Загрузка видео...

Не удалось загрузить видео

На главную

🚀 Announcing LangSmith Skills + CLI 🚀 Agent improvements are increasingly driven by coding agents themselves. We're releasing LangSmith Skills alongside the LangSmith CLI to make coding agents experts at the agent engineering lifecycle. LangSmith Skills enable agents to debug traces, create datasets, and run experiments - and thanks...

LangChain's profile picture

LangChain

248,342 subscribers

49,416 просмотров • 3 месяцев назад •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

Today, we’re shipping new ways to observe, analyze, and debug agents with LangSmith: • Polly: an AI assistant for AI engineering that helps you understand traces, threads, and improve prompts • LangSmith Fetch: a CLI for pulling trace & thread data straight into your terminal or coding agent Agents are running longer and getting more complex, which demands new debugging workflows beyond simple LLM apps. We wrote a blog on the trends behind this shift— and why tools like Polly and LangSmith Fetch are needed. Shipping reliable agents requires full visibility into agent behavior, with tooling that helps you reason over that data in the UI, the terminal, or alongside coding agents. 📔Learn more about Polly: 📔Learn more about LangSmith Fetch: 📔How to observe deep agents: 📽️ Polly video tutorial: 📽️ LangSmith Fetch video tutorial:
7:10

Today, we’re shipping new ways to observe, analyze, and debug agents with LangSmith: • Polly: an AI assistant for AI engineering that helps you understand traces, threads, and improve prompts • LangSmith Fetch: a CLI for pulling trace & thread data straight into your terminal or coding agent Agents are running longer and getting more complex, which demands new debugging workflows beyond simple LLM apps. We wrote a blog on the trends behind this shift— and why tools like Polly and LangSmith Fetch are needed. Shipping reliable agents requires full visibility into agent behavior, with tooling that helps you reason over that data in the UI, the terminal, or alongside coding agents. 📔Learn more about Polly: 📔Learn more about LangSmith Fetch: 📔How to observe deep agents: 📽️ Polly video tutorial: 📽️ LangSmith Fetch video tutorial:

LangChain

31,035 просмотров • 6 месяцев назад

Introducing LangSmith Fleet. Agents for every team. → Build agents with natural language → Share and control who can edit, run, or clone each agent → Manage authentication with agent identity → Approve actions with human-in-the-loop → Track and audit actions with tracing in LangSmith Observability Try Fleet:
1:06

Introducing LangSmith Fleet. Agents for every team. → Build agents with natural language → Share and control who can edit, run, or clone each agent → Manage authentication with agent identity → Approve actions with human-in-the-loop → Track and audit actions with tracing in LangSmith Observability Try Fleet:

LangChain

9,397,938 просмотров • 2 месяцев назад

Give Claude Code, Codex, OpenClaw, Cline access to the entire web from your terminal. Introducing TinyFish CLI + Skills. 15+ agent workflows ready to use. CLI runs browser automations from bash for max token efficiency. Skills tell agents how to use that CLI. 500 free steps.
0:25

Give Claude Code, Codex, OpenClaw, Cline access to the entire web from your terminal. Introducing TinyFish CLI + Skills. 15+ agent workflows ready to use. CLI runs browser automations from bash for max token efficiency. Skills tell agents how to use that CLI. 500 free steps.

TinyFish

182,864 просмотров • 2 месяцев назад

Introducing mem0 CLI 🚀 Give your agents memory from the terminal - add, search, and retrieve memory - remember agents + developers's preference - agent-first, JSON schema-driven We built mem0 CLI to help agents remember Get started npm install -g @mem0/cli Open source 👇
0:36

Introducing mem0 CLI 🚀 Give your agents memory from the terminal - add, search, and retrieve memory - remember agents + developers's preference - agent-first, JSON schema-driven We built mem0 CLI to help agents remember Get started npm install -g @mem0/cli Open source 👇

Taranjeet

20,443 просмотров • 2 месяцев назад

🔗 Announcing LangChain OSS Skills LangChain has the most popular frameworks for building AI agents — and now your coding agent can be an expert in it. We're excited to release the first iteration of LangChain OSS Skills, giving your agent expertise in our open source frameworks. The skills include guidance on how to use langchain, langgraph, and deepagents to effectively build agents. ➡️ Install our OSS skills for your coding agent here: ➡️ Read more:
0:43

