正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

Introducing ADK Go, a new open-source toolkit designed to empower Go developers to build powerful AI agents. Highlights: 0:00 Introducing the Go ADK 0:53 Build your first Go agent 1:49 Run your agent 2:23 Understanding Tools 3:28 Run your agent with tools 5:00 Multi-agent patterns in Go 7:58 State,... show more

Google AI Developers

117,555 subscribers

39,753 次观看 • 1 年前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

24 条评论

Google AI Developers 的头像

Google AI Developers1 年前

Read the blog for more details:

Google AI Developers 的头像

Google AI Developers1 年前

More resources to start building: 🔵 Sample: 🔵 Docs: 🔵 Quickstart:

Himanshu Kumar 的头像

Himanshu Kumar1 年前

Google, that ADK Go toolkit sounds quite promising; I'm eager to see how it shapes the future of AI development, you know!

Gopinathan A 的头像

Gopinathan A1 年前

Eased our work👍

Founder Match 的头像

Founder Match1 年前

Google does not stop.

shankar 的头像

shankar1 年前

From running your first agent to orchestrating multi-agent patterns, ADK Go is like giving Go developers a Swiss Army knife for AI. Tech geeks, this one’s going to be fun to explore!

Tobe Duru 的头像

Tobe Duru1 年前

finally, a toolkit that makes sense for go devs

mindseednews 的头像

mindseednews1 年前

4. “Open-source ADK Go is powerful, but imagine merging it with a visual agent builder for non-coders — that would democratize AI even more.”

mindseednews 的头像

mindseednews1 年前

Great start! But imagine integrating this with multimodal context memory — agents that learn not just from code, but from interaction patterns. That would be the next

mindseednews 的头像

mindseednews1 年前

3. “Love this! What if ADK Go included emotional state mapping APIs? That could unlock more human-like AI agent behavior.”

ASI 的头像

ASI1 年前

Open-source AI agent toolkits for diverse languages expand the developer ecosystem - removing barriers accelerates agent innovation.

nyx 的头像

nyx1 年前

Go developers finally getting their AI agent toolkit. Python devs had a 2 year head start but Go's concurrency is about to make agents actually fast

Alex 的头像

Alex1 年前

LFG! 🥳🥳🥳

Uriah 的头像

Uriah1 年前

rust sdk please

Shubh Jain 的头像

Shubh Jain1 年前

This looks really promising for Go developers! The multi-agent patterns section caught my attention - can you share more about how these patterns can be applied in real-world AI projects?This looks really promising for Go developers! The multi-agent patterns section caught my attention - can we expect more documentation on scaling these agents in future updates?

bash 的头像

bash1 年前

This has now helped me settle the choice between Rust and Go. Thank you

Ivan Cheung 的头像

Ivan Cheung1 年前

Let us know all the things you build!

Ditectrev 的头像

Ditectrev1 年前

Pure innovation😍😍😍

mindseednews 的头像

mindseednews1 年前

5. “Strong foundation. Now we need a ‘collaborative AI swarm’ framework — agents that communicate like neurons across different Go instances.”

MindyCore 的头像

MindyCore1 年前

Awesome! 💙

Alin 的头像

Alin1 年前

ADK Go empowers Go developers to build AI agents with Google's open-source toolkit. Multiagent orchestration shifts development from Python-only to production-scale Go workflows. Does native Go performance justify learning new framework or stick with established Python ecosystem?

LordOfTheYaml 的头像

LordOfTheYaml1 年前

Crazy stuff. 🤯

mindseednews 的头像

mindseednews1 年前

2. “Brilliant toolkit! I think the next evolution could be ‘adaptive personality agents’ — where each agent evolves based on user feedback loops.”

