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🚀 LangSmith for Startups Spotlight: Cogent Security Cogent is building AI agents that protect the world's largest organizations from cyberattacks. One of the hardest problems in cybersecurity is going from finding a vulnerability to actually fixing it. Cogent is automating that entire process from end-to-end. Cogent is already working...

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LangChain

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18,513 次观看 • 5 个月前 •via X (Twitter)

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We asked, you answered — our State of AI Agents Report is here! 🤖✨ We surveyed 1300+ industry professionals, from developers to business leaders, on how they're using AI agents today — and the results are in. What are the top use cases for agents? The biggest challenges when building agents? And who's finding success after deploying their agents to production? Read the full report ➡️ Here's 5 key insights in the thread below 🧵👇
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We asked, you answered — our State of AI Agents Report is here! 🤖✨ We surveyed 1300+ industry professionals, from developers to business leaders, on how they're using AI agents today — and the results are in. What are the top use cases for agents? The biggest challenges when building agents? And who's finding success after deploying their agents to production? Read the full report ➡️ Here's 5 key insights in the thread below 🧵👇

LangChain

103,586 次观看 • 1 年前

Karpathy's Agentic Engineering finally has proper tooling! (built by Google) Karpathy defined agentic engineering as the discipline that separates production agent work from vibe coding. The core skills he listed were spec design, eval loops, and security oversight. The problem has been that practicing this still requires a different tool for every phase: - editor for code - a terminal for scaffolding - a browser for testing - a cloud console for deployment - and a separate framework for evals. Every transition is a context switch. The solution to production-grade Agentic Engineering is now actually implemented in Google’s Agents CLI. It covers the entire workflow in one place for scaffolding, evaluating, and deploying ADK agents. One setup command injects 7 ADK-specific skills into a coding agent's context, which lets it handle scaffolding, evals, deployment, and enterprise registration through natural language. I tested this end-to-end by building a RAG agent from scratch using Claude Code. It scaffolded the full project from the ADK agentic_rag template, generated 20 eval scenarios with LLM-as-judge scoring, and returned a quantitative scorecard. Finally, it also deployed everything to Agent Runtime and registered the agent to Gemini Enterprise, so the entire org can discover and use it. The video below shows this in action, and I worked with the Google Cloud team to put this together. Agents CLI GitHub repo → (don't forget to star it ⭐ ) I wrote up the full build covering all six steps from install to enterprise registration. It includes the eval scorecard, the instruction loophole the eval caught before deployment, and what the deployment process actually looks like end-to-end. Read it below.
0:15

Karpathy's Agentic Engineering finally has proper tooling! (built by Google) Karpathy defined agentic engineering as the discipline that separates production agent work from vibe coding. The core skills he listed were spec design, eval loops, and security oversight. The problem has been that practicing this still requires a different tool for every phase: - editor for code - a terminal for scaffolding - a browser for testing - a cloud console for deployment - and a separate framework for evals. Every transition is a context switch. The solution to production-grade Agentic Engineering is now actually implemented in Google’s Agents CLI. It covers the entire workflow in one place for scaffolding, evaluating, and deploying ADK agents. One setup command injects 7 ADK-specific skills into a coding agent's context, which lets it handle scaffolding, evals, deployment, and enterprise registration through natural language. I tested this end-to-end by building a RAG agent from scratch using Claude Code. It scaffolded the full project from the ADK agentic_rag template, generated 20 eval scenarios with LLM-as-judge scoring, and returned a quantitative scorecard. Finally, it also deployed everything to Agent Runtime and registered the agent to Gemini Enterprise, so the entire org can discover and use it. The video below shows this in action, and I worked with the Google Cloud team to put this together. Agents CLI GitHub repo → (don't forget to star it ⭐ ) I wrote up the full build covering all six steps from install to enterprise registration. It includes the eval scorecard, the instruction loophole the eval caught before deployment, and what the deployment process actually looks like end-to-end. Read it below.

