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👋 Say hi to WorkBuddy: China's most popular desktop AI agent, now available worldwide. WorkBuddy handles the tedious work autonomously and delivers ready-to-use project files across coding, analysis, and productivity scenarios. What sets it apart: Built-in Skills Gallery: Call on 100+ experts with pre-loaded knowledge, skills, and workflows. For...

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JUST IN: Perplexity launched "Perplexity Computer" — and it might be the most complete AI agent system available right now. Not a chatbot upgrade. Not a research tool with a new name. A system that plans entire projects, delegates to specialist AI models, and runs autonomously for hours, days, or months (their words). Here's what makes the architecture genuinely different: → Opus 4.6 handles core reasoning and orchestration → Gemini handles deep research (spawning its own sub-agents) → Grok handles lightweight speed tasks → Veo 3.1 handles video generation → Nano Banana handles image creation → ChatGPT 5.2 handles long-context recall and wide search → You can override model choices per subtask 19 models total. Each task runs in an isolated environment with a real filesystem, real browser, and real tool integrations. You describe an outcome. It breaks it into tasks and subtasks, creates sub-agents for each, and coordinates them automatically. When a sub-agent hits a problem, it spawns more sub-agents to solve it. And it connects to your existing stack — GitHub, Google Drive, Gmail, Slack, Jira, Linear, Notion, Confluence, Ahrefs, Airtable, and more. Critically, it doesn't just run once. It can run on a schedule. Reading your docs, checking your project boards, pulling from your CRM, and acting on what it finds. Market monitoring. Competitor tracking. Weekly reports with charts. Content pipelines. CRON jobs that actually execute. Not "AI that helps you once." AI that runs in the background for days or months. Think of it as managed OpenClaw — similar autonomous capability (scheduled tasks, multi-step workflows, tool integrations) but fully managed. No Mac Mini. No security config. No infrastructure to maintain. I tested it with a complex prompt — a full stock trading simulator with what-if scenarios, correlation heatmaps, sentiment analysis, and a Bloomberg Terminal aesthetic. Two prompts later: deployed to Netlify via GitHub, with working CRON jobs updating live data. I've started using it to analyze my portfolio. But coding is just one lane. This thing researches, writes reports, generates datasets, creates videos, processes documents, and connects to your existing tools — all in one coordinated workflow. The real shift: you don't choose a model anymore. You describe what you need. The system routes each piece of work to whichever model does it best — and spawns new agents when it hits a wall. 19 models, dynamic sub-agents, scheduled tasks, and your entire tool stack connected. Thoughts?
0:37

JUST IN: Perplexity launched "Perplexity Computer" — and it might be the most complete AI agent system available right now. Not a chatbot upgrade. Not a research tool with a new name. A system that plans entire projects, delegates to specialist AI models, and runs autonomously for hours, days, or months (their words). Here's what makes the architecture genuinely different: → Opus 4.6 handles core reasoning and orchestration → Gemini handles deep research (spawning its own sub-agents) → Grok handles lightweight speed tasks → Veo 3.1 handles video generation → Nano Banana handles image creation → ChatGPT 5.2 handles long-context recall and wide search → You can override model choices per subtask 19 models total. Each task runs in an isolated environment with a real filesystem, real browser, and real tool integrations. You describe an outcome. It breaks it into tasks and subtasks, creates sub-agents for each, and coordinates them automatically. When a sub-agent hits a problem, it spawns more sub-agents to solve it. And it connects to your existing stack — GitHub, Google Drive, Gmail, Slack, Jira, Linear, Notion, Confluence, Ahrefs, Airtable, and more. Critically, it doesn't just run once. It can run on a schedule. Reading your docs, checking your project boards, pulling from your CRM, and acting on what it finds. Market monitoring. Competitor tracking. Weekly reports with charts. Content pipelines. CRON jobs that actually execute. Not "AI that helps you once." AI that runs in the background for days or months. Think of it as managed OpenClaw — similar autonomous capability (scheduled tasks, multi-step workflows, tool integrations) but fully managed. No Mac Mini. No security config. No infrastructure to maintain. I tested it with a complex prompt — a full stock trading simulator with what-if scenarios, correlation heatmaps, sentiment analysis, and a Bloomberg Terminal aesthetic. Two prompts later: deployed to Netlify via GitHub, with working CRON jobs updating live data. I've started using it to analyze my portfolio. But coding is just one lane. This thing researches, writes reports, generates datasets, creates videos, processes documents, and connects to your existing tools — all in one coordinated workflow. The real shift: you don't choose a model anymore. You describe what you need. The system routes each piece of work to whichever model does it best — and spawns new agents when it hits a wall. 19 models, dynamic sub-agents, scheduled tasks, and your entire tool stack connected. Thoughts?

