Hi, I'm Sam and I'm a product manager at Langchain and today I'm going to give you a brief tour of the Langmith agent builder which we're launching as a public beta this week. Uh so these are the agents that I have available for myself in production right now. Uh you can see my support email filter assistant, my daily calendar briefer.Uh, the one I'm going to be showing today is the linear issue manager, which monitors a Slack channel that the engineering team that builds the agent builder spends most of it ...

Hey, it's Jacob from Linkchain. So, we just released Linksmith Agent Builder in public beta. Agent Builder allows you to build production grade agents without writing any code.And over the last month or so, we've seen people build a ton of different agents. And one of the most popular ones is an email assistant. You know, an agent that can go read your emails, help prioritize the right ones, categorize and label, and then maybe draft responses for your most important messages.So, over the next few minutes, ...

Hey, it's Jacob from LChain. Now, we just released Linksmith Agent Builder in public beta. And over the last month or so, since we first released the product in private preview, we've seen people build thousands of different agents.And one of the most common use cases we've seen is building an email assistant. You know, something that can read through your emails, help prioritize draft responses, things like that. And so, over the next few minutes, I want to show how you can build your own email assistant u ...

Product Overview - Langsmith Agent Builder is a new no-code agent experience that allows users to build and describe agents in natural language, incorporating memory for adaptation and learning [1] - The core of building an agent lies in crafting a detailed prompt, with Langsmith Agent Builder providing tools like metaprompting to assist in this process [2][3] - Agents can remember interactions and update prompts in a memory bank, enabling continuous learning and adaptation [4] Key Features - Metaprompting helps users refine their initial ideas into detailed prompts through follow-up questions [3][6] - Agents can connect to internal tools or APIs with proper Oauth and credentials [8] - A test chat feature allows users to debug agents by pausing execution before tools are used [10] - Memory enables agents to update instructions based on interactions, allowing them to learn and adapt over time [11][12][14] - The agent inbox allows users to monitor agents, receive notifications, and provide assistance when needed [18] Agent Management - Users can monitor agent threads, categorized as idle, busy, interrupted, or errored, to manage agent performance [16] - The agent builder is not a visual workflow builder but focuses on agent autonomy and memory [19] Example Use Case - A daily briefer agent can be created to read a user's calendar and send a report via Slack at a specified time [5][7] - The agent can be instructed to perform specific tasks, such as writing a poem, and will update its memory to incorporate these instructions [11][12][13]