Akshay 🚀

258,436 次观看 • 2 个月前

Agentic traces contain perfect information about an agent’s behavior with every plan, action, and retry. But that information gets lost in a sea of JSON. So we built AgentPrism: open source React components that turn traces into visual diagrams for debugging AI agents. You can plug in your OpenTelemetry data and see your agent’s process unfold: messages, tool calls, retries. Quotient AI automatically monitors, analyzes, and improves AI agents. Being able to review traces quickly is paramount for their research, and for their customers. “Dealing with agent traces was one of the biggest frustrations for our researchers and a huge time sink. All of that has gone away since adding AgentPrism, and we’re excited to bring that functionality to our users.” — Julia Neagu
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Agentic traces contain perfect information about an agent’s behavior with every plan, action, and retry. But that information gets lost in a sea of JSON. So we built AgentPrism: open source React components that turn traces into visual diagrams for debugging AI agents. You can plug in your OpenTelemetry data and see your agent’s process unfold: messages, tool calls, retries. Quotient AI automatically monitors, analyzes, and improves AI agents. Being able to review traces quickly is paramount for their research, and for their customers. “Dealing with agent traces was one of the biggest frustrations for our researchers and a huge time sink. All of that has gone away since adding AgentPrism, and we’re excited to bring that functionality to our users.” — Julia Neagu

Evil Martians

101,372 次观看 • 10 个月前

Today marks General Availability of AgentCore, a set of infrastructure building blocks for developers and companies to build secure, scalable agents. When we first started AWS, the vast majority of developers were spending most of their time on the undifferentiated heavy lifting of infrastructure instead of what differentiated their feature. So, we solved that problem by building primitive building blocks like compute and storage and database that would allow teammates and customers to quickly build and deploy new experiences without having to reinvent the wheel each time. We realized the same thing was happening with AI agents. It's too difficult and it's slowing customers down. That's why we created AgentCore, a set of services to build, deploy, and operate highly capable agents using any framework or model, with enterprise-grade security and scalability. These building blocks (like serverless secure runtime, memory, observability, a gateway that does MCP translation, etc) help customers tackle some of the biggest challenges of going from prototype to production, much more quickly, securely, and scalably. AgentCore has been in preview for several weeks, and customers have been quite excited about it. The AgentCore SDK has already been downloaded over a million times and we're seeing transformative results, such as Cohere Health expecting to reduce medical review times by 30-40% in highly regulated healthcare, and teams at Cox Automotive and Experian are embracing its flexibility to deploy and operate agents at scale. Inside Amazon, our Amazon Devices Operations & Supply Chain team is using AgentCore to develop an agentic manufacturing approach where AI agents work together to automate manual processes – turning what used to be days of engineering time into processes that take under an hour with high precision. Just like AWS changed how companies build and scale applications, we believe AgentCore will do the same for AI agents, enabling the next generation of innovation.
0:15

Today marks General Availability of AgentCore, a set of infrastructure building blocks for developers and companies to build secure, scalable agents. When we first started AWS, the vast majority of developers were spending most of their time on the undifferentiated heavy lifting of infrastructure instead of what differentiated their feature. So, we solved that problem by building primitive building blocks like compute and storage and database that would allow teammates and customers to quickly build and deploy new experiences without having to reinvent the wheel each time. We realized the same thing was happening with AI agents. It's too difficult and it's slowing customers down. That's why we created AgentCore, a set of services to build, deploy, and operate highly capable agents using any framework or model, with enterprise-grade security and scalability. These building blocks (like serverless secure runtime, memory, observability, a gateway that does MCP translation, etc) help customers tackle some of the biggest challenges of going from prototype to production, much more quickly, securely, and scalably. AgentCore has been in preview for several weeks, and customers have been quite excited about it. The AgentCore SDK has already been downloaded over a million times and we're seeing transformative results, such as Cohere Health expecting to reduce medical review times by 30-40% in highly regulated healthcare, and teams at Cox Automotive and Experian are embracing its flexibility to deploy and operate agents at scale. Inside Amazon, our Amazon Devices Operations & Supply Chain team is using AgentCore to develop an agentic manufacturing approach where AI agents work together to automate manual processes – turning what used to be days of engineering time into processes that take under an hour with high precision. Just like AWS changed how companies build and scale applications, we believe AgentCore will do the same for AI agents, enabling the next generation of innovation.