Paweł Huryn

219,822 görüntüleme • 6 ay önce

The upgraded Google app for desktop is now available for Windows users globally in English. 💻✨ Use a simple keyboard shortcut (Alt + Space) to instantly find what you need—information from the web, your computer files, installed apps, and Google Drive files—all from the Search box. With AI Mode in Search and Lens built right in, you can ask whatever’s on your mind or search what’s on your screen to get helpful AI-powered responses with links to the web.
0:26

The upgraded Google app for desktop is now available for Windows users globally in English. 💻✨ Use a simple keyboard shortcut (Alt + Space) to instantly find what you need—information from the web, your computer files, installed apps, and Google Drive files—all from the Search box. With AI Mode in Search and Lens built right in, you can ask whatever’s on your mind or search what’s on your screen to get helpful AI-powered responses with links to the web.

Rajan Patel

114,317 görüntüleme • 4 ay önce

FINALLY! Anthropic just shipped the missing piece between OpenClaw and Claude Cowork… Remote control You can now text Claude from your phone using “Dispatch” and it: - Executes tasks on your desktop. - Reads your local files. - Searches your Slack and email. - Builds presentations. - Organizes your folders. One persistent conversation. You send it a mission from your pocket. You come back to finished work sitting in your file system. Your phone just became a remote control for an AI employee that lives on your computer.
0:23

FINALLY! Anthropic just shipped the missing piece between OpenClaw and Claude Cowork… Remote control You can now text Claude from your phone using “Dispatch” and it: - Executes tasks on your desktop. - Reads your local files. - Searches your Slack and email. - Builds presentations. - Organizes your folders. One persistent conversation. You send it a mission from your pocket. You come back to finished work sitting in your file system. Your phone just became a remote control for an AI employee that lives on your computer.

Josh Kale

368,609 görüntüleme • 5 ay önce

AI agents are only as powerful as the content they can access. Anthropic announced Dispatch in Claude Cowork — assign tasks from your phone, let Claude navigate your computer, get complex work done autonomously. But without a file system built for AI, even the most capable agent is working blind. Connect Claude Cowork to Box and your files become the foundation it reasons from. Is your content infrastructure ready for AI agents?
0:52

AI agents are only as powerful as the content they can access. Anthropic announced Dispatch in Claude Cowork — assign tasks from your phone, let Claude navigate your computer, get complex work done autonomously. But without a file system built for AI, even the most capable agent is working blind. Connect Claude Cowork to Box and your files become the foundation it reasons from. Is your content infrastructure ready for AI agents?

Box

432,932 görüntüleme • 5 ay önce

Introducing Base44 Superagents. AI agents built with managed infrastructure, secured by default, one-click integrations, and 24/7 execution from the start. Everything is taken care of so you can focus on what your agent does, not how to get it running. That means no API keys to juggle, no config files, no security setup, and no maintenance. We handle all of it. Your Superagent connects to all the tools you already use in one click, runs on schedules and triggers, remembers context across sessions, acts proactively on your behalf, and keeps working around the clock. All from wherever you already are, WhatsApp, Telegram, Slack, or your browser. The AI agent everyone's been waiting for, with everything you need already built in. We're excited to get this into your hands, so we're giving free credits to everyone who comments and reposts in the next 24 hours.
1:51

