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Agents changed software forever. For everyone. You won't need to "learn a tool" anymore. Instead, you'll tell tools what you want, and they will figure out how to do it. This is a huge shift. I'm currently working with Spoki, an AI agentic conversational platform. After looking at this,...

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12,095 просмотров • 1 месяц назад •via X (Twitter)

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Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)
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Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)

Rohan Paul

16,584 просмотров • 1 месяц назад

NEW: Introducing Octane AI Agentic Commerce Quizzes - Increase sales with AI. What is it? A sales quiz AI agent that makes 1-1 personalized sales experiences for every single customer. In real time. Powered by our new AI model CORE-1. Examples: 📸 Want to ask your customer to take a selfie and your AI agent automatically recommends them a full outfit from your catalog? Octane AI agents can do that. 🪞 Want to have an AI agent hand pick out each product for a personalized skin care routine? Want them to upload a selfie to detect their skin tone? Octane AI agents can do can that. 📊 Want to create an incredibly detailed report with graphs and tables and graphics thats generated by AI for each customer? Octane AI agents can do that. We give you the building blocks and you can build anything. And you can build it fast because our AI will do the heavy lifting for you. This is v1 and a representation of where our commerce and quiz technology is headed. Available today to everyone at 🆕 What we are launching today: • Smart Quiz Builder: Have an AI agent plan out and build your Octane AI quiz for you. It can even write custom HTML for beautiful results pages and progress bars. • Smart Products: It can take forever to setup the recommendation logic for a quiz. For those of you who need help, simply add smart products to your Octane AI quiz and your very own AI agent will hand-pick products for each customer who takes your quiz. It’s amazing. • Smart Copy: Instead of showing everyone who takes your quiz the exact same copy, use AI to personalize the quiz for every single person who takes it. Explain why these specific products are perfect for specifically them. • Image Analyzer: Let your customers upload or take a photo during the quiz and have AI analyze it. You can use this for anything from skin tone detection to picking out outfits! • Shopping Assistant: An AI agent that lives on your store that can help your customers at the right time. We have been building quiz software for almost 10 years now and AI is enabling us to make quizzes even more powerful. This is just the v1 of what we will be releasing in this area. We are so excited to see what you create with these new agentic products. Get creative, we think you will be surprised at how many interesting experiences you can create with Octane AI now.
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NEW: Introducing Octane AI Agentic Commerce Quizzes - Increase sales with AI. What is it? A sales quiz AI agent that makes 1-1 personalized sales experiences for every single customer. In real time. Powered by our new AI model CORE-1. Examples: 📸 Want to ask your customer to take a selfie and your AI agent automatically recommends them a full outfit from your catalog? Octane AI agents can do that. 🪞 Want to have an AI agent hand pick out each product for a personalized skin care routine? Want them to upload a selfie to detect their skin tone? Octane AI agents can do can that. 📊 Want to create an incredibly detailed report with graphs and tables and graphics thats generated by AI for each customer? Octane AI agents can do that. We give you the building blocks and you can build anything. And you can build it fast because our AI will do the heavy lifting for you. This is v1 and a representation of where our commerce and quiz technology is headed. Available today to everyone at 🆕 What we are launching today: • Smart Quiz Builder: Have an AI agent plan out and build your Octane AI quiz for you. It can even write custom HTML for beautiful results pages and progress bars. • Smart Products: It can take forever to setup the recommendation logic for a quiz. For those of you who need help, simply add smart products to your Octane AI quiz and your very own AI agent will hand-pick products for each customer who takes your quiz. It’s amazing. • Smart Copy: Instead of showing everyone who takes your quiz the exact same copy, use AI to personalize the quiz for every single person who takes it. Explain why these specific products are perfect for specifically them. • Image Analyzer: Let your customers upload or take a photo during the quiz and have AI analyze it. You can use this for anything from skin tone detection to picking out outfits! • Shopping Assistant: An AI agent that lives on your store that can help your customers at the right time. We have been building quiz software for almost 10 years now and AI is enabling us to make quizzes even more powerful. This is just the v1 of what we will be releasing in this area. We are so excited to see what you create with these new agentic products. Get creative, we think you will be surprised at how many interesting experiences you can create with Octane AI now.