🔗 Announcing LangChain OSS Skills LangChain has the most popular frameworks for building AI agents — and now your coding agent can be an expert in it. We're excited to release the first iteration of LangChain OSS Skills, giving your agent expertise in our open source frameworks. The skills include guidance on how to use langchain, langgraph, and deepagents to effectively build agents. ➡️ Install our OSS skills for your coding agent here: ➡️ Read more:

LangChain OSS

65,840 просмотров • 3 месяцев назад

Polly is our AI assistant built directly into LangSmith to help you debug, analyze, and improve your agents — now generally available. Now, Polly lives on every page of LangSmith, remembers your full session as you navigate, and can take action to update prompts, compare experiments, write evaluators, and more. Read the blog: See the docs: Try Polly in LangSmith:
2:05

Polly is our AI assistant built directly into LangSmith to help you debug, analyze, and improve your agents — now generally available. Now, Polly lives on every page of LangSmith, remembers your full session as you navigate, and can take action to update prompts, compare experiments, write evaluators, and more. Read the blog: See the docs: Try Polly in LangSmith:

LangChain

12,595 просмотров • 2 месяцев назад

Introducing: Superset CLI 🎮 Drive Superset from within the terminal, or sit back and let your agents do it 🏖️ Create workspaces, spin up agents, edit tasks, etc. All through the terminal, updates the app in real-time. Works with automation and remote workspaces. Teach it to your agents with skills: npx skills add Available now: brew install superset-sh/tap/superset
1:16

Introducing: Superset CLI 🎮 Drive Superset from within the terminal, or sit back and let your agents do it 🏖️ Create workspaces, spin up agents, edit tasks, etc. All through the terminal, updates the app in real-time. Works with automation and remote workspaces. Teach it to your agents with skills: npx skills add Available now: brew install superset-sh/tap/superset

Superset

19,847 просмотров • 1 месяц назад

Introducing the Firecrawl Skill + CLI for Agents 🔥 Agents like Claude Code, Codex, and OpenCode need live quality context from the web. The CLI pulls web content to local files with bash-powered search for the highest token efficiency. $ npx skills add firecrawl/cli
0:24

Introducing the Firecrawl Skill + CLI for Agents 🔥 Agents like Claude Code, Codex, and OpenCode need live quality context from the web. The CLI pulls web content to local files with bash-powered search for the highest token efficiency. $ npx skills add firecrawl/cli

Firecrawl

86,971 просмотров • 4 месяцев назад

Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail
3:02

Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail

LangChain

33,192 просмотров • 11 месяцев назад

LangSmith Agent Builder is generally available 🎉 It’s surprisingly easy to build agents now. Even a VC can do it…👇 Try it free: Read the announcement:
1:44

LangSmith Agent Builder is generally available 🎉 It’s surprisingly easy to build agents now. Even a VC can do it…👇 Try it free: Read the announcement:

LangChain

109,724 просмотров • 5 месяцев назад

🔗 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

41,016 просмотров • 5 месяцев назад

AI agents can now autonomously discover and install Marketplace integrations using the Vercel CLI. ▲ ~/ 𝚗𝚙𝚡 𝚜𝚔𝚒𝚕𝚕𝚜 𝚊𝚍𝚍 𝚟𝚎𝚛𝚌𝚎𝚕/𝚟𝚎𝚛𝚌𝚎𝚕 --𝚜𝚔𝚒𝚕𝚕 𝚟𝚎𝚛𝚌𝚎𝚕-𝚌𝚕𝚒 Install the CLI skill and ask your coding agent to integrate a Vercel Marketplace product.
0:25

AI agents can now autonomously discover and install Marketplace integrations using the Vercel CLI. ▲ ~/ 𝚗𝚙𝚡 𝚜𝚔𝚒𝚕𝚕𝚜 𝚊𝚍𝚍 𝚟𝚎𝚛𝚌𝚎𝚕/𝚟𝚎𝚛𝚌𝚎𝚕 --𝚜𝚔𝚒𝚕𝚕 𝚟𝚎𝚛𝚌𝚎𝚕-𝚌𝚕𝚒 Install the CLI skill and ask your coding agent to integrate a Vercel Marketplace product.