Introducing Base44 Superagents. AI agents built with managed infrastructure, secured by default, one-click integrations, and 24/7 execution from the start. Everything is taken care of so you can focus on what your agent does, not how to get it running. That means no API keys to juggle, no config files, no security setup, and no maintenance. We handle all of it. Your Superagent connects to all the tools you already use in one click, runs on schedules and triggers, remembers context across sessions, acts proactively on your behalf, and keeps working around the clock. All from wherever you already are, WhatsApp, Telegram, Slack, or your browser. The AI agent everyone's been waiting for, with everything you need already built in. We're excited to get this into your hands, so we're giving free credits to everyone who comments and reposts in the next 24 hours.

Base44

1,582,753 görüntüleme • 5 ay önce

Run your coding agent on a local model, with QVAC. OpenCode now plugs into a model on your own machine through our official plugin. That changes two things. Privacy by default. Your repo, your prompts, and every command the agent runs stay on your device. No third-party model ever sees your code. For an agent that reads your codebase and runs commands, that is the point, not a nice-to-have. New workflows. With no meter and no rate limit, the agent does not have to stop. Let it loop on a task, refactor a whole repo overnight, or run a watch-build-fix loop that keeps going. Setup takes a few minutes: one line in opencode.json and OpenCode runs on a local QVAC model. In the video demo, it handles three real developer tasks back to back, fully offline.
1:53

Run your coding agent on a local model, with QVAC. OpenCode now plugs into a model on your own machine through our official plugin. That changes two things. Privacy by default. Your repo, your prompts, and every command the agent runs stay on your device. No third-party model ever sees your code. For an agent that reads your codebase and runs commands, that is the point, not a nice-to-have. New workflows. With no meter and no rate limit, the agent does not have to stop. Let it loop on a task, refactor a whole repo overnight, or run a watch-build-fix loop that keeps going. Setup takes a few minutes: one line in opencode.json and OpenCode runs on a local QVAC model. In the video demo, it handles three real developer tasks back to back, fully offline.

QVAC

11,382,936 görüntüleme • 2 ay önce

🚨 Tencent just dropped a serious open-source AI contender. Meet Hy4 Preview built for productivity, coding & agentic workflows. 770B total parameters. 49B active. 1M+ token context. But the numbers aren’t the most interesting part. Hy4 Preview is designed to handle what actually matters: planning, tool use, coding, research, document workflows and complex multi-step tasks. In Tencent’s internal blind evaluation across 203 engineering tasks, it scored 2.99/4, edging out GLM 5.3 (2.92) and Kimi K3 (2.94). From full-stack development and research to workplace automation and even game development, this looks less like “just another LLM” and more like a model built to get real work done. Worth watching 👀 🔗 Try it with WorkBuddy: Tencent Hy Tencent AI WorkBuddy
1:02

🚨 Tencent just dropped a serious open-source AI contender. Meet Hy4 Preview built for productivity, coding & agentic workflows. 770B total parameters. 49B active. 1M+ token context. But the numbers aren’t the most interesting part. Hy4 Preview is designed to handle what actually matters: planning, tool use, coding, research, document workflows and complex multi-step tasks. In Tencent’s internal blind evaluation across 203 engineering tasks, it scored 2.99/4, edging out GLM 5.3 (2.92) and Kimi K3 (2.94). From full-stack development and research to workplace automation and even game development, this looks less like “just another LLM” and more like a model built to get real work done. Worth watching 👀 🔗 Try it with WorkBuddy: Tencent Hy Tencent AI WorkBuddy

RAVI KUMAR SAHU

63,568 görüntüleme • 6 gün önce

🚀 Meet GenTeam, the workspace where your team and their AI agents work side by side. We've reimagined Genspark Teams into something new: a place where people and agents chat, stay on the same page, and get work done together. Your team, instantly staffed — deploy agents from the marketplace in one click (Marketer, Coder, Designer, Copywriter, and more), or build your own. Real pros, not chatbots — every agent runs on frontier models, has access to all the tools and Skills in Genspark, and works 24/7. Work side by side — bring your own agents in, DM them privately, or pull people and agents into a group chat to collaborate. Your data, protected — clean, reliable permission controls you can trust. Meet your new team →
3:37