Matt Schlicht

290,828 просмотров • 7 месяцев назад

Automation tools like Zapier & N8N are powerful, but let's be honest: they're overwhelming for a non-technical sales team that wants to close deals fast. You just want to connect your CRM to your contracts and proposals. You don't want to learn a complex tool or hire a freelancer to do it. We're building Docsyde to fix this. Tell our AI agent "Doc" what you want, in plain English. And watch it build the entire workflow in seconds 👇🏾
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Automation tools like Zapier & N8N are powerful, but let's be honest: they're overwhelming for a non-technical sales team that wants to close deals fast. You just want to connect your CRM to your contracts and proposals. You don't want to learn a complex tool or hire a freelancer to do it. We're building Docsyde to fix this. Tell our AI agent "Doc" what you want, in plain English. And watch it build the entire workflow in seconds 👇🏾

timi the chef 👨🏾‍🍳

19,482 просмотров • 8 месяцев назад

Launching AI Discovery And Communication DeepAgent discovers other AI agents and software tools on the fly and communicates with them to perform complex tasks. Here is how it works - - DeepAgent searches for other AI agents and tools - Finds the right tool for the job - Establishes contact using MCP and handles auth - Collaborates with the other tool to get the job done! - Remembers this tool for future colabs! Much like humans, it can create a team of AI agents or software tools to perform tasks. Here it is, learning about MindMaps, communicating with another server, and creating a Mindmap!!
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Launching AI Discovery And Communication DeepAgent discovers other AI agents and software tools on the fly and communicates with them to perform complex tasks. Here is how it works - - DeepAgent searches for other AI agents and tools - Finds the right tool for the job - Establishes contact using MCP and handles auth - Collaborates with the other tool to get the job done! - Remembers this tool for future colabs! Much like humans, it can create a team of AI agents or software tools to perform tasks. Here it is, learning about MindMaps, communicating with another server, and creating a Mindmap!!

Bindu Reddy

13,598 просмотров • 1 год назад

If you’ve never written code before, this is for you. I’ve just launched a course that shows you, in less than 30 minutes, how to describe an idea for an app and build it with AI. In this course, you'll build a working web application - a funny interactive birthday message generator that runs in your browser and can be shared with friends. You'll customize it by telling AI how you want it changed, and tweak it until it works the way you want. By the end, you'll have a repeatable process you can apply to build a wide variety of applications. If you want to try vibe coding, this will be the best place to start! Further, you'll be able to use these techniques with whatever tool you're most comfortable with (like ChatGPT, Gemini, Claude, or others) -- we're vendor neutral. Skills you'll gain: - How to build web apps with AI - zero coding skills needed - How to fix and improve your creations by chatting with AI - A simple process you can use to build other things you can dream up Building with AI is one of the most fun things in the world. Please join me and take your first step! I think you will be surprised at what you can build. And if you're an experienced engineer, please share this with someone in your life who's been curious about building with AI. Come build with me!
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If you’ve never written code before, this is for you. I’ve just launched a course that shows you, in less than 30 minutes, how to describe an idea for an app and build it with AI. In this course, you'll build a working web application - a funny interactive birthday message generator that runs in your browser and can be shared with friends. You'll customize it by telling AI how you want it changed, and tweak it until it works the way you want. By the end, you'll have a repeatable process you can apply to build a wide variety of applications. If you want to try vibe coding, this will be the best place to start! Further, you'll be able to use these techniques with whatever tool you're most comfortable with (like ChatGPT, Gemini, Claude, or others) -- we're vendor neutral. Skills you'll gain: - How to build web apps with AI - zero coding skills needed - How to fix and improve your creations by chatting with AI - A simple process you can use to build other things you can dream up Building with AI is one of the most fun things in the world. Please join me and take your first step! I think you will be surprised at what you can build. And if you're an experienced engineer, please share this with someone in your life who's been curious about building with AI. Come build with me!

