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Anthropic has released a 36-minute guide to building AI Agents that automate an entire company. Free. From the engineers who built Claude. Agents that work, distribute tasks, and execute everything on their own. 6:00 → Key concepts and architecture 9:19 → Hands-on workshop (building the agent) 19:51 → Live... show more

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19,932 views • 17 days ago •via X (Twitter)

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Don't waste 2 years learning to build AI agents. An Anthropic engineer who built Claude Code tells you what to learn from scratch instead. 60 minutes course. Free: 00:00 - AI agent architecture 24:47 - LangGraph AI agent 29:15 - building AI agents live Prompting is the old job. Building AI agent loops is the new one. Bookmark now & watch it. Then build your own AI agent with the guide below.

Don't waste 2 years learning to build AI agents. An Anthropic engineer who built Claude Code tells you what to learn from scratch instead. 60 minutes course. Free: 00:00 - AI agent architecture 24:47 - LangGraph AI agent 29:15 - building AI agents live Prompting is the old job. Building AI agent loops is the new one. Bookmark now & watch it. Then build your own AI agent with the guide below.

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Don't waste 2 years building AI agents the wrong way. An Anthropic engineer dropped a 1 hour course on the exact way to build AI agents from scratch. • 00:00 - building a Claude AI agent live • 34:01 - taking AI agents to production • 52:20 - AI agent harness Prompting is the old job. Building AI agentic loops is the new one. This one video replaces 10 paid courses on vibe coding. Bookmark & watch it now. Then build your own AI agent with the guide below.

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2,133,626 views • 1 month ago

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Wow Anthropic just released Claude Code for Web/Mobile, and it changes everything Now AI Agents can build apps for you 24/7 Here's your full beginner's guide to building an AI agent army that works for you all day (trust me you want to bookmark this one)

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160,772 views • 10 months ago

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62,153 views • 2 months ago

Andrew Ng just released a 2-hour course On building agentic skills from scratch with Anthropic: 00:00 - How to build agent skills with Claude 22:32 - Claude pre-built skills for AI agents 41:07 - Agentic skills vs tools, MCP, and subagents 01:06:06 - Skills for long-running agents This 2-hour watch can replace 10 paid courses on building agents Taught with Anthropic themselves Bookmark and watch it tonight Then read the article below

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104,084 views • 1 month ago

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Anthropic just dropped 5 workshops that take you from zero to a full app with AI agents. Useful at any level, just pick the timecode where you're at: 00:00 - The model choice nobody explains 31:14 - All you need to know about prompting 1:04:42 - Claude Code features most people never find 1:51:34 - From a prompt to a working product 2:19:10 - Building your first app with Claude Watch today, then go to the guide that explains everything you have to know about loops.

Anthropic just dropped 5 workshops that take you from zero to a full app with AI agents. Useful at any level, just pick the timecode where you're at: 00:00 - The model choice nobody explains 31:14 - All you need to know about prompting 1:04:42 - Claude Code features most people never find 1:51:34 - From a prompt to a working product 2:19:10 - Building your first app with Claude Watch today, then go to the guide that explains everything you have to know about loops.

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54,349 views • 1 month ago

Anthropic engineer just dropped a full walkthrough on building AI agents from scratch this single video is worth more than any $600 AI agents course here's what she covers: > what Agent, Environment, and Session actually mean > how to stream live events from your agent > wiring up custom tools from scratch > the server-side loop that makes agents actually work > roadmap to subagents, vaults, and memory 37 minutes that will answer every question you have about building agents the people who understand what Claude can actually do are building things everyone else thinks requires a whole team most of them aren't smarter, they just know features that most people have never heard of full breakdown on every Claude feature worth knowing in the article below

Anthropic engineer just dropped a full walkthrough on building AI agents from scratch this single video is worth more than any $600 AI agents course here's what she covers: > what Agent, Environment, and Session actually mean > how to stream live events from your agent > wiring up custom tools from scratch > the server-side loop that makes agents actually work > roadmap to subagents, vaults, and memory 37 minutes that will answer every question you have about building agents the people who understand what Claude can actually do are building things everyone else thinks requires a whole team most of them aren't smarter, they just know features that most people have never heard of full breakdown on every Claude feature worth knowing in the article below

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39,240 views • 3 months ago

An AI engineer at Microsoft has just revealed how their teams build AI agents using Anthropic (Claude). It’s a free 34-minute workshop delivered directly by the Microsoft team. Save it to your favorites and watch it as soon as possible. 🔖 Opus 4.7 + more than 1,400 MCP tools already ready to use. You connect Claude to an agent → add tools → deploy it to production. It’s way more practical and useful than most of those “vibe-coding” courses that sell for 500).

An AI engineer at Microsoft has just revealed how their teams build AI agents using Anthropic (Claude). It’s a free 34-minute workshop delivered directly by the Microsoft team. Save it to your favorites and watch it as soon as possible. 🔖 Opus 4.7 + more than 1,400 MCP tools already ready to use. You connect Claude to an agent → add tools → deploy it to production. It’s way more practical and useful than most of those “vibe-coding” courses that sell for 500).