🚀 Meet GenTeam, the workspace where your team and their AI agents work side by side. We've reimagined Genspark Teams into something new: a place where people and agents chat, stay on the same page, and get work done together. Your team, instantly staffed — deploy agents from the marketplace in one click (Marketer, Coder, Designer, Copywriter, and more), or build your own. Real pros, not chatbots — every agent runs on frontier models, has access to all the tools and Skills in Genspark, and works 24/7. Work side by side — bring your own agents in, DM them privately, or pull people and agents into a group chat to collaborate. Your data, protected — clean, reliable permission controls you can trust. Meet your new team →

Genspark

107,924 görüntüleme • 1 ay önce

I've been testing Hy4 preview on real world productivity and coding tasks, and one thing stood out immediately: It does more than generate an answer. It breaks complex requests into clear steps, retains context, and follows detailed instructions across longer workflows. That focus on practical execution makes sense. Tencent developed the training data with experts across software engineering, gaming, finance, and security, then co designed the model with products like WorkBuddy. For me, the difference was especially noticeable in coding, document analysis, and planning tasks. The entire process felt more reliable from start to finish. Pricing is also surprisingly accessible: $0.834 per 1M input tokens $2.501 per 1M output tokens $0.042 per 1M cache hits Hy4 preview is free to experience on WorkBuddy for the next two weeks. Tencent Hy Tencent AI WorkBuddy
0:24

I've been testing Hy4 preview on real world productivity and coding tasks, and one thing stood out immediately: It does more than generate an answer. It breaks complex requests into clear steps, retains context, and follows detailed instructions across longer workflows. That focus on practical execution makes sense. Tencent developed the training data with experts across software engineering, gaming, finance, and security, then co designed the model with products like WorkBuddy. For me, the difference was especially noticeable in coding, document analysis, and planning tasks. The entire process felt more reliable from start to finish. Pricing is also surprisingly accessible: $0.834 per 1M input tokens $2.501 per 1M output tokens $0.042 per 1M cache hits Hy4 preview is free to experience on WorkBuddy for the next two weeks. Tencent Hy Tencent AI WorkBuddy

Alamin

46,261 görüntüleme • 7 gün önce

Today I built this voice agent while on a call with it Introducing /this-needs-a-call - it's a slash command to start a phone call - grill or be grilled by the voice agent in realtime - your coding agent listens in on the call via MCP and works while you talk for hours
6:15

Today I built this voice agent while on a call with it Introducing /this-needs-a-call - it's a slash command to start a phone call - grill or be grilled by the voice agent in realtime - your coding agent listens in on the call via MCP and works while you talk for hours

jacob paris ▲

32,463 görüntüleme • 2 ay önce

Introducing Le Chat Enterprise, the most customizable and secure agent-powered AI assistant for businesses, making AI a real leverage for competitiveness. - Integration with your company knowledge (starting with Gmail, Google Drive, Sharepoint…) - Ability to add frequently used documents for better-informed outputs - Enterprise-grade features: agents, coding assistant, web search, global news coverage… - Secure deployment: on-prem, in your cloud, or as a service.
1:21

Introducing Le Chat Enterprise, the most customizable and secure agent-powered AI assistant for businesses, making AI a real leverage for competitiveness. - Integration with your company knowledge (starting with Gmail, Google Drive, Sharepoint…) - Ability to add frequently used documents for better-informed outputs - Enterprise-grade features: agents, coding assistant, web search, global news coverage… - Secure deployment: on-prem, in your cloud, or as a service.