Andrew Ng

635,434 просмотров • 6 месяцев назад

Google’s new Agent2Agent protocol is a key step toward a future of AI Agent interoperability. No single tool has all the data a user or business needs for most workflows, so we need Agents to be able to talk to each other. Salesforce will have AI Agents that understand the inner workings of CRM, Workday will have AI Agents that understand HR workflows, Box has AI Agents that understand content and documents, and so on. It’s easy to conceive of a world where we have tens of thousands of these tool Agents and then billions or trillions of customized Agents that are extensions of those. So openness becomes key. Workflows need data from multiple systems to complete the task — like a sales report that needs documents and CRM data or an HR task that needs HR policies and employee details — and that’s where A2A comes in. This protocol gives AI Agent providers a way of talking to each other and simplifying the way that Agents communicate, understand each other’s capabilities, and so on. It’s great to see more interoperability, along with MCP, emerging in the AI space right now, as this will define the future of most IT stacks.
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Google’s new Agent2Agent protocol is a key step toward a future of AI Agent interoperability. No single tool has all the data a user or business needs for most workflows, so we need Agents to be able to talk to each other. Salesforce will have AI Agents that understand the inner workings of CRM, Workday will have AI Agents that understand HR workflows, Box has AI Agents that understand content and documents, and so on. It’s easy to conceive of a world where we have tens of thousands of these tool Agents and then billions or trillions of customized Agents that are extensions of those. So openness becomes key. Workflows need data from multiple systems to complete the task — like a sales report that needs documents and CRM data or an HR task that needs HR policies and employee details — and that’s where A2A comes in. This protocol gives AI Agent providers a way of talking to each other and simplifying the way that Agents communicate, understand each other’s capabilities, and so on. It’s great to see more interoperability, along with MCP, emerging in the AI space right now, as this will define the future of most IT stacks.

Aaron Levie

139,591 просмотров • 1 год назад

Agentforce will empower Volkswagen Group to craft personalized customer journeys–powered by data, inspired by people. Learn how they plan to provide world-class service to more customers with connected data, intelligent tools, and AI-powered CRM:
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Agentforce will empower Volkswagen Group to craft personalized customer journeys–powered by data, inspired by people. Learn how they plan to provide world-class service to more customers with connected data, intelligent tools, and AI-powered CRM:

Salesforce

17,011 просмотров • 10 месяцев назад

everyone in the AI CRM race is building the wrong product. after onboarding 700+ customers one by one and min person, zoom and slack and saw some go, i learned the painfully obvious insight: The best CRM is no CRM at all. Not a better CRM. Not a faster CRM. A CRM you forget exists completely. That’s what we’re building. Octolane AI is world's first self-driving AI CRM. It finds your deals. Writes your follow-ups. Updates every field. While you sleep. You never log in. You never update a field. You never “use” it. The CRM disappears. The results don’t. We’re 5 people. Y Combinator W24. Shipping 7 days a week from whatever office will have us. To everyone on that list with your mega-rounds: respect. But we’re coming. 100 days. Building in public. Let the market decide
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everyone in the AI CRM race is building the wrong product. after onboarding 700+ customers one by one and min person, zoom and slack and saw some go, i learned the painfully obvious insight: The best CRM is no CRM at all. Not a better CRM. Not a faster CRM. A CRM you forget exists completely. That’s what we’re building. Octolane AI is world's first self-driving AI CRM. It finds your deals. Writes your follow-ups. Updates every field. While you sleep. You never log in. You never update a field. You never “use” it. The CRM disappears. The results don’t. We’re 5 people. Y Combinator W24. Shipping 7 days a week from whatever office will have us. To everyone on that list with your mega-rounds: respect. But we’re coming. 100 days. Building in public. Let the market decide