Andy Jassy

24,990 次观看 • 10 个月前

I'm proud to share that Glean has surpassed $300M ARR, just five months after crossing $200M and growing ~3x over the past 15 months. This is an exciting milestone for Glean, and it's a signal about where the enterprise AI market is heading. We’ve long believed the real challenge in enterprise AI is not access to models. It is grounding AI in how a company actually works: its people, knowledge, workflows, permissions, and systems. That’s even clearer now. The companies creating real value with AI are not just adopting better models. They are building systems that understand their business well enough to deliver reliable outcomes at scale. That is the real moat, and it is what we’ve been building at Glean: an unrivaled context layer for enterprise AI. That context has to work across the business, not just inside a single team or use case. We see that in how customers adopt Glean: more than 85% use it across five or more job functions. It also has to meet the security and governance demands of complex enterprises. We see that in who is choosing Glean: our Fortune 500 customer count nearly doubled year over year. And it has to make economic sense as usage grows. In our recent benchmark with Claude Cowork, Glean was preferred roughly 2.5x as often as off-the-shelf MCP tools and used 30% fewer tokens on average. Better context improves both quality and efficiency. I enjoyed talking with CNBC's Deirdre Bosa about this broader shift. In enterprise AI, the winners will not be defined by better models alone. They will be defined by who builds the strongest foundation for enterprise context. Thank you to our customers, partners, and team for helping us build the future of enterprise AI.
0:15

I'm proud to share that Glean has surpassed $300M ARR, just five months after crossing $200M and growing ~3x over the past 15 months. This is an exciting milestone for Glean, and it's a signal about where the enterprise AI market is heading. We’ve long believed the real challenge in enterprise AI is not access to models. It is grounding AI in how a company actually works: its people, knowledge, workflows, permissions, and systems. That’s even clearer now. The companies creating real value with AI are not just adopting better models. They are building systems that understand their business well enough to deliver reliable outcomes at scale. That is the real moat, and it is what we’ve been building at Glean: an unrivaled context layer for enterprise AI. That context has to work across the business, not just inside a single team or use case. We see that in how customers adopt Glean: more than 85% use it across five or more job functions. It also has to meet the security and governance demands of complex enterprises. We see that in who is choosing Glean: our Fortune 500 customer count nearly doubled year over year. And it has to make economic sense as usage grows. In our recent benchmark with Claude Cowork, Glean was preferred roughly 2.5x as often as off-the-shelf MCP tools and used 30% fewer tokens on average. Better context improves both quality and efficiency. I enjoyed talking with CNBC's Deirdre Bosa about this broader shift. In enterprise AI, the winners will not be defined by better models alone. They will be defined by who builds the strongest foundation for enterprise context. Thank you to our customers, partners, and team for helping us build the future of enterprise AI.

Arvind Jain

281,201 次观看 • 3 个月前

$zkHive X $DONGO 🤝 We are excited to announce our partnership with Dongo AI ! Dongo AI is a platform designed to simplify and connect the expansive world of cryptocurrency for everyday users. Using their product users can research their preferred tokens and pose questions about the project, leveraging our AI's technology. We’re happy to announce that #zkHive is going to be one of the first projects to be integrated into Dongo’s upcoming platform launch. In addition #HiveBot will be integrated into Dongo’s community, and our security APIs will be used to secure the thousands of users of the Congo ecosystem! Thanks to the AI platform that DONGO is building, $ZKHIVE is going to protect thousands of new users! This is another great step by both parties to promote AI and security in the space!
0:14

$zkHive X $DONGO 🤝 We are excited to announce our partnership with Dongo AI ! Dongo AI is a platform designed to simplify and connect the expansive world of cryptocurrency for everyday users. Using their product users can research their preferred tokens and pose questions about the project, leveraging our AI's technology. We’re happy to announce that #zkHive is going to be one of the first projects to be integrated into Dongo’s upcoming platform launch. In addition #HiveBot will be integrated into Dongo’s community, and our security APIs will be used to secure the thousands of users of the Congo ecosystem! Thanks to the AI platform that DONGO is building, $ZKHIVE is going to protect thousands of new users! This is another great step by both parties to promote AI and security in the space!