Mistral AI

109,624 görüntüleme • 1 yıl önce

Most AI agents stop at chat. Agent Max is built for what comes after. Max tools. Max control and configurability. Max production readiness. Your agent can use: • any tools, APIs, MCP, and workflows • built-in knowledge: docs/website • multi-model: OpenAI, Claude, Gemini... • agent-to-agent handoffs • human-in-the-loop • logs, usage tracking, environments, and RBAC • enterprise controls for SOC2/GDPR/HIPAA/ISO needs • hosted chat UI, API, Skill in agents, Slack, WhatsApp, Teams, Voice, and more Agent Max is live now in BuildShip for everyone. Give it a try, or comment/DM to book a demo if you want help setting up your first agent.
1:15

Most AI agents stop at chat. Agent Max is built for what comes after. Max tools. Max control and configurability. Max production readiness. Your agent can use: • any tools, APIs, MCP, and workflows • built-in knowledge: docs/website • multi-model: OpenAI, Claude, Gemini... • agent-to-agent handoffs • human-in-the-loop • logs, usage tracking, environments, and RBAC • enterprise controls for SOC2/GDPR/HIPAA/ISO needs • hosted chat UI, API, Skill in agents, Slack, WhatsApp, Teams, Voice, and more Agent Max is live now in BuildShip for everyone. Give it a try, or comment/DM to book a demo if you want help setting up your first agent.

BuildShip

75,946 görüntüleme • 2 ay önce

Introducing Workshop: cloud + on-device agentic AI. And to celebrate, we're giving away $250k in Google Gemini AI credits. (details below). The future of AI work is neither cloud-based nor local. It's both. In Workshop Cloud, you can use agents powered by frontier models like Claude and/or open source models like Z.ai's GLM-5 to build internal tools, dashboards, and AI web apps. Or, breeze through tasks like managing your Google and Meta Ads. In Workshop Desktop, you can do all the same right on your computer, plus make desktop apps, mobile apps, and 3D creations. Our favorite part? You can power the full agent experience with local models like Qwen 3.5 family on your computer. Fully offline. 2026 is the year in which local models for agentic tasks will become viable for mainstream use. But the setup for tools like OpenClaw is like setting up Linux from scratch on your computer. Workshop Desktop is one-click to install on Windows, Mac, and Linux. It recommends which open source model you should use for your hardware and lets you download and run it right in the app. And its agent harness allows you to chat, create websites, build personal utilities, and analyze data. 100% offline. Or multitask with AI models in the cloud while running other agent threads locally. Start in Workshop Cloud when you want flexibility and speed. Download your project and continue in Workshop Desktop when you want local files, privacy, and/or better performance on large code bases. Publish from either. The agent tooling space is maturing and discerning users have come to expect a lot from their tools. We've packed Workshop with features to help you 10x your productivity. - Native support for skills - Autocompaction for seamless context management - Built-in AI for your apps - Dozens of connectors, like Google Drive, Big Query, and Supabase - dbt integration to ground your dashboards in your semantic layer - Native Github integration - Private app deployment - ... and more (+ we're shipping super fast) To access the free credit offer, RT this post and reply with "Workshop". Make sure you are following us so we can DM you the instructions to redeem. - First 100 to RT + comment get $500 in credits. - Everyone else gets up to $250 And thanks to our partners Modal, Google Gemini, and Z.ai!
3:50

