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🚀 LangSmith Agent Builder is now available in Public Beta Now anyone can create production ready agents without writing code, just chat. Agent Builder guides you from initial idea to deployed agent, creating detailed prompts, selecting required tools, and even creating subagents. Our Beta release also includes: 🧰 Bring... show more

LangChain

267,591 subscribers

37,866 views • 10 months ago •via X (Twitter)

Education Science & Technology Finance

Anya Rossi• Live Now

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16 Comments

Warden / Halo10 months ago

Just in time for Warden Studio release 🙌

Thomas Taylor10 months ago

no code agents are officially here from the langchain team!

Alin10 months ago

Spicy take: Every agent framework claims "no-code" or "just chat" but 90% of real use cases still need someone who can code to fix hallucinations. You're not eliminating engineers, you're creating customer-support tickets disguised as agent errors.

TechAI10 months ago

Huge step forward — building production-ready agents without code is a game changer. Excited to try this out! #AI #TechAI

SamusDevyjr 💻🤔10 months ago

Perfect timing. 🤩I’m building an AI-powered resume tool + local second brain, and this kind of guided agent flow will remove a ton of early overhead.

Atoms.Dev10 months ago

Solid move making agent creation public! No-code access gonna empower so many more builders to experiment. Curious how the prompt crafting flows.

AI/ACC10 months ago

No-code is a founder distraction. The real levers are P&L mapping, speed, and complexity. Stop building agent toys; build value.

manuel7 months ago

Hey @clanker_world , deploy a token on base named LangSmith Ticker LangSmith

Devticks10 months ago

No-code agents, just chat!

Buur Diendé ⭐️⭐️ 🇸🇳🇩🇿🇫🇷10 months ago

🤩 Is there a way to use built agent in a nextjs project ?

AI/ACC10 months ago

Easy construction is tuition. The only signal is a hard PnL map tied to closed-loop value capture, measured in unit payback and latency.

Nikhil Kulkarni10 months ago

oh ok amazing! great way for non techies to get started in the ecosystem

TechX Global10 months ago

Huge step forward. Making production-ready agents accessible without code is exactly what the ecosystem needed.

diamond10 months ago

In the tools list, there’s no option to add an MCP.

LangChain10 months ago

@BRAKING_NEWS_AI Thanks for checking it out - you can configure an MCP server for Agent Builder in your LangSmith workspace. Docs here:

Himanshu Kumar10 months ago

Wow, that's fantastic, LangChain! But will these no-code agents truly understand the nuances, you know?

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LangChain

24,885,978 views • 7 months ago

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:

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LangChain

111,687 views • 8 months ago

✨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 ➡️

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LangChain

26,513 views • 8 months ago

🚀 LangSmith Agent Builder is GA – and we’re moving fast Agent Builder lets you build an agent with a simple prompt. But sometimes you want something that’s ready to go. Today we’re introducing the Agent Builder Template Library: ready-to-deploy agents built with the companies who know their domains best. Templates include: Tavily: competitor intelligence PagerDuty: on-call triage Box: document intake review +more Supports: Gmail, Google Calendar, Slack, Linear, Pylon, GitHub, LinkedIn, X, Tavily, Exa + any app with an MCP server 👉 Try Agent Builder: 📣 Read the announcement:

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LangChain

46,037 views • 8 months ago

AI Agents can now connect to 100,000+ APIs instantly. Postman's AI Agent builder can turn any API into an MCP server in seconds without writing a single line of Code. You can use it in Claude, Cursor, Windsurf and other AI tools.

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Shubham Saboo

79,818 views • 1 year ago

Our MCP Marketplace is now in Beta. Introducing Shopify for AI Agents: no-code creation + community extensibility. Create utility agents by assembling abilities from SendAI, Graffle, & Genopets - WHITTAKR Agent Era community. Or deploy your own via our simple MCP Server tools. More 🧵

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Elite Agents (EAs)

68,938 views • 1 year ago

Introducing LangSmith Agent Builder 🤖🧱 A true agent building experience (not workflows!!), all through a simple natural language interface. Describe your agent to "build" it, then interact with it via chat, or add an automatic trigger. Connect your agents to any MCP server, or use our builtin tools. These agents also come with builtin memory, so they can optimize themselves over time, both ambiently, and from user feedback! Sign up for the waitlist today:

