Creation: Deploy your AI Agent in minutes using FlockX’s intuitive platform. No technical expertise required. Global Reach via Businesses gain instant access to a global audience, while users unlock seamless connections to enterprises worldwide—mutually empowering growth. Engage clients, resolve queries, and capture global opportunities as users interact seamlessly with your business through the platform. Proven Business Impact: Effortlessly automate critical workflows, from lead generation to loyalty management, with precision and scalability. Seamless community integration: Understand and engage your audience by connecting your AI Agent to Discord and Telegram Messenger, with tools like calendars, information dashboards, and embedded chat widgets streamlining communication. Built with the trusted uAgents framework: and hosted securely on these Agents integrate directly into your existing systems while adapting to evolving demands. 🔗Next Steps: Create your AI Agent: Claim pre-registered access: Over 1 million businesses have already been onboarded—verify if your Agent is ready for activation. The AI-driven economy demands agility. Equip your business with the tools to compete—and lead. Learn how to deploy your Agent in one minute or less.

Fetch.ai

38,300 次观看 • 1 年前

I'm giving away Claude Code for FREE. Yes, you read that right -- the world's best AI, now completely FREE. My mission is to get the next billion people to write great software. I believe EVERYONE should have access to the best AI, but so many are constrained by costs. I'm solving this by: disrupting the world's fastest growing industry = AI + with the most proven business model = Ads You can actually try it out now -- just one line of code, and you unlock all the powers of Claude Code, for free. how it works: 1. sign up on Giga AI Free 2. change Claude Code env variables to use our inference endpoint 2. to support the free usage, we'll add ads inside the AI responses (only contextual and relevant ads, no spam) Since we get too many signups, there's a waitlist, but we'll be rolling it out to the maximum people as we can. Watch the video to get started & comment and retweet to get access first.

I'm giving away Claude Code for FREE. Yes, you read that right -- the world's best AI, now completely FREE. My mission is to get the next billion people to write great software. I believe EVERYONE should have access to the best AI, but so many are constrained by costs. I'm solving this by: disrupting the world's fastest growing industry = AI + with the most proven business model = Ads You can actually try it out now -- just one line of code, and you unlock all the powers of Claude Code, for free. how it works: 1. sign up on Giga AI Free 2. change Claude Code env variables to use our inference endpoint 2. to support the free usage, we'll add ads inside the AI responses (only contextual and relevant ads, no spam) Since we get too many signups, there's a waitlist, but we'll be rolling it out to the maximum people as we can. Watch the video to get started & comment and retweet to get access first.

Namanyay

488,019 次观看 • 10 个月前