Vishal Bulbule 的头像

Vishal Bulbule1 年前

Here is Complete Hands-on WOrkshop on Google ADK & MCP Server

相关视频

1) Go to 2) Choose the "Canvas" from the tools 3) Follow Antonio Gulli and build your *grooving agent* Here is Agent WordLift in action 👇👇

1) Go to 2) Choose the "Canvas" from the tools 3) Follow Antonio Gulli and build your grooving agent Here is Agent WordLift in action 👇👇

Andrea Volpini

42,303 次观看 • 10 个月前

Build smarter AI agents, faster. ⚡️ The open-source Agent Development Kit makes it easy to create modular, multi-agent systems using the models and tools you prefer. Join the ADK Hackathon →

Build smarter AI agents, faster. ⚡️ The open-source Agent Development Kit makes it easy to create modular, multi-agent systems using the models and tools you prefer. Join the ADK Hackathon →

Google for Developers

11,240 次观看 • 1 年前

💫 Simplify your AI agent development. Google's new open-source Agent Development Kit (ADK) is designed for effortless multi-modal and multi-agent systems. Get started →

💫 Simplify your AI agent development. Google's new open-source Agent Development Kit (ADK) is designed for effortless multi-modal and multi-agent systems. Get started →

Google for Developers

13,232 次观看 • 1 年前

Don't waste 2 years learning to become an AI engineer in 2026. Google just gave the complete playbook on full AI agent engineering. 2 hour course. Free: • 00:00 - build your first AI agent • 45:38 - multi agent architecture • 55:30 - AI agents with MCP tools • 1:30:45 - AI agent loop engineering • 1:39:54 - AI agent graph engineering I watched it last night. Halfway through, I realized I could break into Anthropic in weeks, not years. Bookmark now. Watch it. Then build your own AI agent with the guide below.

Don't waste 2 years learning to become an AI engineer in 2026. Google just gave the complete playbook on full AI agent engineering. 2 hour course. Free: • 00:00 - build your first AI agent • 45:38 - multi agent architecture • 55:30 - AI agents with MCP tools • 1:30:45 - AI agent loop engineering • 1:39:54 - AI agent graph engineering I watched it last night. Halfway through, I realized I could break into Anthropic in weeks, not years. Bookmark now. Watch it. Then build your own AI agent with the guide below.

Roan

53,151 次观看 • 2 个月前

This is literally the easiest way to build an AI agent. Zero code. You only need to run a couple of commands. (I've said this before, but Google ADK is my favorite way to build code-first agents.) Here is what you need to do: 1. Open your terminal and create an empty folder 2. Run `uv init` inside the folder (if you don't have uv installed, you are really missing out!) 3. Install the google-adk library using the following command: `uv add google-adk`. 4. At this point, you can use the ask to create your agent with a single command: `uv run adk create --type=config my_agent`. This will ask you a couple of questions, including your GEMINI_API_KEY (you can create one online). 5. The command above will create a my_agent/root_agent.yaml file. Open it and add the following two lines at the end of the file so your agent can use Google to search for stuff: tools: - name: google_search 6. You have everything you need now. Run the adk web interface and start playing with your agent: `uv run adk web` That's it! Literally zero code. The agent works off the YAML configuration file.

This is literally the easiest way to build an AI agent. Zero code. You only need to run a couple of commands. (I've said this before, but Google ADK is my favorite way to build code-first agents.) Here is what you need to do: 1. Open your terminal and create an empty folder 2. Run `uv init` inside the folder (if you don't have uv installed, you are really missing out!) 3. Install the google-adk library using the following command: `uv add google-adk`. 4. At this point, you can use the ask to create your agent with a single command: `uv run adk create --type=config my_agent`. This will ask you a couple of questions, including your GEMINI_API_KEY (you can create one online). 5. The command above will create a my_agent/root_agent.yaml file. Open it and add the following two lines at the end of the file so your agent can use Google to search for stuff: tools: - name: google_search 6. You have everything you need now. Run the adk web interface and start playing with your agent: `uv run adk web` That's it! Literally zero code. The agent works off the YAML configuration file.

