Video wird geladen...

Video konnte nicht geladen werden

Beim Laden dieses Videos ist ein Problem aufgetreten. Dies könnte an einem vorübergehenden Netzwerkproblem liegen oder das Video ist möglicherweise nicht verfügbar.

Build a loan underwriting agent workflow in ~5 mins 💵🤖 (No code, just English) I built an agentic workflow that can process incoming PDFs of financial statements: checking statements, bank statements, brokerage accounts, and extract/normalize the financials in each source of data. I did this by specifying the schemas... show more

Jerry Liu

70,975 subscribers

30,015 Aufrufe • vor 6 Monaten •via X (Twitter)

Wissenschaft & Technologie Finanzen

Anya Rossi• Live Now

Private livecam show

0 Kommentare

Keine Kommentare verfügbar

Kommentare vom Original-Post werden hier angezeigt

Ähnliche Videos

A Web-Based, Agentic ComfyUI-Style Builder for 3D Okay, this is actually pretty interesting. I’ve been testing Flow, a new tool from 3DAIStudio . It’s basically a web-based, ComfyUI-style workflow builder made around 3D, with specialized nodes, logic nodes, and an AI agent that can help build the workflow for you. I tested it across a few different pipelines, models, and node setups — and it works surprisingly well. Full review + results in the video 👇

A Web-Based, Agentic ComfyUI-Style Builder for 3D Okay, this is actually pretty interesting. I’ve been testing Flow, a new tool from 3DAIStudio . It’s basically a web-based, ComfyUI-style workflow builder made around 3D, with specialized nodes, logic nodes, and an AI agent that can help build the workflow for you. I tested it across a few different pipelines, models, and node setups — and it works surprisingly well. Full review + results in the video 👇

Stefan 3D AI

10,142 Aufrufe • vor 17 Tagen

“Intelligent Document Processing” 📑🧪 as an industry is gone . With our latest release this week, *anyone* can build and deploy a specialized document agent in seconds ⚡️🤖, and customize the steps via code. Let’s take a tour through our invoice processing and contract matching agent: given an invoice, extract out vendor details and line items, and match it against the corresponding MSA with the vendor. 1️⃣ Put in your name and API key, and deploy the agent in 5 seconds 2️⃣ Upload some sample contracts and invoices, and watch the workflow run. 3️⃣ If you want to customize it, you can clone our source repository, modify the internals, and deploy the agent! It is both more accurate and more customizable than existing IDP solutions. With coding agents today, the ease of use is equivalent too. Click on the “agents” tab in LlamaCloud to check it out! Invoice processing repo: LlamaAgents Docs:

“Intelligent Document Processing” 📑🧪 as an industry is gone . With our latest release this week, anyone can build and deploy a specialized document agent in seconds ⚡️🤖, and customize the steps via code. Let’s take a tour through our invoice processing and contract matching agent: given an invoice, extract out vendor details and line items, and match it against the corresponding MSA with the vendor. 1️⃣ Put in your name and API key, and deploy the agent in 5 seconds 2️⃣ Upload some sample contracts and invoices, and watch the workflow run. 3️⃣ If you want to customize it, you can clone our source repository, modify the internals, and deploy the agent! It is both more accurate and more customizable than existing IDP solutions. With coding agents today, the ease of use is equivalent too. Click on the “agents” tab in LlamaCloud to check it out! Invoice processing repo: LlamaAgents Docs:

Jerry Liu

34,480 Aufrufe • vor 7 Monaten

Here is a step-by-step introduction to building a workflow with a custom AI agent that uses MCP. I explain every component in the video: 1. Building the MCP server 2. Building the agent and an MCP client 3. Building a workflow that uses the agent The goal is simple: Generate a dialogue between two people and make one yell and the other answer with sarcasm. Kestra is sponsoring this video. They are an open-source orchestration platform (repo link below), and I used them to build the workflow that connects every component.

Here is a step-by-step introduction to building a workflow with a custom AI agent that uses MCP. I explain every component in the video: 1. Building the MCP server 2. Building the agent and an MCP client 3. Building a workflow that uses the agent The goal is simple: Generate a dialogue between two people and make one yell and the other answer with sarcasm. Kestra is sponsoring this video. They are an open-source orchestration platform (repo link below), and I used them to build the workflow that connects every component.