zkHive

28,714 次观看 • 2 年前

$ZKHIVE X $NMT 🤝 We are excited to announce our major partnership with one of the leading AI projects in the space - NetMind.AI ! $NMT is an award winning AI powerhouse that has quickly become one of the most recognized decentralized AI platforms in the space, thanks to their wide range of offerings, from cost effective compute farms to elite AI consultancy services and AI chatbots. As part of our long term partnership, $ZKHIVE and NMT are going to build security AI models together 🤖🐝 #zkHive will also receive an access to $NMT’s compute farm as well as AI consultancy from $NMT’s team of experts, and $NMT will get access to all of #zkHive’s products and APIs! This partnership will improve zkHive’s AI capabilities and introduce thousands of new users to $ZKHIVE ecosystem!
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$ZKHIVE X $NMT 🤝 We are excited to announce our major partnership with one of the leading AI projects in the space - NetMind.AI ! $NMT is an award winning AI powerhouse that has quickly become one of the most recognized decentralized AI platforms in the space, thanks to their wide range of offerings, from cost effective compute farms to elite AI consultancy services and AI chatbots. As part of our long term partnership, $ZKHIVE and NMT are going to build security AI models together 🤖🐝 #zkHive will also receive an access to $NMT’s compute farm as well as AI consultancy from $NMT’s team of experts, and $NMT will get access to all of #zkHive’s products and APIs! This partnership will improve zkHive’s AI capabilities and introduce thousands of new users to $ZKHIVE ecosystem!

zkHive

44,354 次观看 • 2 年前

✨ Klarna's AI Assistant, powered by LangGraph and LangSmith, handles customer support tasks for 85 million active users — reducing customer resolution time by 80% ✨ 🛍️ Klarna’s flagship AI Assistant is revolutionizing the shopping and payments experience. Built on LangGraph and powered by LangSmith, the AI Assistant handles tasks ranging from customer payments, to refunds, to other payment escalations. ‼️ In the past 9 months, they’ve reduced average customer query resolution time by 80%, enabling faster responses to user queries and saving analysts and engineers hours a week of investigation time. 🔄 They’ve also automated ~70% of repetitive support tasks, freeing up customer service agents to handle complex, high-value interactions
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✨ Klarna's AI Assistant, powered by LangGraph and LangSmith, handles customer support tasks for 85 million active users — reducing customer resolution time by 80% ✨ 🛍️ Klarna’s flagship AI Assistant is revolutionizing the shopping and payments experience. Built on LangGraph and powered by LangSmith, the AI Assistant handles tasks ranging from customer payments, to refunds, to other payment escalations. ‼️ In the past 9 months, they’ve reduced average customer query resolution time by 80%, enabling faster responses to user queries and saving analysts and engineers hours a week of investigation time. 🔄 They’ve also automated ~70% of repetitive support tasks, freeing up customer service agents to handle complex, high-value interactions

LangChain

10,852 次观看 • 1 年前

Today, we're announcing a $60M Series B led by Battery Ventures, bringing our total funding to $85M in just under a year. Also joining the round are founders and operators who’ve built generational companies of the last two decades – tobi lutke (CEO, Shopify), arash ferdowsi (Dropbox), Claire Hughes Johnson (Stripe), and more. The round came together in 6 days. Here's why. Every major category in enterprise software is seeing multiple AI-native challengers. CRM, ERP, ITSM – all being rebuilt from scratch by a new generation of companies applying AI to solve persistent problems we couldn’t before. Employee Management (also known as HCM) is the exception. It’s the last frontier, and we believe the most important one. The operating layer to manage people, run payroll, benefits, compliance, and IT, for every company in the world, is still built on architecture that predates AI by decades. This fundraise is the story of how Warp is changing that. The average Warp customer is growing 5x faster than their peers, with 1/10th of the HR and admin overhead. We’re seeing a massive shift happening in how the best companies run their people operations. From the fastest-growing AI-startups to massive public companies, the winning teams are running lean: HR, finance, and ops generalists who automate as much as possible, and use their time instead for strategic work that AI can’t automate. Warp is the platform of choice for ambitious companies operating at this new pace. Legacy HCMs help humans track the work. Warp uses AI to proactively complete the work. Workday was built for the last era. We're building for the next one. And it’s working. We've – - Doubled ARR in Q1 - On track to $2B+ payroll volume this year - Signed enterprise customers with thousands of employees - Launched entire product lines back-to-back: Warp benefits brokerage and Warp Fabric (our AI-native IT automation suite built in-house). A few thank-yous: 1. Our customers, the fastest-growing companies in the world, who trust us with their most critical systems. We wouldn't be here without you. 2. Our team - 50+ people in NYC who've built this platform, taken on the hardest problems in business-critical software. We're just getting started. 3. Our investors doubling down in this round, and some of our earliest believers – Sound Ventures (ashton kutcher, Effie Epstein), Derek Grant, (Arnav Sahu), Harj Taggar at Y Combinator, Balaji, Kevin Hartz, Kyle Vogt, Amjad Masad, HOF Capital (Fady Yacoub), colinevans (OpenAI) We're here to arm ambitious American companies with Workday-grade power, but with the usability and delight of an Apple product. With this new funding, we plan to fund deeper AI agents, tax and compliance infrastructure, expand our product suite, and support even closely our fast-growing customers. Come join us.
0:11