Coffee with One 🇺🇸

70,538 просмотров • 5 месяцев назад

Announcing my new course: Agentic AI! Building AI agents is one of the most in-demand skills in the job market. This course, available now at teaches you how. You'll learn to implement four key agentic design patterns: - Reflection, in which an agent examines its own output and figures out how to improve it - Tool use, in which an LLM-driven application decides which functions to call to carry out web search, access calendars, send email, write code, etc. - Planning, where you'll use an LLM to decide how to break down a task into sub-tasks for execution, and - Multi-agent collaboration, in which you build multiple specialized agents — much like how a company might hire multiple employees — to perform a complex task You'll also learn to take a complex application and systematically decompose it into a sequence of tasks to implement using these design patterns. But here's what I think is the most important part of this course: Having worked with many teams on AI agents, I've found that the single biggest predictor of whether someone executes well is their ability to drive a disciplined process for evals and error analysis. In this course, you'll learn how to do this, so you can efficiently home in on which components to improve in a complex agentic workflow. Instead of guessing what to work on, you'll let evals data guide you. This will put you significantly ahead of the game compared to the vast majority of teams building agents. Together, we'll build a deep research agent that searches, synthesizes, and reports, using all of these agentic design patterns and best practices. This self-paced course is taught in a vendor neutral way, using raw Python - without hiding details in a framework. You'll see how each step works, and learn the core concepts that you can then implement using any popular agentic AI framework, or using no framework. The only prerequisite is familiarity with Python, though knowing a bit about LLMs helps. Come join me, and let's build some agentic AI systems! Sign up to get started:
2:34

Announcing my new course: Agentic AI! Building AI agents is one of the most in-demand skills in the job market. This course, available now at teaches you how. You'll learn to implement four key agentic design patterns: - Reflection, in which an agent examines its own output and figures out how to improve it - Tool use, in which an LLM-driven application decides which functions to call to carry out web search, access calendars, send email, write code, etc. - Planning, where you'll use an LLM to decide how to break down a task into sub-tasks for execution, and - Multi-agent collaboration, in which you build multiple specialized agents — much like how a company might hire multiple employees — to perform a complex task You'll also learn to take a complex application and systematically decompose it into a sequence of tasks to implement using these design patterns. But here's what I think is the most important part of this course: Having worked with many teams on AI agents, I've found that the single biggest predictor of whether someone executes well is their ability to drive a disciplined process for evals and error analysis. In this course, you'll learn how to do this, so you can efficiently home in on which components to improve in a complex agentic workflow. Instead of guessing what to work on, you'll let evals data guide you. This will put you significantly ahead of the game compared to the vast majority of teams building agents. Together, we'll build a deep research agent that searches, synthesizes, and reports, using all of these agentic design patterns and best practices. This self-paced course is taught in a vendor neutral way, using raw Python - without hiding details in a framework. You'll see how each step works, and learn the core concepts that you can then implement using any popular agentic AI framework, or using no framework. The only prerequisite is familiarity with Python, though knowing a bit about LLMs helps. Come join me, and let's build some agentic AI systems! Sign up to get started:

Andrew Ng

885,642 просмотров • 9 месяцев назад

Proactive AI Agents Today’s AI products are reactive. You give the model a prompt, it responds with an answer. These are useful, but I’m excited about products that take this further and shift the paradigm from “ask → answer” to “observe → act." These agents will continuously monitor context in the background across all of your connected tools and data, predict what matters, and take action before being asked to do so – much like a human does. So instead of you prompting the model, the model will start prompting you. Examples here could include agents that remind you about tasks you forgot to complete, resolve customer issues before support tickets are filed, or debug and ship code fixes automatically. This shift represents a new paradigm where AI products behave more like humans and less like tools. We’re already starting to see this dynamic with products like OpenClaw, Poke, and more - and we’ve only scratched the surface of capabilities here. We’re accepting applications for the next cohort of a16z a16z speedrun 🧊 – If you’re building the next generation of AI products, apply online.
0:50

