Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

What is a Managed Deep Agent? How does it differ from a Deep Agent? How do you get started? Jess Weng from the LangChain Academy team answers all of these questions in 2 minutes

LangChain's profile picture

LangChain

270,999 subscribers

17,946 Aufrufe • vor 2 Tagen •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

6 Kommentare

Profilbild von Hershal Rao
Hershal Raovor 2 Tagen

@jess_weng18 finally a tutorial shorter than my agent's infinite loop

Profilbild von Dusan Odalovic
Dusan Odalovicvor 2 Tagen

@jess_weng18 2 minutes is less than my agent takes to read its own instructions hihihi

Profilbild von cortexch
cortexchvor 2 Tagen

@jess_weng18 what specific examples of real world tasks does she use for Managed Deep Agents?

Profilbild von Sarah B.
Sarah B.vor 2 Tagen

@jess_weng18 i’ve been trying to understand where managed agents fit into the workflow, so a 2-minute breakdown sounds perfect. saving this for later!

Profilbild von Flix Muller
Flix Mullervor 2 Tagen

@jess_weng18 The shift from building AI agents to managing them reliably is a big step forward. Making powerful agent workflows easier to deploy and maintain could help more teams put AI into production.

Profilbild von Arunkumar S
Arunkumar Svor 2 Tagen

@jess_weng18 @grok send me a summary of this

Ähnliche Videos

PSA: You can connect a Managed Deep Agent to Slack. Mentions, DMs, and thread replies all start a run. Your agent posts its response back in the same conversation. Here’s how to get started ⤵️
5:03

PSA: You can connect a Managed Deep Agent to Slack. Mentions, DMs, and thread replies all start a run. Your agent posts its response back in the same conversation. Here’s how to get started ⤵️

LangChain

21,920 Aufrufe • vor 1 Monat

☑️ New from LangChain Academy: Become a LangChain Certified Agent Engineer The first certification for the full Agent Development Lifecycle. For the first 2 months, use code LCAE50 for 50% off.
0:56

☑️ New from LangChain Academy: Become a LangChain Certified Agent Engineer The first certification for the full Agent Development Lifecycle. For the first 2 months, use code LCAE50 for 50% off.

LangChain

34,677 Aufrufe • vor 2 Monaten

What does market depth actually do to a token? How does liquidity across exchanges affect you? Ask Agent answers questions like these. Ask anything about a token, and get it explained in plain language.
0:22

What does market depth actually do to a token? How does liquidity across exchanges affect you? Ask Agent answers questions like these. Ask anything about a token, and get it explained in plain language.

Rena Labs

37,525 Aufrufe • vor 1 Monat

You can turn an existing LangGraph agent into a fully functional voice agent with Pipecat AI. This 17-minute walkthrough shows you exactly how to do it.
16:58

You can turn an existing LangGraph agent into a fully functional voice agent with Pipecat AI. This 17-minute walkthrough shows you exactly how to do it.

LangChain

19,023 Aufrufe • vor 4 Monaten

🔗 New LangChain Academy Course: Introduction to LangChain (Python) 🔗 Learn how to build with LangChain – our open source framework that makes it easy to start building agents with any model provider. In this course, you’ll create agents that can reason, use tools, and take action, and learn how to debug their behavior with LangSmith. Along the way, you’ll: - Build an agent with the `create_agent` abstraction - Use LangChain’s core building blocks: Models, Messages, Memory, and Tools - Customize your agent with middleware - Debug your agent with LangSmith Observability & Studio By the end of the course, you’ll have assembled a full team of personal assistants. Enroll for free ➡️
2:25

🔗 New LangChain Academy Course: Introduction to LangChain (Python) 🔗 Learn how to build with LangChain – our open source framework that makes it easy to start building agents with any model provider. In this course, you’ll create agents that can reason, use tools, and take action, and learn how to debug their behavior with LangSmith. Along the way, you’ll: - Build an agent with the `create_agent` abstraction - Use LangChain’s core building blocks: Models, Messages, Memory, and Tools - Customize your agent with middleware - Debug your agent with LangSmith Observability & Studio By the end of the course, you’ll have assembled a full team of personal assistants. Enroll for free ➡️