Introducing Workshop: cloud + on-device agentic AI. And to celebrate, we're giving away $250k in Google Gemini AI credits. (details below). The future of AI work is neither cloud-based nor local. It's both. In Workshop Cloud, you can use agents powered by frontier models like Claude and/or open source models like Z.ai's GLM-5 to build internal tools, dashboards, and AI web apps. Or, breeze through tasks like managing your Google and Meta Ads. In Workshop Desktop, you can do all the same right on your computer, plus make desktop apps, mobile apps, and 3D creations. Our favorite part? You can power the full agent experience with local models like Qwen 3.5 family on your computer. Fully offline. 2026 is the year in which local models for agentic tasks will become viable for mainstream use. But the setup for tools like OpenClaw is like setting up Linux from scratch on your computer. Workshop Desktop is one-click to install on Windows, Mac, and Linux. It recommends which open source model you should use for your hardware and lets you download and run it right in the app. And its agent harness allows you to chat, create websites, build personal utilities, and analyze data. 100% offline. Or multitask with AI models in the cloud while running other agent threads locally. Start in Workshop Cloud when you want flexibility and speed. Download your project and continue in Workshop Desktop when you want local files, privacy, and/or better performance on large code bases. Publish from either. The agent tooling space is maturing and discerning users have come to expect a lot from their tools. We've packed Workshop with features to help you 10x your productivity. - Native support for skills - Autocompaction for seamless context management - Built-in AI for your apps - Dozens of connectors, like Google Drive, Big Query, and Supabase - dbt integration to ground your dashboards in your semantic layer - Native Github integration - Private app deployment - ... and more (+ we're shipping super fast) To access the free credit offer, RT this post and reply with "Workshop". Make sure you are following us so we can DM you the instructions to redeem. - First 100 to RT + comment get $500 in credits. - Everyone else gets up to $250 And thanks to our partners Modal, Google Gemini, and Z.ai!

Workshop AI

29,124 görüntüleme • 5 ay önce

A 100% open-source alternative to n8n! Sim is a drag-and-drop UI for creating powerful AI agent workflows: - Runs locally on your machine - Works with local LLMs I built a stock market research agent & connected it to Telegram in minutes. Here's a step-by-step guide:
8:21

A 100% open-source alternative to n8n! Sim is a drag-and-drop UI for creating powerful AI agent workflows: - Runs locally on your machine - Works with local LLMs I built a stock market research agent & connected it to Telegram in minutes. Here's a step-by-step guide:

Akshay 🚀

176,601 görüntüleme • 8 ay önce

New course: Spec-Driven Development with Coding Agents, built in partnership with JetBrains, and taught by Paul Everitt | @pauleveritt@fosstodon.org. Vibe coding is fast, but often produces code that doesn't match what you asked for. This short course teaches you spec-driven development: write a detailed spec defining what to build, and work with your coding agent to implement it. Many of the best developers already build this way. A spec lets you control large code changes with a few words, preserve context across agent sessions, and stay in control as your project grows in complexity. Skills you'll gain: - Write a detailed specification to define your mission, tech stack, and roadmap, giving your agent the context it needs from the start - Plan, implement, and validate features in iterative loops using a spec as your agent's guide - Apply the same repeatable workflow to both new and legacy codebases - Package your workflow into a portable agent skill that works across agents and IDEs Join and write specs that keep your coding agent on track!
2:51

New course: Spec-Driven Development with Coding Agents, built in partnership with JetBrains, and taught by Paul Everitt | @[email protected]. Vibe coding is fast, but often produces code that doesn't match what you asked for. This short course teaches you spec-driven development: write a detailed spec defining what to build, and work with your coding agent to implement it. Many of the best developers already build this way. A spec lets you control large code changes with a few words, preserve context across agent sessions, and stay in control as your project grows in complexity. Skills you'll gain: - Write a detailed specification to define your mission, tech stack, and roadmap, giving your agent the context it needs from the start - Plan, implement, and validate features in iterative loops using a spec as your agent's guide - Apply the same repeatable workflow to both new and legacy codebases - Package your workflow into a portable agent skill that works across agents and IDEs Join and write specs that keep your coding agent on track!

Andrew Ng

464,592 görüntüleme • 4 ay önce

Introducing Nebula Live: The fastest way to work with your agents. You can now talk, text or show them anything. They work in real time, understand what you're saying and autonomously kick off work. Invite your teammates into a live session and everyone can collaborate together. Experience hands free building while just talking and the best part is all your context is saved in the workspace forever. Background mode mutes your agent but they still listen to you, kick off work and let you know when things are done. Share your screen or camera and your agent can see what you are doing. Now in beta across desktop, mobile and web. We're giving away $100 for you to experience Nebula Live. Reply with what you want to talk to your agents about.
0:49

Introducing Nebula Live: The fastest way to work with your agents. You can now talk, text or show them anything. They work in real time, understand what you're saying and autonomously kick off work. Invite your teammates into a live session and everyone can collaborate together. Experience hands free building while just talking and the best part is all your context is saved in the workspace forever. Background mode mutes your agent but they still listen to you, kick off work and let you know when things are done. Share your screen or camera and your agent can see what you are doing. Now in beta across desktop, mobile and web. We're giving away $100 for you to experience Nebula Live. Reply with what you want to talk to your agents about.