Proactive AI Agents Today’s AI products are reactive. You give the model a prompt, it responds with an answer. These are useful, but I’m excited about products that take this further and shift the paradigm from “ask → answer” to “observe → act." These agents will continuously monitor context in the background across all of your connected tools and data, predict what matters, and take action before being asked to do so – much like a human does. So instead of you prompting the model, the model will start prompting you. Examples here could include agents that remind you about tasks you forgot to complete, resolve customer issues before support tickets are filed, or debug and ship code fixes automatically. This shift represents a new paradigm where AI products behave more like humans and less like tools. We’re already starting to see this dynamic with products like OpenClaw, Poke, and more - and we’ve only scratched the surface of capabilities here. We’re accepting applications for the next cohort of a16z a16z speedrun 🧊 – If you’re building the next generation of AI products, apply online.

Kenan Saleh

76,564 просмотров • 1 месяц назад

🚨BIGGEST ANNOUNCEMENT OF MY LIFE: I've been working on something big these last few months It's called Creator Buddy, and it's the best AI content tool you'll ever use It's an AI content coach that will help you create WAY better content on X It's jam packed with awesome AI tools that will help you create content that attracts you a massive audience: • AI coach that reviews all your old content to let you know what's working • AI content repurposing tool that helps you take a tweet and turn it into videos, blogs, and other forms of content • Brain dumping tool that takes what's on your mind and turns it into content • A bookmarking tool that's like X bookmarks except actually useful This is the most important project of my life and I can't wait for you to try it out The biggest challenge I see for content creators on X is they struggle to find their voice. They struggle to figure out what their niche should be or what they should talk about Creator Buddy solves this It's not an AI tool that creates you content. It's an AI tool that helps you discover who you are and what makes you unique and interesting. I'm launching Creator Buddy in the next month or so and want you to test it out. Beta testing begins in the next week and the first wave of users will be my subscribers on X I'll also be choosing 10 random people who like/RT this post to beta test it early Second wave will be through my newsletter (link in bio) Third wave will be to my reply guys (make sure to reply early and often) Creator Buddy is going to be the single greatest AI content creation tool and I can't wait for you to use it!
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🚨BIGGEST ANNOUNCEMENT OF MY LIFE: I've been working on something big these last few months It's called Creator Buddy, and it's the best AI content tool you'll ever use It's an AI content coach that will help you create WAY better content on X It's jam packed with awesome AI tools that will help you create content that attracts you a massive audience: • AI coach that reviews all your old content to let you know what's working • AI content repurposing tool that helps you take a tweet and turn it into videos, blogs, and other forms of content • Brain dumping tool that takes what's on your mind and turns it into content • A bookmarking tool that's like X bookmarks except actually useful This is the most important project of my life and I can't wait for you to try it out The biggest challenge I see for content creators on X is they struggle to find their voice. They struggle to figure out what their niche should be or what they should talk about Creator Buddy solves this It's not an AI tool that creates you content. It's an AI tool that helps you discover who you are and what makes you unique and interesting. I'm launching Creator Buddy in the next month or so and want you to test it out. Beta testing begins in the next week and the first wave of users will be my subscribers on X I'll also be choosing 10 random people who like/RT this post to beta test it early Second wave will be through my newsletter (link in bio) Third wave will be to my reply guys (make sure to reply early and often) Creator Buddy is going to be the single greatest AI content creation tool and I can't wait for you to use it!