Today, we're announcing a $60M Series B led by Battery Ventures, bringing our total funding to $85M in just under a year. Also joining the round are founders and operators who’ve built generational companies of the last two decades – tobi lutke (CEO, Shopify), arash ferdowsi (Dropbox), Claire Hughes Johnson (Stripe), and more. The round came together in 6 days. Here's why. Every major category in enterprise software is seeing multiple AI-native challengers. CRM, ERP, ITSM – all being rebuilt from scratch by a new generation of companies applying AI to solve persistent problems we couldn’t before. Employee Management (also known as HCM) is the exception. It’s the last frontier, and we believe the most important one. The operating layer to manage people, run payroll, benefits, compliance, and IT, for every company in the world, is still built on architecture that predates AI by decades. This fundraise is the story of how Warp is changing that. The average Warp customer is growing 5x faster than their peers, with 1/10th of the HR and admin overhead. We’re seeing a massive shift happening in how the best companies run their people operations. From the fastest-growing AI-startups to massive public companies, the winning teams are running lean: HR, finance, and ops generalists who automate as much as possible, and use their time instead for strategic work that AI can’t automate. Warp is the platform of choice for ambitious companies operating at this new pace. Legacy HCMs help humans track the work. Warp uses AI to proactively complete the work. Workday was built for the last era. We're building for the next one. And it’s working. We've – - Doubled ARR in Q1 - On track to $2B+ payroll volume this year - Signed enterprise customers with thousands of employees - Launched entire product lines back-to-back: Warp benefits brokerage and Warp Fabric (our AI-native IT automation suite built in-house). A few thank-yous: 1. Our customers, the fastest-growing companies in the world, who trust us with their most critical systems. We wouldn't be here without you. 2. Our team - 50+ people in NYC who've built this platform, taken on the hardest problems in business-critical software. We're just getting started. 3. Our investors doubling down in this round, and some of our earliest believers – Sound Ventures (ashton kutcher, Effie Epstein), Derek Grant, (Arnav Sahu), Harj Taggar at Y Combinator, Balaji, Kevin Hartz, Kyle Vogt, Amjad Masad, HOF Capital (Fady Yacoub), colinevans (OpenAI) We're here to arm ambitious American companies with Workday-grade power, but with the usability and delight of an Apple product. With this new funding, we plan to fund deeper AI agents, tax and compliance infrastructure, expand our product suite, and support even closely our fast-growing customers. Come join us.

Ayush S

1,129,432 次观看 • 2 个月前

LocalHost (localhost HQ) is working with Anthropic (Anthropic) to support founders building and deploying AI in production. Through this collaboration, LocalHost portfolio companies and a select group of high-signal community startups will receive Anthropic credits to build with Claude and experiment, iterate, and ship their applications. As more companies move from AI experimentation to production systems, access to reliable models and strong infrastructure matters. We’re excited to support founders who are designing products around AI from the start, rather than adding it on later.
0:14

LocalHost (localhost HQ) is working with Anthropic (Anthropic) to support founders building and deploying AI in production. Through this collaboration, LocalHost portfolio companies and a select group of high-signal community startups will receive Anthropic credits to build with Claude and experiment, iterate, and ship their applications. As more companies move from AI experimentation to production systems, access to reliable models and strong infrastructure matters. We’re excited to support founders who are designing products around AI from the start, rather than adding it on later.