Nebula

11,584 görüntüleme • 1 ay önce

New course: Gemini CLI: Code & Create with an Open-Source Agent, built with Google Cloud Tech/Gemini CLI and taught by Jack Wotherspoon. Agentic coding assistants like Gemini CLI are transforming how developers work. This short course teaches you to use Google's open-source agent to coordinate local tools and cloud services for coding and non-coding workflows. Gemini CLI works from your terminal, so it works with your local files and development tools. You can also connect it to services through MCP. Then provide high-level instructions, and it autonomously plans and executes complex workflows. Skills you'll gain: - Build website features and automate code reviews with GitHub ActionsCreate data dashboards that combine local files with cloud data sources - Use MCP servers and extensions to orchestrate workflows across GitHub, Canva, and Google Workspace - Generate social media content from multimedia files like conference recordings I particularly appreciate that Gemini CLI is open-source. You can see exactly how it works, read the prompts it uses, and understand its architecture. The community has contributed thousands of pull requests. Since Gemini 3’s release I've found Gemini CLI highly capable - this is a tool worth having in your toolbox! Whether you're prototyping applications, automating workflows, or working with multimedia content, join to learn to delegate complex tasks and build faster:
2:50

New course: Gemini CLI: Code & Create with an Open-Source Agent, built with Google Cloud Tech/Gemini CLI and taught by Jack Wotherspoon. Agentic coding assistants like Gemini CLI are transforming how developers work. This short course teaches you to use Google's open-source agent to coordinate local tools and cloud services for coding and non-coding workflows. Gemini CLI works from your terminal, so it works with your local files and development tools. You can also connect it to services through MCP. Then provide high-level instructions, and it autonomously plans and executes complex workflows. Skills you'll gain: - Build website features and automate code reviews with GitHub ActionsCreate data dashboards that combine local files with cloud data sources - Use MCP servers and extensions to orchestrate workflows across GitHub, Canva, and Google Workspace - Generate social media content from multimedia files like conference recordings I particularly appreciate that Gemini CLI is open-source. You can see exactly how it works, read the prompts it uses, and understand its architecture. The community has contributed thousands of pull requests. Since Gemini 3’s release I've found Gemini CLI highly capable - this is a tool worth having in your toolbox! Whether you're prototyping applications, automating workflows, or working with multimedia content, join to learn to delegate complex tasks and build faster:

Andrew Ng

125,385 görüntüleme • 7 ay önce

New agentic short course! Multi AI Agent Systems with crewAI, built with CrewAI's founder and CEO João Moura. In this course, you'll learn how to break down complex tasks into subtasks for multiple AI agents, each playing a specialized role, to execute. For example, to generate a research report, you might have researcher, writer, and quality assurance agents collaborate. You'll define the roles, expectations, and interactions between the agents—like a manager organizing a team. You'll work with key agentic AI techniques like role-playing, tool use, memory, guardrails, and cross-agent collaboration. And you'll build your own multi-agent systems that can tackle complex tasks. I think you'll find it both productive and fun to design agents and watch them collaborate to get things done. Let me know what you think! I believe multi-agent architectures will drive significant progress in AI systems. Please sign up here!
2:39

New agentic short course! Multi AI Agent Systems with crewAI, built with CrewAI's founder and CEO João Moura. In this course, you'll learn how to break down complex tasks into subtasks for multiple AI agents, each playing a specialized role, to execute. For example, to generate a research report, you might have researcher, writer, and quality assurance agents collaborate. You'll define the roles, expectations, and interactions between the agents—like a manager organizing a team. You'll work with key agentic AI techniques like role-playing, tool use, memory, guardrails, and cross-agent collaboration. And you'll build your own multi-agent systems that can tackle complex tasks. I think you'll find it both productive and fun to design agents and watch them collaborate to get things done. Let me know what you think! I believe multi-agent architectures will drive significant progress in AI systems. Please sign up here!