Alex Finn

337,313 просмотров • 1 год назад

Stop deflecting customer requests and start solving them with agentic AI. By bringing AI agents directly to your customers, we are introducing a concierge-style way of providing customer service. Learn more in the 2026 AI agent trends report →
1:00

Stop deflecting customer requests and start solving them with agentic AI. By bringing AI agents directly to your customers, we are introducing a concierge-style way of providing customer service. Learn more in the 2026 AI agent trends report →

Google Cloud

11,693 просмотров • 2 месяцев назад

I miss building simple, working software. At some point, we decided to complicate everything for no reason. Today, people can't build anything without using three frameworks, 17 libraries, and a swarm of microservices. And here is a funny paradox: To understand how these complex systems work, we've had to build systems and tools that generate data we can later analyze. But the more data we produce, the harder it is to process and make sense of it. We are in the middle of an observability crisis. The tools we have are inefficient, and we don't have enough people to keep systems running. A few weeks ago, I met the team Resolve AI, and they have built a fundamentally new approach to observability and incident management: Instead of depending on humans to run a system, Resolve built a Production Software Engineer who runs the system using AI while letting people supervise. And it's not only crazy, but I think this will fundamentally change how we monitor and maintain systems in production for years to come. I recorded a quick video to showcase a simple example of how Resolve works behind the scenes. There are two main things I'd like you to notice: 1. The tool can correlate data across logs, metrics, and traces coming from different systems. You don't have to do any work to get the information that matters right in front of you. 2. (This is the big one!) The tool can diagnose what's happening and give you instructions on how to solve it. It can produce causal relationships across the entire system stack. Resolve is backed by investors like Replit's founder Amjad Masad, Reid Hoffman, Jeff Dean, Fei Fei Li, Andy Price, among others. They are currently working with a select number of companies and want to onboard a few more. If you are interested in trying them out, go to this link: Honestly, this is one of the most impressive uses of AI I've seen.
5:18

I miss building simple, working software. At some point, we decided to complicate everything for no reason. Today, people can't build anything without using three frameworks, 17 libraries, and a swarm of microservices. And here is a funny paradox: To understand how these complex systems work, we've had to build systems and tools that generate data we can later analyze. But the more data we produce, the harder it is to process and make sense of it. We are in the middle of an observability crisis. The tools we have are inefficient, and we don't have enough people to keep systems running. A few weeks ago, I met the team Resolve AI, and they have built a fundamentally new approach to observability and incident management: Instead of depending on humans to run a system, Resolve built a Production Software Engineer who runs the system using AI while letting people supervise. And it's not only crazy, but I think this will fundamentally change how we monitor and maintain systems in production for years to come. I recorded a quick video to showcase a simple example of how Resolve works behind the scenes. There are two main things I'd like you to notice: 1. The tool can correlate data across logs, metrics, and traces coming from different systems. You don't have to do any work to get the information that matters right in front of you. 2. (This is the big one!) The tool can diagnose what's happening and give you instructions on how to solve it. It can produce causal relationships across the entire system stack. Resolve is backed by investors like Replit's founder Amjad Masad, Reid Hoffman, Jeff Dean, Fei Fei Li, Andy Price, among others. They are currently working with a select number of companies and want to onboard a few more. If you are interested in trying them out, go to this link: Honestly, this is one of the most impressive uses of AI I've seen.

Santiago

82,074 просмотров • 1 год назад

Linear CEO Karri Saarinen says some companies are using "friction forms" to help engineers break through bureaucracy and get new AI tools approved faster: "There are a lot of companies where employees ask, 'Can I use agents?' and they say, 'No, you can’t.' And they don’t really have a reason for it, or they say, 'We have to evaluate it,' and that evaluation takes months." "This has to change. The industry is moving so fast, so you cannot have month-long, multi-month processes to evaluate every single new tool. I think the security standpoint is valid, but you have to figure out a new way to think about security and not just block new tools." "One hack I’ve seen at some companies is that they have this friction form. So engineers who feel friction and want to use new tools or AI file a friction form, and that escalates it to higher leadership. Then it makes an SLA that has to be resolved in a week or 10 days." "And so you force the hand of procurement, IT, and security people to do something about it. Because the incentive a lot of times in these jobs is that you don’t want to rock the boat, so you don’t want to change things if you don’t have to."
1:35