LangChain

41,233 Aufrufe • vor 10 Monaten

🔥 Our latest LangChain Academy course – Deep Research with LangGraph – is now live! 🔥 Deep research agents are taking off – from major AI labs to companies building their own. Research is inherently open-ended. You can't always predict whether a question needs broad exploration or deep analysis. Agents excel here because they adapt on the fly, using each finding to decide where to dig next. Building these systems ourselves and with customers, we've learned that structure matters. The best research agents scope problems with users first. Then, they coordinate multiple specialists instead of overwhelming one generalist. LangGraph is built for these types of long-running, multi-agent workflows. Its persistence layer tracks progress across agents. LangSmith gives you the observability and evaluation tools you need to track and improve performance. In this course, you'll build and evaluate: - A user scoping agent to define research parameters - A multi-agent research team with supervisor - And add tool integration via MCP Enroll for free ➡️
2:47

🔥 Our latest LangChain Academy course – Deep Research with LangGraph – is now live! 🔥 Deep research agents are taking off – from major AI labs to companies building their own. Research is inherently open-ended. You can't always predict whether a question needs broad exploration or deep analysis. Agents excel here because they adapt on the fly, using each finding to decide where to dig next. Building these systems ourselves and with customers, we've learned that structure matters. The best research agents scope problems with users first. Then, they coordinate multiple specialists instead of overwhelming one generalist. LangGraph is built for these types of long-running, multi-agent workflows. Its persistence layer tracks progress across agents. LangSmith gives you the observability and evaluation tools you need to track and improve performance. In this course, you'll build and evaluate: - A user scoping agent to define research parameters - A multi-agent research team with supervisor - And add tool integration via MCP Enroll for free ➡️

LangChain

61,205 Aufrufe • vor 1 Jahr

Introducing Trajectories in LangSmith. A view of agent behavior that everyone on the team can understand at a glance.
0:31

Introducing Trajectories in LangSmith. A view of agent behavior that everyone on the team can understand at a glance.

LangChain

25,140 Aufrufe • vor 28 Tagen

✨New LangChain Academy Course: Learn to build with LangSmith Agent Builder 🪄 Learn how to build your own agents with LangSmith Agent Builder. Anyone can now build agents for complex daily tasks, without writing code. We built Agent Builder for anyone whose day gets swallowed by routine work. The research, follow-ups, updates, scheduling, and status checks that are essential to your operations, but quickly take over your calendar. Agent Builder is different from traditional workflow automations. You don’t need to map every step, tinker with if-this-then-that branching, or babysit dependencies. You just give it feedback like you would a teammate, and the agent learns using its memory. In this quickstart course, you'll learn how to: - Build an email agent - Understand what agents can do - Improve your agent - Set up triggers and your Agent Inbox Enroll for free ➡️
1:45

✨New LangChain Academy Course: Learn to build with LangSmith Agent Builder 🪄 Learn how to build your own agents with LangSmith Agent Builder. Anyone can now build agents for complex daily tasks, without writing code. We built Agent Builder for anyone whose day gets swallowed by routine work. The research, follow-ups, updates, scheduling, and status checks that are essential to your operations, but quickly take over your calendar. Agent Builder is different from traditional workflow automations. You don’t need to map every step, tinker with if-this-then-that branching, or babysit dependencies. You just give it feedback like you would a teammate, and the agent learns using its memory. In this quickstart course, you'll learn how to: - Build an email agent - Understand what agents can do - Improve your agent - Set up triggers and your Agent Inbox Enroll for free ➡️

LangChain

26,513 Aufrufe • vor 9 Monaten

🤖LangSmith Agent Builder Technical Highlights Yesterday we launched LangSmith Agent Builder. Here's a quick technical overview at what is going on under the hood (from memory to an innovative UX):
1:05