Vercel Developers

209,857 просмотров • 3 месяцев назад

📊 Learn how to observe & evaluate agents on LangChain Academy 📊 Testing applications is essential to the development lifecycle, but LLM systems are non-deterministic – you can’t always predict how they will behave. Add multi-turn interactions and tool-calling agents, and testing agents becomes even more complex than traditional software testing 😵‍💫 To address this challenge, LangSmith provides a comprehensive platform for agent engineering that helps teams use live production data for continuous testing and improvement 🚀 In our quickstart course, LangSmith Essentials, you’ll learn how to observe, evaluate, and deploy your agent in less than 30 minutes. Enroll for free ➡️
1:44

📊 Learn how to observe & evaluate agents on LangChain Academy 📊 Testing applications is essential to the development lifecycle, but LLM systems are non-deterministic – you can’t always predict how they will behave. Add multi-turn interactions and tool-calling agents, and testing agents becomes even more complex than traditional software testing 😵‍💫 To address this challenge, LangSmith provides a comprehensive platform for agent engineering that helps teams use live production data for continuous testing and improvement 🚀 In our quickstart course, LangSmith Essentials, you’ll learn how to observe, evaluate, and deploy your agent in less than 30 minutes. Enroll for free ➡️

LangChain

13,464 просмотров • 5 месяцев назад

Blackbox Agent through the CLI got new some SKILLs design make sure to use `/skills` to give the agent more specialization on the tasks you want
0:47

Blackbox Agent through the CLI got new some SKILLs design make sure to use `/skills` to give the agent more specialization on the tasks you want

BLACKBOX AI

56,614 просмотров • 5 месяцев назад

Today we're open sourcing a technical preview of the GitHub Copilot CLI SDK. Build agents with custom tools in Go, Python, TypeScript, and C#. Built on the same agent loop that powers the Copilot CLI and GitHub Coding Agent. Supports BYOK, and any model. Here is the Copilot CLI driving Excel:
0:29

Today we're open sourcing a technical preview of the GitHub Copilot CLI SDK. Build agents with custom tools in Go, Python, TypeScript, and C#. Built on the same agent loop that powers the Copilot CLI and GitHub Coding Agent. Supports BYOK, and any model. Here is the Copilot CLI driving Excel:

Evan Boyle

184,357 просмотров • 5 месяцев назад

Introducing LangSmith Fleet: an enterprise workspace for creating, using, and managing your fleet of agents. Fleet agents have their own memory, access to a collection of tools and skills, and can be exposed through the communication channels your team uses every day. Fleet includes: → Agent identity and credential management with “Claws” and “Assistants” → Sharing and permissions to control who can run, clone, and edit (just like Google Docs) → Custom Slack bots so each agent has its own identity in Slack Try Fleet: Read the announcement:
1:57

Introducing LangSmith Fleet: an enterprise workspace for creating, using, and managing your fleet of agents. Fleet agents have their own memory, access to a collection of tools and skills, and can be exposed through the communication channels your team uses every day. Fleet includes: → Agent identity and credential management with “Claws” and “Assistants” → Sharing and permissions to control who can run, clone, and edit (just like Google Docs) → Custom Slack bots so each agent has its own identity in Slack Try Fleet: Read the announcement:

LangChain

148,506 просмотров • 2 месяцев назад

Announcing the Agent Store! It's npm for agents: - Publish specialized agents - Run them by CLI or SDK - Compose them to build higher level agents This is the end game for agents 🧠
3:47

Announcing the Agent Store! It's npm for agents: - Publish specialized agents - Run them by CLI or SDK - Compose them to build higher level agents This is the end game for agents 🧠

James Grugett

21,913 просмотров • 9 месяцев назад

🚀 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 просмотров • 3 месяцев назад

Introducing: Clanker CLI and Skills we've launched a new clanker cli and skills so all of your clankers can clank clankers more easily. for the cli, run: npm install -g clanker-sdk clanker-sdk deploy to add the skill, simply tell your agent to add it at we're excited to keep supporting more agentic use cases to clanker launching and trading. clank clank 🫡
0:24

Introducing: Clanker CLI and Skills we've launched a new clanker cli and skills so all of your clankers can clank clankers more easily. for the cli, run: npm install -g clanker-sdk clanker-sdk deploy to add the skill, simply tell your agent to add it at we're excited to keep supporting more agentic use cases to clanker launching and trading. clank clank 🫡

clanker

18,554 просмотров • 3 месяцев назад

We’ve added a CLI for Claude Platform to make every API endpoint runnable from your terminal. Call the Messages API, stand up Claude Managed Agents, pipe results straight into your shell. The ant CLI is well understood by coding agents (Claude Code) using the claude-api skill.
0:30

We’ve added a CLI for Claude Platform to make every API endpoint runnable from your terminal. Call the Messages API, stand up Claude Managed Agents, pipe results straight into your shell. The ant CLI is well understood by coding agents (Claude Code) using the claude-api skill.

ClaudeDevs

1,197,594 просмотров • 13 дней назад