Santiago

140,922 次观看 • 11 个月前

Watch this ADK TypeScript tutorial from Mandy Chan to build an AI agent using the open-source toolkit. 04:50 Science Teacher Agent demo 08:30 Customer Order Agent demo

Watch this ADK TypeScript tutorial from Mandy Chan to build an AI agent using the open-source toolkit. 04:50 Science Teacher Agent demo 08:30 Customer Order Agent demo

Google AI Developers

25,024 次观看 • 9 个月前

Introducing the new Aomni - an AI agent that builds other agents for you. Now you can go from idea -> fully working agent with 1 prompt. We provide all the tools and contact datasets to build agents that excel at revenue gen activities. Here are some cool use cases 🧵

Introducing the new Aomni - an AI agent that builds other agents for you. Now you can go from idea -> fully working agent with 1 prompt. We provide all the tools and contact datasets to build agents that excel at revenue gen activities. Here are some cool use cases 🧵

David

71,729 次观看 • 1 年前

🚨 Breaking: Google just open-sourced the Agent Development Kit (ADK) a framework for building AI agents and multi-agent systems. - Build agents in under 100 lines. - Supports MCP More information and how to get started 👇 1/5

🚨 Breaking: Google just open-sourced the Agent Development Kit (ADK) a framework for building AI agents and multi-agent systems. - Build agents in under 100 lines. - Supports MCP More information and how to get started 👇 1/5

AshutoshShrivastava

130,522 次观看 • 1 年前

Go from idea to a working agent faster with the Agents API. Build and run cloud agents with the Codex harness, fully managed by OpenAI. We handle orchestration, long-running sessions, and context management. You focus on what makes your agent unique. Available in public beta.

Go from idea to a working agent faster with the Agents API. Build and run cloud agents with the Codex harness, fully managed by OpenAI. We handle orchestration, long-running sessions, and context management. You focus on what makes your agent unique. Available in public beta.

OpenAI Developers

1,941,295 次观看 • 1 个月前

The best way to learn AI is to build with agents. To help with that, we've launched hands-on labs and a new series on Agentic Engineering. First topic: Agent Skills. Next in the pipeline: planning, context engineering, multi-agent systems, long-running agents,.. Go build!

The best way to learn AI is to build with agents. To help with that, we've launched hands-on labs and a new series on Agentic Engineering. First topic: Agent Skills. Next in the pipeline: planning, context engineering, multi-agent systems, long-running agents,.. Go build!

elvis

31,802 次观看 • 5 个月前

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

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

Lunar

198,150 次观看 • 3 个月前

Build your first AI agent + MCP Server in Python. Here is everything you need to build your first AI agent in less than 20 minutes. About the code you'll see here: 1. I used Google ADK with Gemini Flash to power the agent 2. The agent connects to an MCP server 3. It also uses two custom tools to do its work 4. You can see everything the agent does thanks to Comet's Opik library Here is the video, free for you to watch.

Build your first AI agent + MCP Server in Python. Here is everything you need to build your first AI agent in less than 20 minutes. About the code you'll see here: 1. I used Google ADK with Gemini Flash to power the agent 2. The agent connects to an MCP server 3. It also uses two custom tools to do its work 4. You can see everything the agent does thanks to Comet's Opik library Here is the video, free for you to watch.

Santiago

56,569 次观看 • 1 年前

Google Engineers just dropped a 1-hour course on agentic engineering from scratch: 0% - 00:00 – How to build your first AI agent 25% - 08:24 – Build agent memory (short, persistent, long) 50% - 28:34 – Agentic loops, long-running AI agents 100% - 1:00:22 – Multi-agentic systems This 1-hour guide will replace 10 paid agentic courses on the internet. Watch it today, then read how to run multiple agents in the article below.

Google Engineers just dropped a 1-hour course on agentic engineering from scratch: 0% - 00:00 – How to build your first AI agent 25% - 08:24 – Build agent memory (short, persistent, long) 50% - 28:34 – Agentic loops, long-running AI agents 100% - 1:00:22 – Multi-agentic systems This 1-hour guide will replace 10 paid agentic courses on the internet. Watch it today, then read how to run multiple agents in the article below.