🤖LangSmith Agent Builder Technical Highlights Yesterday we launched LangSmith Agent Builder. Here's a quick technical overview at what is going on under the hood (from memory to an innovative UX):

LangChain

27,135 Aufrufe • vor 9 Monaten

LangChain Academy is live! Our first course — Introduction to LangGraph — teaches you the in-and-outs of building a reliable AI agent. In this course, you’ll learn how to: 🛠️ Build agents with LangGraph's graph-based workflows 🔄 Use memory + human-in-the-loop for smarter, self-corrective agents 📚 Create your own AI assistant that can perform knowledge tasks Enroll now for free ➡️ Bring LangChain Academy to your company ➡️
2:36

LangChain Academy is live! Our first course — Introduction to LangGraph — teaches you the in-and-outs of building a reliable AI agent. In this course, you’ll learn how to: 🛠️ Build agents with LangGraph's graph-based workflows 🔄 Use memory + human-in-the-loop for smarter, self-corrective agents 📚 Create your own AI assistant that can perform knowledge tasks Enroll now for free ➡️ Bring LangChain Academy to your company ➡️

LangChain

105,491 Aufrufe • vor 2 Jahren

In 13 minutes, Jeff Barg, Vyshu Khota, and Soroush Khadem walk through how Clay scaled agent evals agents at 300M+ runs a month. Topics covered: ✅ Their four quadrant eval framework ✅ Why closing the production-to-eval loop is the hardest part ✅ How a data lake and long context changed what agents can do with data
13:00

In 13 minutes, Jeff Barg, Vyshu Khota, and Soroush Khadem walk through how Clay scaled agent evals agents at 300M+ runs a month. Topics covered: ✅ Their four quadrant eval framework ✅ Why closing the production-to-eval loop is the hardest part ✅ How a data lake and long context changed what agents can do with data

LangChain

11,325 Aufrufe • vor 1 Monat

.Mukil Loganathan’s Interrupt keynote on Sandboxes. In 20 minutes, you’ll learn how to run agent code safely. Isolated from your runtime, with network controls, persistent state, and snapshot/restore when things go wrong.
0:27

.Mukil Loganathan’s Interrupt keynote on Sandboxes. In 20 minutes, you’ll learn how to run agent code safely. Isolated from your runtime, with network controls, persistent state, and snapshot/restore when things go wrong.

LangChain

16,796 Aufrufe • vor 4 Monaten

Introducing LangSmith Custom Apps Create any interface from your agent data with a prompt. If you can think it, LangSmith can build it. Now GA.
0:38

Introducing LangSmith Custom Apps Create any interface from your agent data with a prompt. If you can think it, LangSmith can build it. Now GA.

LangChain

16,768 Aufrufe • vor 28 Tagen

Managed Deep Agents explained in 1 minute by Harrison Chase
1:05

Managed Deep Agents explained in 1 minute by Harrison Chase

LangChain

25,423 Aufrufe • vor 4 Monaten

🔥 New LangChain Academy Course: LangChain Essentials (Python & TypeScript) 🔥 Learn the basics of LangChain – our open source framework that makes it easy to start building agents with any model provider. Last week, we released LangChain 1.0. We’ve completely rewritten LangChain to be opinionated, focused, and powered by LangGraph’s runtime. It includes a new `create_agent` abstraction to build agents quickly, middleware for flexibility, and standard content blocks that work across any model provider. In this quickstart course, you'll learn how to: - Build an agent with the `create_agent` abstraction - Use LangChain’s core building blocks: Models, Messages, Memory, and Tools - Customize your agent with middleware - Debug and test your agent with LangSmith Observability & Evaluation Enroll for free ➡️
1:37