Suhas Sumukh

18,897 次观看 • 7 个月前

ClickUp now employs over 100,000 AI AGENTS for our customers. This is from just THREE WEEKS of customers vibe coding full-blown teams of agents, THEMSELVES. BUT there's a problem. Since Super Agents are built agnostically, horizontally, and deeply capable with human-level abilities, you can literally build an agent for anything. We found that MOST of our customers have NO CLUE where to start. This is their very FIRST TIME EVER managing an agent. What I recommend is starting with a PROBLEM. Everybody can think of a problem they have. Just tell Super Agent Builder about your problems... about where you're WASTING time... about what you WISH you could do but you can't because of resource constraints. We've also found that human FEEDBACK and iteration are KEY. After agents are done with their jobs, give them feedback... Was it good? Was it bad? What do you want to see differently? They AUTOMATICALLY SELF-IMPROVE. Every time, they'll continuously get SMARTER. Personally, I find that agents go from AVERAGE intelligence to SUPER-human intelligence within about a month of working with them. Super Agents have truly democratized productivity, empowering literally anyone to build personalized, powerful agents in minutes. What problems do you wish you could solve? What do you not have enough time to get done? What would you like to do but don't have the resources for? What busy work do you wish you could get rid of?
0:16

ClickUp now employs over 100,000 AI AGENTS for our customers. This is from just THREE WEEKS of customers vibe coding full-blown teams of agents, THEMSELVES. BUT there's a problem. Since Super Agents are built agnostically, horizontally, and deeply capable with human-level abilities, you can literally build an agent for anything. We found that MOST of our customers have NO CLUE where to start. This is their very FIRST TIME EVER managing an agent. What I recommend is starting with a PROBLEM. Everybody can think of a problem they have. Just tell Super Agent Builder about your problems... about where you're WASTING time... about what you WISH you could do but you can't because of resource constraints. We've also found that human FEEDBACK and iteration are KEY. After agents are done with their jobs, give them feedback... Was it good? Was it bad? What do you want to see differently? They AUTOMATICALLY SELF-IMPROVE. Every time, they'll continuously get SMARTER. Personally, I find that agents go from AVERAGE intelligence to SUPER-human intelligence within about a month of working with them. Super Agents have truly democratized productivity, empowering literally anyone to build personalized, powerful agents in minutes. What problems do you wish you could solve? What do you not have enough time to get done? What would you like to do but don't have the resources for? What busy work do you wish you could get rid of?

Zeb Evans

18,324 次观看 • 7 个月前

🔐 Who We Are 🔐 At TRD Network, we’re building the foundation of secure AI infrastructure for the decentralized world. Our mission is simple: stop cyber threats before they start, with unmatched encryption, real-time monitoring, and decentralized protection. 🚀 What We Do 🚀 We combine military-grade encryption, AI-powered threat detection, and DePIN architecture to deliver enterprise-grade security across Web3. From crypto wallets to dApps, we guard your data and digital assets 24/7. 📍 How It Started 📍 Born from a vision to make Web3 truly secure, TRD was built by cybersecurity experts and blockchain engineers determined to end the rise of digital breaches. Today, we’re proud to protect protocols, platforms, and people across the globe. The future is decentralized, and it needs defense. That’s where we come in. Welcome to TRD Network! 💡
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🔐 Who We Are 🔐 At TRD Network, we’re building the foundation of secure AI infrastructure for the decentralized world. Our mission is simple: stop cyber threats before they start, with unmatched encryption, real-time monitoring, and decentralized protection. 🚀 What We Do 🚀 We combine military-grade encryption, AI-powered threat detection, and DePIN architecture to deliver enterprise-grade security across Web3. From crypto wallets to dApps, we guard your data and digital assets 24/7. 📍 How It Started 📍 Born from a vision to make Web3 truly secure, TRD was built by cybersecurity experts and blockchain engineers determined to end the rise of digital breaches. Today, we’re proud to protect protocols, platforms, and people across the globe. The future is decentralized, and it needs defense. That’s where we come in. Welcome to TRD Network! 💡

T.R.D Network

133,527 次观看 • 1 年前

I’m incredibly proud to share that OpenAI chose Brex to power their global spend and financial operations. When you're building at the frontier of AI and scaling global teams and infrastructure at an unprecedented pace like OpenAI is, Finance can't be the thing that slows you down. You need spend visibility the moment it happens, controls that enforce themselves, and agentic workflows that eliminate the manual work so your team stays focused on driving the business forward. We were so impressed by OpenAI’s rigor in evaluating every solution in the market, and whether they align to the agentic future OpenAI is building. Their decision to run on Brex is a huge testament to our AI roadmap and vision for the future of Finance. We started Brex around a simple idea: companies shouldn't have to choose between speed and control. There's no company in the world where that tradeoff matters more than OpenAI. We are honored to support them as they build the future. The best AI companies in the world, including OpenAI, Anthropic, Cursor, Vercel, Granola, Sierra, and Mercor choose Brex over every alternative for that exact reason. If you want to understand who’s truly building the future of AI in Finance, follow the customers you admire the most – not the hype.
0:10