Linear CEO Karri Saarinen says some companies are using "friction forms" to help engineers break through bureaucracy and get new AI tools approved faster: "There are a lot of companies where employees ask, 'Can I use agents?' and they say, 'No, you can’t.' And they don’t really have a reason for it, or they say, 'We have to evaluate it,' and that evaluation takes months." "This has to change. The industry is moving so fast, so you cannot have month-long, multi-month processes to evaluate every single new tool. I think the security standpoint is valid, but you have to figure out a new way to think about security and not just block new tools." "One hack I’ve seen at some companies is that they have this friction form. So engineers who feel friction and want to use new tools or AI file a friction form, and that escalates it to higher leadership. Then it makes an SLA that has to be resolved in a week or 10 days." "And so you force the hand of procurement, IT, and security people to do something about it. Because the incentive a lot of times in these jobs is that you don’t want to rock the boat, so you don’t want to change things if you don’t have to."

TBPN

15,799 просмотров • 3 месяцев назад

New short course: Serverless Agentic Workflows with Amazon Bedrock. Learn to build and deploy serverless agents in this course created with Amazon Web Services and taught by Mike G Chambers, a Senior Developer Advocate at AWS specializing in GenAI. (Disclosure: I serve on Amazon's board.) Generative AI applications are becoming more complex, sophisticated, and agentic. Agentic applications have workloads that can be hard to predict in advance -- for example, what tools will it decide to call? -- and a serverless architecture helps you efficiently providing on-demand resources. This course teaches you to build and deploy a serverless agentic application. You’ll learn to create agents with tools, code execution, and guardrails, and build responsible agents for business use cases: - Build a customer service bot for a fictional tea mug business that can answering questions, retrieve information, and process orders. - Connect your customer service agent to a CRM to get customer info and log support tickets in real-time. - Explore how you invoke the agent, and see the trace to review the agent’s thought process and observation loop until it reaches its final output. - Attach a code interpreter to your agent, giving it the ability to perform accurate calculations by writing and running its own Python code. - Implement guardrails to prevent your agent from revealing sensitive information or using inappropriate language. By the end, you will have built a sophisticated AI agent capable of handling real-world customer support scenarios. Please sign up here!
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New short course: Serverless Agentic Workflows with Amazon Bedrock. Learn to build and deploy serverless agents in this course created with Amazon Web Services and taught by Mike G Chambers, a Senior Developer Advocate at AWS specializing in GenAI. (Disclosure: I serve on Amazon's board.) Generative AI applications are becoming more complex, sophisticated, and agentic. Agentic applications have workloads that can be hard to predict in advance -- for example, what tools will it decide to call? -- and a serverless architecture helps you efficiently providing on-demand resources. This course teaches you to build and deploy a serverless agentic application. You’ll learn to create agents with tools, code execution, and guardrails, and build responsible agents for business use cases: - Build a customer service bot for a fictional tea mug business that can answering questions, retrieve information, and process orders. - Connect your customer service agent to a CRM to get customer info and log support tickets in real-time. - Explore how you invoke the agent, and see the trace to review the agent’s thought process and observation loop until it reaches its final output. - Attach a code interpreter to your agent, giving it the ability to perform accurate calculations by writing and running its own Python code. - Implement guardrails to prevent your agent from revealing sensitive information or using inappropriate language. By the end, you will have built a sophisticated AI agent capable of handling real-world customer support scenarios. Please sign up here!

Andrew Ng

81,048 просмотров • 1 год назад

I think we're entering a new era of AI creation. The best tools won't just generate content. They'll help you discover what to create. Dreamina Octo is one of the first tools that made me feel that shift. 🧵👇
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I think we're entering a new era of AI creation. The best tools won't just generate content. They'll help you discover what to create. Dreamina Octo is one of the first tools that made me feel that shift. 🧵👇