🔥 New LangChain Academy Course: LangChain Essentials (Python & TypeScript) 🔥 Learn the basics of LangChain – our open source framework that makes it easy to start building agents with any model provider. Last week, we released LangChain 1.0. We’ve completely rewritten LangChain to be opinionated, focused, and powered by LangGraph’s runtime. It includes a new `create_agent` abstraction to build agents quickly, middleware for flexibility, and standard content blocks that work across any model provider. In this quickstart course, you'll learn how to: - Build an agent with the `create_agent` abstraction - Use LangChain’s core building blocks: Models, Messages, Memory, and Tools - Customize your agent with middleware - Debug and test your agent with LangSmith Observability & Evaluation Enroll for free ➡️

LangChain

50,518 Aufrufe • vor 1 Jahr

🚀 New LangChain Academy Course: Building Reliable Agents 🚀 Shipping agents to production is hard. Traditional software is deterministic – when something breaks, you check the logs and fix the code. But agents rely on non-deterministic models. Add multi-step reasoning, tool use, and real user traffic, and building reliable agents becomes far more complex than traditional system design. The goal of this course is to teach you how to take an agent from first run to production-ready system through iterative cycles of improvement. You’ll learn how to do this with LangSmith, our agent engineering platform for observing, evaluating, and deploying agents. Enroll for free ➡️
2:02

🚀 New LangChain Academy Course: Building Reliable Agents 🚀 Shipping agents to production is hard. Traditional software is deterministic – when something breaks, you check the logs and fix the code. But agents rely on non-deterministic models. Add multi-step reasoning, tool use, and real user traffic, and building reliable agents becomes far more complex than traditional system design. The goal of this course is to teach you how to take an agent from first run to production-ready system through iterative cycles of improvement. You’ll learn how to do this with LangSmith, our agent engineering platform for observing, evaluating, and deploying agents. Enroll for free ➡️

LangChain

30,744 Aufrufe • vor 7 Monaten

Insights Agent & Multi-turn Evals Agents run for a long period of time and have multiple interactions with users, tackling a wide variety of problems. Today we’re launching two new features in LangSmith, our agent engineering platform, so you can better understand your agent behavior: • Insights Agent is a new agent that automatically categorizes agent behavior patterns in LangSmith • Multi-turn Evals lets you evaluate agent trajectory across complete conversations, so you can see if the agent actually accomplished user goals Learn more:
0:40

Insights Agent & Multi-turn Evals Agents run for a long period of time and have multiple interactions with users, tackling a wide variety of problems. Today we’re launching two new features in LangSmith, our agent engineering platform, so you can better understand your agent behavior: • Insights Agent is a new agent that automatically categorizes agent behavior patterns in LangSmith • Multi-turn Evals lets you evaluate agent trajectory across complete conversations, so you can see if the agent actually accomplished user goals Learn more:

LangChain

13,322 Aufrufe • vor 1 Jahr

Anthropic Managed Agents team: "Fable 5 - is our best model for self-improving agent systems. add /loops, dynamic workflows, dreaming - and you're unstoppable." in 13 minutes, the Anthropic team shows how to build self-improving agent systems with Fable 5 from scratch. Worth more than a $500 agent-building course. Live from the Anthropic stage in Japan. Unpublished
13:23

Anthropic Managed Agents team: "Fable 5 - is our best model for self-improving agent systems. add /loops, dynamic workflows, dreaming - and you're unstoppable." in 13 minutes, the Anthropic team shows how to build self-improving agent systems with Fable 5 from scratch. Worth more than a $500 agent-building course. Live from the Anthropic stage in Japan. Unpublished

Movez

67,091 Aufrufe • vor 4 Monaten

How to run agent evals with Harbor Framework and LangSmith sandboxes, full traces included.
9:18

How to run agent evals with Harbor Framework and LangSmith sandboxes, full traces included.

LangChain

11,376 Aufrufe • vor 3 Monaten

At Interrupt, we learned how LinkedIn cut time-to-interview by 60% By building a hiring agent with LangGraph. Watch the full session:
1:29

At Interrupt, we learned how LinkedIn cut time-to-interview by 60% By building a hiring agent with LangGraph. Watch the full session:

LangChain

14,458 Aufrufe • vor 3 Monaten