Ricker

12,070 次观看 • 2 个月前

Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside a single graph: 0% → 17:44 - build your first AI agent 25% → 39:30 - run agents with loop engineering 50% → 1:12:38 - turn agent loops into graphs 75% → 1:34:26 - build agents that regulate themselves 100% → 1:55:05 - orchestrate the entire multi-agent system Most people build one agent and stop there. Google is teaching the entire stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the next one. This 2-hour course is worth more than most paid agent engineering courses. Bookmark it and watch today Then read the full architecture below ↓

Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside a single graph: 0% → 17:44 - build your first AI agent 25% → 39:30 - run agents with loop engineering 50% → 1:12:38 - turn agent loops into graphs 75% → 1:34:26 - build agents that regulate themselves 100% → 1:55:05 - orchestrate the entire multi-agent system Most people build one agent and stop there. Google is teaching the entire stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the next one. This 2-hour course is worth more than most paid agent engineering courses. Bookmark it and watch today Then read the full architecture below ↓

Lunar

12,509 次观看 • 2 个月前

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

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

Lunar

404,903 次观看 • 3 个月前

build an agent that speaks your UI. your charts. your forms. your seat maps. multi-turn, streaming, interactive. introducing tambo 1.0, the open-source generative UI toolkit for react.

build an agent that speaks your UI. your charts. your forms. your seat maps. multi-turn, streaming, interactive. introducing tambo 1.0, the open-source generative UI toolkit for react.

Michael Magán

262,602 次观看 • 8 个月前

Anthropic just released 5 workshops on building self-improving agentic systems from scratch: 00:00 - Ship your first Claude agent 36:44 - Self-improving agents (tools,skills) 1:21:25 - Build memory for Claude agents 1:49:47 - Set up a proactive agent 2:11:31 - Make your agent autonomous These 3-hours of Claude workshops will replace 20 paid agentic courses. Watch today, then read article below on how to build a self-improving agentic system with Fable 5.

Anthropic just released 5 workshops on building self-improving agentic systems from scratch: 00:00 - Ship your first Claude agent 36:44 - Self-improving agents (tools,skills) 1:21:25 - Build memory for Claude agents 1:49:47 - Set up a proactive agent 2:11:31 - Make your agent autonomous These 3-hours of Claude workshops will replace 20 paid agentic courses. Watch today, then read article below on how to build a self-improving agentic system with Fable 5.

Codez

508,264 次观看 • 4 个月前

Google Senior Engineer Annie Wang just dropped a free hands-on course on Graph RAG agents, from scratch: Setup → Graph Schema → Embeddings → Hybrid Search (RRF) → ADK Agent → Deploy 0% → 0:00 – a Graph RAG agent with ADK 25% → 13:01 – Build the graph schema and visualize your data 77% → 39:16 – Hybrid search + RRF 84% → 43:05 – Wiring up the ADK agent: runner, session service, memory service 100% → 51:06 – Final demo and deploying the agent with FastAPI This is one of the few guides that walks through real code and architecture, from an empty project to a working agent. Watch it, then build it yourself

Google Senior Engineer Annie Wang just dropped a free hands-on course on Graph RAG agents, from scratch: Setup → Graph Schema → Embeddings → Hybrid Search (RRF) → ADK Agent → Deploy 0% → 0:00 – a Graph RAG agent with ADK 25% → 13:01 – Build the graph schema and visualize your data 77% → 39:16 – Hybrid search + RRF 84% → 43:05 – Wiring up the ADK agent: runner, session service, memory service 100% → 51:06 – Final demo and deploying the agent with FastAPI This is one of the few guides that walks through real code and architecture, from an empty project to a working agent. Watch it, then build it yourself

Morty

19,362 次观看 • 1 个月前