Andrew Ng

350,175 görüntüleme • 2 yıl önce

I am hooked on Dynamic Workflows! The idea of generating harnesses on the fly is so compelling that I reverse-engineered it for my agent orchestrator. And then I built a monitoring dashboard (as an HTML artifact) to track tasks, metrics, and reports. I can now use and monitor dynamic workflows in my agent orchestrator with coding agents like Claude Code, Codex, Pi, and even my own custom-built DAIR.AI agent. This is clearly the future of working with agents to accomplish complex, long-running tasks. Some use cases I'm having success with: - Branching deep research tasks (with verification) - Parallel deep research tasks - Session mining of all my agent sessions - Bug hunting - Triaging - Fact-checking - LLM councils - AI simulations - Data synthesis - Evals generation ... and many others Dynamic workflows, like agent skills, feel like an important primitive to not only get the most out of agents but also incorporate dynamic behaviors and important components like cooperation and verification. There is so much exploration ground here. The exciting part is that this is not limited to coding tasks; it extends to business use cases and many other technical domains like science and research.
0:25

I am hooked on Dynamic Workflows! The idea of generating harnesses on the fly is so compelling that I reverse-engineered it for my agent orchestrator. And then I built a monitoring dashboard (as an HTML artifact) to track tasks, metrics, and reports. I can now use and monitor dynamic workflows in my agent orchestrator with coding agents like Claude Code, Codex, Pi, and even my own custom-built DAIR.AI agent. This is clearly the future of working with agents to accomplish complex, long-running tasks. Some use cases I'm having success with: - Branching deep research tasks (with verification) - Parallel deep research tasks - Session mining of all my agent sessions - Bug hunting - Triaging - Fact-checking - LLM councils - AI simulations - Data synthesis - Evals generation ... and many others Dynamic workflows, like agent skills, feel like an important primitive to not only get the most out of agents but also incorporate dynamic behaviors and important components like cooperation and verification. There is so much exploration ground here. The exciting part is that this is not limited to coding tasks; it extends to business use cases and many other technical domains like science and research.

elvis

103,977 görüntüleme • 3 ay önce

Your engineering team is about to snap. And your AI coding agent is making it worse. Introducing CodeRabbit Agent for Slack 🎉 A second brain for engineering teams. Because your tribal knowledge lives in Slack threads nobody can find. At CodeRabbit, we review millions of PRs every week and know how ace engineering teams operate on the planet. The same three things slow every team we see: - Context and decisions that live elsewhere. - Lack of a team-level durable knowledge base - And a trust layer that gives a safety net to your teams Built for Agentic SDLC workflows, CodeRabbit Agent for Slack solves all three problems in one shot while enabling teams to collaborate in real-time with the Agent. CodeRabbit Agent is Slack-native and builds your team’s operating context from every thread, every decision, every conversation your team has ever had. Make your team’s context compound!
1:37

Your engineering team is about to snap. And your AI coding agent is making it worse. Introducing CodeRabbit Agent for Slack 🎉 A second brain for engineering teams. Because your tribal knowledge lives in Slack threads nobody can find. At CodeRabbit, we review millions of PRs every week and know how ace engineering teams operate on the planet. The same three things slow every team we see: - Context and decisions that live elsewhere. - Lack of a team-level durable knowledge base - And a trust layer that gives a safety net to your teams Built for Agentic SDLC workflows, CodeRabbit Agent for Slack solves all three problems in one shot while enabling teams to collaborate in real-time with the Agent. CodeRabbit Agent is Slack-native and builds your team’s operating context from every thread, every decision, every conversation your team has ever had. Make your team’s context compound!

Harjot Gill

4,776,608 görüntüleme • 4 ay önce