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Brace

30,846 views • 11 months ago

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:

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LangChain

149,127 views • 6 months ago

🤖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):

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LangChain

27,135 views • 8 months ago

Opus 5.5 makes this AI stack look f…cking illegal 10 GitHub repos for building everything around the model 01 zen-mcp-server ▸ → your agent debates Gemini, GPT and local models mid-task 02 claude-context ▸ → semantic code search so the agent stops grepping blind 03 wshobson/agents ▸ → a roster of subagents, each with one narrow job 04 mcp-agent ▸ → workflow patterns built around MCP tools, not around chat 05 Backlog.md ▸ → tasks live in git, so the agent and you read the same board 06 Claude Code Development Kit ▸ → hooks, subagents and MCP wired for context at scale 07 agent-rules ▸ → shared guardrails the agent inherits in every repo 08 Agent Skills ▸ → one file that teaches the agent a job, portable across tools 09 agent-scan ▸ → scans your agents, MCP servers and skills for what leaks 10 awesome-claude-code-toolkit ▸ → the map: agents, skills, commands, hooks, MCP configs the architecture: rules → context → subagents → tools → state → review → scan I'd split the stack like this: context: claude-context → Development Kit work: wshobson/agents → mcp-agent → zen-mcp-server state: Backlog.md safety: agent-rules → Agent Skills → agent-scan everyone posts the SDK and the CLI the layer that decides whether your agent survives a week is this one the model is one folder in the stack ⭣

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rody

11,358 views • 1 day ago

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

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LangChain

33,192 views • 1 year ago

Subagents have arrived in Gemini CLI! 🤖🚀 Create your own custom subagents in Gemini CLI! Subagents are specialized, expert agents that the main agent can delegate work to. 📦- Subagents have their own set of tools, MCP servers, system instructions, and context window. 🏷️- Use Agent to explicitly delegate to a subagent 🧹- Keeps the main context window clean ⚡️- Speed up work by running agents in parallel Read more in the launch blog below 👇

Subagents have arrived in Gemini CLI! 🤖🚀 Create your own custom subagents in Gemini CLI! Subagents are specialized, expert agents that the main agent can delegate work to. 📦- Subagents have their own set of tools, MCP servers, system instructions, and context window. 🏷️- Use Agent to explicitly delegate to a subagent 🧹- Keeps the main context window clean ⚡️- Speed up work by running agents in parallel Read more in the launch blog below 👇

Jack Wotherspoon

222,206 views • 5 months ago

🔗 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 ➡️

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LangChain

41,214 views • 9 months ago

Your business is about to run itself. Razorpay Agent Studio is now rolling out. Build your own AI agents for: Recon. Ops. Disputes. Drop-offs. And more. The world’s first agent platform built on payments infrastructure. Built in partnership with Anthropic What’s live: → 8+ agents live today → 7+ connectors (ElevenLabs, Tally, Sarvam, WhatsApp, Slack, and more) → Build your own agent (beta) → Strong guardrails and evals Already in motion: → 6 launch partners, 2 agent partners → Builder Day → May 9 Early access & details →

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Harshil Mathur

19,773 views • 6 months ago

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BuildShip

75,958 views • 3 months ago

🚀 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 to the CLI, agents are able to do it all natively through the terminal, where they're most comfortable. Try out LangSmith Skills and the CLI with your own coding agents! ➡️ Skills: ➡️ CLI:

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LangChain

49,662 views • 7 months ago

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:

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 views • 11 months ago

MCP connectors are now available in Basedash. Basedash already reads from your databases and SaaS tools. Now it can act on them too. Connect any MCP server (Linear, HubSpot, Slack, Resend, Notion, GitHub, your own internal one) and the Basedash agent gets new tools it can use right inside chat. Try it today.

MCP connectors are now available in Basedash. Basedash already reads from your databases and SaaS tools. Now it can act on them too. Connect any MCP server (Linear, HubSpot, Slack, Resend, Notion, GitHub, your own internal one) and the Basedash agent gets new tools it can use right inside chat. Try it today.

Basedash

11,138 views • 4 months ago

🚀 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 ➡️

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LangChain

30,744 views • 7 months ago

🔥 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 ➡️

🔥 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 views • 11 months ago