I’m incredibly proud to share that OpenAI chose Brex to power their global spend and financial operations. When you're building at the frontier of AI and scaling global teams and infrastructure at an unprecedented pace like OpenAI is, Finance can't be the thing that slows you down. You need spend visibility the moment it happens, controls that enforce themselves, and agentic workflows that eliminate the manual work so your team stays focused on driving the business forward. We were so impressed by OpenAI’s rigor in evaluating every solution in the market, and whether they align to the agentic future OpenAI is building. Their decision to run on Brex is a huge testament to our AI roadmap and vision for the future of Finance. We started Brex around a simple idea: companies shouldn't have to choose between speed and control. There's no company in the world where that tradeoff matters more than OpenAI. We are honored to support them as they build the future. The best AI companies in the world, including OpenAI, Anthropic, Cursor, Vercel, Granola, Sierra, and Mercor choose Brex over every alternative for that exact reason. If you want to understand who’s truly building the future of AI in Finance, follow the customers you admire the most – not the hype.

Pedro Franceschi

62,546 次观看 • 5 个月前

Our @Grammarly AI agents are here! Today, we’re launching eight new AI agents designed for students and professionals. We created many of these agents with students in mind because they’re the first generation entering a job market where employers expect both subject expertise AND AI fluency. These agents help with everything from finding credible sources to predicting reader reactions. One agent we’ve gotten great feedback on is AI Grader (I wish I had this in school), which you can see in the video below. It looks at your assignment rubric and gives you suggestions like your professor would, and a grade prediction before you submit your work. And these agents are available in docs, our new AI-native writing surface! I’m deeply proud of this launch—docs is powered by Coda (Superhuman Docs) technology and is a great integration moment between Grammarly and Coda. This is just the beginning of Grammarly’s journey to offering agents that work everywhere people work and collaborate. I’ve been loving using these agents, and I’m excited for our customers to get access. Try them for yourself here and let me know what you think:
0:17

Our @Grammarly AI agents are here! Today, we’re launching eight new AI agents designed for students and professionals. We created many of these agents with students in mind because they’re the first generation entering a job market where employers expect both subject expertise AND AI fluency. These agents help with everything from finding credible sources to predicting reader reactions. One agent we’ve gotten great feedback on is AI Grader (I wish I had this in school), which you can see in the video below. It looks at your assignment rubric and gives you suggestions like your professor would, and a grade prediction before you submit your work. And these agents are available in docs, our new AI-native writing surface! I’m deeply proud of this launch—docs is powered by Coda (Superhuman Docs) technology and is a great integration moment between Grammarly and Coda. This is just the beginning of Grammarly’s journey to offering agents that work everywhere people work and collaborate. I’ve been loving using these agents, and I’m excited for our customers to get access. Try them for yourself here and let me know what you think:

Shishir

13,564 次观看 • 1 年前

A Blue Chip For Every Asset Class One of the key aspects that will set PinLink apart when our RWA-tokenized DePIN marketplace goes live is that, straight from launch, users will be able to buy fractional shares of assets from almost every key DePIN and AI asset category. Central to our strategy is to secure at least one blue chip integration for each asset category in time for to live. We’ve already announced integrations of: for GPUs Fetch.ai for AI agents Alephium for miners Quilibrium for nodes We’ll be aggressively pursuing integrations or similar prestige for categories including AI models, hotspot devices, IOT devices and tokenized data sets for AI training. Prepare for the most comprehensive offering the DePIN and decentralized AI sector is yet to see.
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A Blue Chip For Every Asset Class One of the key aspects that will set PinLink apart when our RWA-tokenized DePIN marketplace goes live is that, straight from launch, users will be able to buy fractional shares of assets from almost every key DePIN and AI asset category. Central to our strategy is to secure at least one blue chip integration for each asset category in time for to live. We’ve already announced integrations of: for GPUs Fetch.ai for AI agents Alephium for miners Quilibrium for nodes We’ll be aggressively pursuing integrations or similar prestige for categories including AI models, hotspot devices, IOT devices and tokenized data sets for AI training. Prepare for the most comprehensive offering the DePIN and decentralized AI sector is yet to see.