Md Riyazuddin

47,689 просмотров • 25 дней назад

New course to bring you up to state-of-the-art at using AI to help you code: Build Apps with Windsurf's AI Coding Agents, built in partnership with WIndsurf (Codeium) and taught by Anshul Ramachandran! AI-assisted IDEs (Integrated Development Environments) make developers’ workflows faster, more efficient, and much more fun. Agentic tools like Windsurf are more than just code autocomplete—they are collaborative coding agents that help you break down complex applications, iterate efficiently, and generate code that spans multiple files. Although a lot of coding assistants share the same underlying large language models for planning and reasoning, a major point of distinction is how they handle tools, keep track of context, and stay aligned with your intent as a developer. For instance, if you make modifications to a class definition in your code and make the same modifications to other classes in the same directory, you might tell the AI agent "Do the same thing in similar places in this directory." Here, tracking your intent means understanding that “the same thing" refers to that recent edit you just made, which must be followed by appropriate search and tool-calling to implement the changes. In this course, you'll learn the inner workings of coding agents, their strengths and limitations, and how to use Windsurf to quickly build several applications. In detail, you'll: - Build a mental model of how agents work by combining human-action tracking, tool integration, and context awareness to carry out an agentic coding workflow. - Learn the challenges of code search and discovery and how a multi-step retrieval approach helps coding agents address them. - Use Windsurf to analyze and understand a large, old codebase and update it to the latest versions of the frameworks and packages it uses. - Build a Wikipedia data analysis app that retrieves, parses, and analyzes word frequencies. - Enhance the performance of your Wikipedia analysis app by adding caching, and through this, also learn how to course-correct when the AI agent produces unexpected results. - Learn tips and tricks such as keyboard shortcuts, autocomplete, and @ mentions to quickly call on agentic capabilities. - Use image/multimodal capabilities of the AI agent to increase your development velocity; you'll see an example of uploading a mockup with sketched-out UI features, and ask the agent to use that to build new functionality to an app. By the end of this course, you’ll understand agentic coding in-depth and know how to use it to make your development process much faster, more efficient, and enjoyable. Please sign up here!
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New course to bring you up to state-of-the-art at using AI to help you code: Build Apps with Windsurf's AI Coding Agents, built in partnership with WIndsurf (Codeium) and taught by Anshul Ramachandran! AI-assisted IDEs (Integrated Development Environments) make developers’ workflows faster, more efficient, and much more fun. Agentic tools like Windsurf are more than just code autocomplete—they are collaborative coding agents that help you break down complex applications, iterate efficiently, and generate code that spans multiple files. Although a lot of coding assistants share the same underlying large language models for planning and reasoning, a major point of distinction is how they handle tools, keep track of context, and stay aligned with your intent as a developer. For instance, if you make modifications to a class definition in your code and make the same modifications to other classes in the same directory, you might tell the AI agent "Do the same thing in similar places in this directory." Here, tracking your intent means understanding that “the same thing" refers to that recent edit you just made, which must be followed by appropriate search and tool-calling to implement the changes. In this course, you'll learn the inner workings of coding agents, their strengths and limitations, and how to use Windsurf to quickly build several applications. In detail, you'll: - Build a mental model of how agents work by combining human-action tracking, tool integration, and context awareness to carry out an agentic coding workflow. - Learn the challenges of code search and discovery and how a multi-step retrieval approach helps coding agents address them. - Use Windsurf to analyze and understand a large, old codebase and update it to the latest versions of the frameworks and packages it uses. - Build a Wikipedia data analysis app that retrieves, parses, and analyzes word frequencies. - Enhance the performance of your Wikipedia analysis app by adding caching, and through this, also learn how to course-correct when the AI agent produces unexpected results. - Learn tips and tricks such as keyboard shortcuts, autocomplete, and @ mentions to quickly call on agentic capabilities. - Use image/multimodal capabilities of the AI agent to increase your development velocity; you'll see an example of uploading a mockup with sketched-out UI features, and ask the agent to use that to build new functionality to an app. By the end of this course, you’ll understand agentic coding in-depth and know how to use it to make your development process much faster, more efficient, and enjoyable. Please sign up here!

Andrew Ng

139,803 просмотров • 1 год назад