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410,279 views • 2 months ago

Anthropic engineer: "You're not supposed to prompt Claude. You're supposed to build a system that prompts itself." In 55-minutes she shows exactly how Anthropic builds agents that remember, fix their own mistakes and get smarter with every run with graphs. No paid agents course I've taken gets this specific. Watch it, then read the guide below on building the same system with Graphs.

Anthropic engineer: "You're not supposed to prompt Claude. You're supposed to build a system that prompts itself." In 55-minutes she shows exactly how Anthropic builds agents that remember, fix their own mistakes and get smarter with every run with graphs. No paid agents course I've taken gets this specific. Watch it, then read the guide below on building the same system with Graphs.

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83,888 views • 18 days ago

In the future, you’ll be able to accomplish a goal by just giving Claude an outcome and a budget. That’s the direction Anthropic is building in with its new Managed Agents features, announced at this week’s Code with Claude developer event. The basic idea: Claude, wrapped in a computer in the cloud, that you can spin up, scale, and manage as needed. Anthropic is taking on the infrastructure that kills most agent products, and making sure that it scales to meet the needs of agents running 24/7. On this week’s AI & I from Every 📧, I talk with Angela Jiang (Angela Jiang), head of product for the Claude platform, and Katelyn Lesse (Katelyn Lesse), head of engineering for the Claude platform, about what Anthropic is building and what it takes to make agents reliable in production. We get into: - Why the "build a generic harness, hot-swap any model behind it" playbook is already outdated. Angela points to eval data on Memory where the same task across different harnesses performed drastically differently. - The infrastructure wall every team hits in production—and why Katelyn thinks “my sandbox died and took the agent with it” is the real reason internal agents don't ship. - Why Anthropic is so bullish on using file systems and skills within Claude, including Angela's argument that those early design choices can compound for years. This is a must-watch for anyone trying to take an agent past the demo and into production. Watch below! Timestamps: How the Claude platform evolved from API to agents: 00:01:48 The primitives that make up Claude Managed Agents: 00:04:09 Why the harness and the model are becoming a single unit: 00:10:37 The infrastructure wall that kills most agent projects in production: 00:18:49 Why team agents need a different shape than individual productivity tools: 00:24:49 How Anthropic's legal team uses an agent to review marketing copy: 00:26:36 Using multi-agent orchestration for advisor strategies, adversarial pairs, and swarms: 00:34:24 How to measure agent success with outcome and budget as the end state: 00:35:50 What the platform looks like a year from now, when Claude writes its own harness: 00:39:11

In the future, you’ll be able to accomplish a goal by just giving Claude an outcome and a budget. That’s the direction Anthropic is building in with its new Managed Agents features, announced at this week’s Code with Claude developer event. The basic idea: Claude, wrapped in a computer in the cloud, that you can spin up, scale, and manage as needed. Anthropic is taking on the infrastructure that kills most agent products, and making sure that it scales to meet the needs of agents running 24/7. On this week’s AI & I from Every 📧, I talk with Angela Jiang (Angela Jiang), head of product for the Claude platform, and Katelyn Lesse (Katelyn Lesse), head of engineering for the Claude platform, about what Anthropic is building and what it takes to make agents reliable in production. We get into: - Why the "build a generic harness, hot-swap any model behind it" playbook is already outdated. Angela points to eval data on Memory where the same task across different harnesses performed drastically differently. - The infrastructure wall every team hits in production—and why Katelyn thinks “my sandbox died and took the agent with it” is the real reason internal agents don't ship. - Why Anthropic is so bullish on using file systems and skills within Claude, including Angela's argument that those early design choices can compound for years. This is a must-watch for anyone trying to take an agent past the demo and into production. Watch below! Timestamps: How the Claude platform evolved from API to agents: 00:01:48 The primitives that make up Claude Managed Agents: 00:04:09 Why the harness and the model are becoming a single unit: 00:10:37 The infrastructure wall that kills most agent projects in production: 00:18:49 Why team agents need a different shape than individual productivity tools: 00:24:49 How Anthropic's legal team uses an agent to review marketing copy: 00:26:36 Using multi-agent orchestration for advisor strategies, adversarial pairs, and swarms: 00:34:24 How to measure agent success with outcome and budget as the end state: 00:35:50 What the platform looks like a year from now, when Claude writes its own harness: 00:39:11

Dan Shipper 📧

66,339 views • 3 months ago

LangChain's CEO and CTO spent 43 minutes on stage laying out the harness, the lifecycle and the infrastructure behind agents that actually survive production: · 2:00 - Why building agents is different from building software · 6:34 - What Deep Agents is: the agent harness explained · 14:48 - LangSmith Sandboxes, announced live · 19:20 - The Agent Development Lifecycle, defined · 25:58 - Why agent trace payloads keep getting larger · 29:38 - The architecture of SmithDB · 34:00 - How Clay and Vanta run on SmithDB · 42:50 - Building the platform for the entire lifecycle The harness is only the first of three layers. The article below covers the other two. Watch this before you ship your next agent ↓