PinLink

39,015 次观看 • 1 年前

Excited to launch a new way to upskill with AI agents. This is how we are making it possible for anyone to learn to build with coding agents. To start, we are launching 4 new hands-on labs on the following topics: - Agent Skills - Agentic Image Generation - 30 Days of Hermes Agents - Prompt Engineering with Agents I am confident that with our new DAIR.AI platform, anyone can learn to become a top AI builder by building and acquiring highly-demanded AI skills. And there is a lot more landing in the coming weeks.
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Excited to launch a new way to upskill with AI agents. This is how we are making it possible for anyone to learn to build with coding agents. To start, we are launching 4 new hands-on labs on the following topics: - Agent Skills - Agentic Image Generation - 30 Days of Hermes Agents - Prompt Engineering with Agents I am confident that with our new DAIR.AI platform, anyone can learn to become a top AI builder by building and acquiring highly-demanded AI skills. And there is a lot more landing in the coming weeks.

elvis

19,058 次观看 • 3 个月前

We’re excited to announce that Kled has received a $1 million LOI from Superpower to help build the future of healthcare AI. Superpower Health, a $300M healthcare leader, has tasked Kled with unlocking one of the most valuable datasets in the world: how the world’s best doctors deliver care to their patients. Kled is building new healthcare integrations inside our app. Patients will be able to securely connect their healthcare portals and share anonymized chat history from conversations with their doctors. In return, they get paid. That data is then licensed to companies like Superpower Health to power next-generation healthcare AI, always with user consent and transparency. This supports Superpower’s mission to make the world’s best healthcare accessible to everyone. This is just the beginning. Healthcare is one of the most important uses of AI, and Kled is positioned to be at the center of it.
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We’re excited to announce that Kled has received a $1 million LOI from Superpower to help build the future of healthcare AI. Superpower Health, a $300M healthcare leader, has tasked Kled with unlocking one of the most valuable datasets in the world: how the world’s best doctors deliver care to their patients. Kled is building new healthcare integrations inside our app. Patients will be able to securely connect their healthcare portals and share anonymized chat history from conversations with their doctors. In return, they get paid. That data is then licensed to companies like Superpower Health to power next-generation healthcare AI, always with user consent and transparency. This supports Superpower’s mission to make the world’s best healthcare accessible to everyone. This is just the beginning. Healthcare is one of the most important uses of AI, and Kled is positioned to be at the center of it.

Kled AI

116,855 次观看 • 11 个月前

Now is the best time for founders and brands to take advantage of this AI bubble to actually stand out from their competitors. First thing that potential customer see is your product video/demo, and If I wanted to buy your product, and the presentation you show me looks crap, I will get an impression you cheaped out on the product as well and just pass. A lot of founders/brands sadly fall for that, especially now with AI hype promising fast and cheap content. Just be honest, if you are a potential customer - would you be converted by AI slop, or videos like ones below, that were fundamentally and manually structured and animated to a T for conversion ?
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Now is the best time for founders and brands to take advantage of this AI bubble to actually stand out from their competitors. First thing that potential customer see is your product video/demo, and If I wanted to buy your product, and the presentation you show me looks crap, I will get an impression you cheaped out on the product as well and just pass. A lot of founders/brands sadly fall for that, especially now with AI hype promising fast and cheap content. Just be honest, if you are a potential customer - would you be converted by AI slop, or videos like ones below, that were fundamentally and manually structured and animated to a T for conversion ?

Leon Fucak

61,980 次观看 • 6 个月前

Our marketing team is just me and ~40 AI agents. I finally got around to putting them into an "org chart", and it's actually really cool to see! Plus, laying them out this way by sub-function (social media, blog, email, community, partners, etc) has given me a bunch of ideas of other agents I want to build. If you're interested in the full version (and the templates/screenshots for each agent), let me know and I'll send it over to you.
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Our marketing team is just me and ~40 AI agents. I finally got around to putting them into an "org chart", and it's actually really cool to see! Plus, laying them out this way by sub-function (social media, blog, email, community, partners, etc) has given me a bunch of ideas of other agents I want to build. If you're interested in the full version (and the templates/screenshots for each agent), let me know and I'll send it over to you.

Jacob Bank

322,749 次观看 • 1 年前