LangChain's CEO and CTO spent 43 minutes on stage laying out the harness, the lifecycle and the infrastructure behind agents that actually survive production: · 2:00 - Why building agents is different from building software · 6:34 - What Deep Agents is: the agent harness explained · 14:48 - LangSmith Sandboxes, announced live · 19:20 - The Agent Development Lifecycle, defined · 25:58 - Why agent trace payloads keep getting larger · 29:38 - The architecture of SmithDB · 34:00 - How Clay and Vanta run on SmithDB · 42:50 - Building the platform for the entire lifecycle The harness is only the first of three layers. The article below covers the other two. Watch this before you ship your next agent ↓

slash1s

14,757 views • 1 month ago

Ex-Google engineer just released a free 3-hour course on building and monetizing AI agents. How to go from one agent to a full system that finds leads and makes money: 00:00 - Design an AI agent system 07:38 - Add human handoffs 19:27 - Understand RAG and vector databases 52:38 - Deploy agents to Google Cloud 1:25:57 - Turn agents into a paid WhatsApp business 1:33:00 - Convert conversations into leads 2:24:01 - Learn loops vs graphs 2:33:08 - Build a multi-tool agent graph Most people are still building AI demos. This course shows the full stack: Agents → RAG → Deployment → Leads → Revenue Building agents is the old workflow. Monetizing agent systems is the new one. This 3-hour watch covers more than most $500 paid courses. Save it before everyone starts selling the same thing.

Ex-Google engineer just released a free 3-hour course on building and monetizing AI agents. How to go from one agent to a full system that finds leads and makes money: 00:00 - Design an AI agent system 07:38 - Add human handoffs 19:27 - Understand RAG and vector databases 52:38 - Deploy agents to Google Cloud 1:25:57 - Turn agents into a paid WhatsApp business 1:33:00 - Convert conversations into leads 2:24:01 - Learn loops vs graphs 2:33:08 - Build a multi-tool agent graph Most people are still building AI demos. This course shows the full stack: Agents → RAG → Deployment → Leads → Revenue Building agents is the old workflow. Monetizing agent systems is the new one. This 3-hour watch covers more than most $500 paid courses. Save it before everyone starts selling the same thing.

Lunar

347,476 views • 22 days ago

Andrew Ng just released a 2-hour course on building agentic skills from scratch with Anthropic: • 00:00 – How to build agent skills with Claude • 22:32 – Claude pre-built skills for AI agents • 41:07 – Agentic skills vs tools, MCP, subagents • 01:06:06 – Skills for long-running agents This 2-hour watch will replace 10 paid courses on building agents, by Anthropic themselves. Watch it today, then read how to build self-improving agentic systems in the article below.

Andrew Ng just released a 2-hour course on building agentic skills from scratch with Anthropic: • 00:00 – How to build agent skills with Claude • 22:32 – Claude pre-built skills for AI agents • 41:07 – Agentic skills vs tools, MCP, subagents • 01:06:06 – Skills for long-running agents This 2-hour watch will replace 10 paid courses on building agents, by Anthropic themselves. Watch it today, then read how to build self-improving agentic systems in the article below.

Codez

64,040 views • 1 month ago

Google just showed how AI engineers are moving from simple "RAG" to "graphs", memory and multimodal agents • 15:32 - setting up the production agent stack • 28:00 - turning disconnected data into a knowledge graph • 41:00 - Graph RAG with semantic + hybrid search • 58:00 - extracting graph context from images, text and video • 1:09:00 - orchestrating specialized agents with ADK • 1:20:00 - giving agents persistent memory across sessions 94-minute Google Cloud workshop, and it’s one of the clearest hands-on examples of the shift from -> RAG → Graph RAG → Memory → Multimodal Agent Graphs. The workshop uses Spanner Graph, Gemini, ADK and Memory Bank to build that stack. Watch it today, then read the full “From RAG to Context Graphs” roadmap below.

Google just showed how AI engineers are moving from simple "RAG" to "graphs", memory and multimodal agents • 15:32 - setting up the production agent stack • 28:00 - turning disconnected data into a knowledge graph • 41:00 - Graph RAG with semantic + hybrid search • 58:00 - extracting graph context from images, text and video • 1:09:00 - orchestrating specialized agents with ADK • 1:20:00 - giving agents persistent memory across sessions 94-minute Google Cloud workshop, and it’s one of the clearest hands-on examples of the shift from -> RAG → Graph RAG → Memory → Multimodal Agent Graphs. The workshop uses Spanner Graph, Gemini, ADK and Memory Bank to build that stack. Watch it today, then read the full “From RAG to Context Graphs” roadmap below.

Morlex

74,134 views • 16 days ago