Santiago

51,527 Aufrufe • vor 1 Jahr

How to build an agentic workflow step by step. This is a 9-minute video where I'll build an application that will do the following: 1. Turn invoices into text (JPG, PNG, PDF...) 2. Extract their amount and due date 3. Format the date 4. Augment the data using tools 5. Craft a message using the above information 6. Send myself an email with this information This workflow uses and GPT4o. At this point, not automating all of the boring tasks around you is absolute negligence.

How to build an agentic workflow step by step. This is a 9-minute video where I'll build an application that will do the following: 1. Turn invoices into text (JPG, PNG, PDF...) 2. Extract their amount and due date 3. Format the date 4. Augment the data using tools 5. Craft a message using the above information 6. Send myself an email with this information This workflow uses and GPT4o. At this point, not automating all of the boring tasks around you is absolute negligence.

Santiago

92,721 Aufrufe • vor 1 Jahr

I made an agent using GitHub Copilot SDK to help me become a running influencer🏃🏾‍♀️✨ Here's the Python code you can use to build an agent that uses MCP and Skills to: - draft and send email - design pitch decks - make a website Copilot CLI then runs all of this in a workflow🐍

I made an agent using GitHub Copilot SDK to help me become a running influencer🏃🏾‍♀️✨ Here's the Python code you can use to build an agent that uses MCP and Skills to: - draft and send email - design pitch decks - make a website Copilot CLI then runs all of this in a workflow🐍

Marlene Mhangami

34,502 Aufrufe • vor 6 Monaten

$Claude Code now has Agent Teams Multiple Claude sessions working in parallel, coordinating through shared tasks and messaging each other. Enable it by adding this to your settings.json: { "env": { "CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS":"1" } } Just describe the team you want in plain English Shift+↑ to check each teammate's progress This + worktrees = workflow multiplier$

Claude Code now has Agent Teams Multiple Claude sessions working in parallel, coordinating through shared tasks and messaging each other. Enable it by adding this to your settings.json: { "env": { "CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS":"1" } } Just describe the team you want in plain English Shift+↑ to check each teammate's progress This + worktrees = workflow multiplier

Daniel San

83,291 Aufrufe • vor 5 Monaten

Building “RAG 2.0” is just making Claude Code running over your filesystem 🤖🗂️ To make this work well, you need to solve three things 1️⃣ Virtualize your filesystem to prevent the agent from messing stuff up. AgentFS by Turso is a nice example of how you can give the agent access to a copy of all your files without messing up your raw data. 2️⃣ Parse unstructured documents like PDFs, pptx, Word into an LLM-ready format. Agentic OCR solutions like LlamaParse can help here 3️⃣ Creating an agentic loop with human-in-the-loop. If you want to control the agent implementation instead of using Claude Code out of the box, you can use LlamaIndex 🦙 workflows to help orchestrate these long-running agent tasks. Shoutout Clelia Bertelli (🦙/acc), check it out! Blog: Repo:

Building “RAG 2.0” is just making Claude Code running over your filesystem 🤖🗂️ To make this work well, you need to solve three things 1️⃣ Virtualize your filesystem to prevent the agent from messing stuff up. AgentFS by Turso is a nice example of how you can give the agent access to a copy of all your files without messing up your raw data. 2️⃣ Parse unstructured documents like PDFs, pptx, Word into an LLM-ready format. Agentic OCR solutions like LlamaParse can help here 3️⃣ Creating an agentic loop with human-in-the-loop. If you want to control the agent implementation instead of using Claude Code out of the box, you can use LlamaIndex 🦙 workflows to help orchestrate these long-running agent tasks. Shoutout Clelia Bertelli (🦙/acc), check it out! Blog: Repo:

Jerry Liu

55,620 Aufrufe • vor 7 Monaten

✨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 ➡️

✨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 6 Monaten

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:

Andrew Ng

105,343 Aufrufe • vor 1 Jahr

Introducing FlowMaker 🌊🤖 A fully open-source, low-code way of building custom agent workflows. Build agents via a drag and drop interface, run it directly in the app, and also directly export it into a deeply custom workflow backed by LlamaIndex 🦙.TS. It’s a fantastic visual tool to help you get started with agents but also gives you full customizability to build the deepest, most advanced workflows, since everything is backed by code. There’s a lot of great low-code agent tools already, but this is a fully-open source template that you can use or clone/customize for your own needs. It was a fun project by Laurie Voss and is intended to give users an easy-on ramp onto our powerful agent orchestration tooling. Also integrates with LlamaCloud in case you want to integrate your own knowledge base into your agent. FlowMaker app: FlowMaker Repo: LlamaCloud:

Introducing FlowMaker 🌊🤖 A fully open-source, low-code way of building custom agent workflows. Build agents via a drag and drop interface, run it directly in the app, and also directly export it into a deeply custom workflow backed by LlamaIndex 🦙.TS. It’s a fantastic visual tool to help you get started with agents but also gives you full customizability to build the deepest, most advanced workflows, since everything is backed by code. There’s a lot of great low-code agent tools already, but this is a fully-open source template that you can use or clone/customize for your own needs. It was a fun project by Laurie Voss and is intended to give users an easy-on ramp onto our powerful agent orchestration tooling. Also integrates with LlamaCloud in case you want to integrate your own knowledge base into your agent. FlowMaker app: FlowMaker Repo: LlamaCloud:

Jerry Liu

20,413 Aufrufe • vor 1 Jahr

I just watched an AI agent operate my Mac like a real human. This AI agent responded to candidates' emails and scheduled Zoom meetings, all from a plain English prompt. Skip the Zapier spaghetti. This is agentic AI; you need to know about:

I just watched an AI agent operate my Mac like a real human. This AI agent responded to candidates' emails and scheduled Zoom meetings, all from a plain English prompt. Skip the Zapier spaghetti. This is agentic AI; you need to know about:

Shruti

36,489 Aufrufe • vor 1 Jahr

Internally at NVIDIA, we use cuOpt based agentic workflows with agent skills to optimize our supply chains. Since it’s open source, you can too. With optimizations ready in minutes instead of weeks, the workflow uses multi-agent LangChain Deep agent orchestration and GPU-accelerated solvers to turn natural language into optimized decisions. Spin it up instantly with a Brev Launchable (preconfigured GPU environment) and grab free developer credits while they last.

Internally at NVIDIA, we use cuOpt based agentic workflows with agent skills to optimize our supply chains. Since it’s open source, you can too. With optimizations ready in minutes instead of weeks, the workflow uses multi-agent LangChain Deep agent orchestration and GPU-accelerated solvers to turn natural language into optimized decisions. Spin it up instantly with a Brev Launchable (preconfigured GPU environment) and grab free developer credits while they last.

NVIDIA AI

22,828 Aufrufe • vor 2 Monaten

"You can't VibeCode Complex Apps" they said. That is until "VAAPs" became a thing. You can vibecode your frontend like mzulali did here, and then plug in an n8n agent as the backend. All you have to do is use a webhook to connect them. Ask the vibecode to send data to your n8n webhook url and then await its response. Make sure that the trigger of your agent workflow is a webhook. His workflow was an agent that has access to fal workflows... Each tool is like a different creative "skill" that the AI agent can call when necessary. This will get much easier to create when VibeCode releases their official n8n integration.

"You can't VibeCode Complex Apps" they said. That is until "VAAPs" became a thing. You can vibecode your frontend like mzulali did here, and then plug in an n8n agent as the backend. All you have to do is use a webhook to connect them. Ask the vibecode to send data to your n8n webhook url and then await its response. Make sure that the trigger of your agent workflow is a webhook. His workflow was an agent that has access to fal workflows... Each tool is like a different creative "skill" that the AI agent can call when necessary. This will get much easier to create when VibeCode releases their official n8n integration.

Learn to VibeCode

18,981 Aufrufe • vor 1 Jahr

Anyone can build an agent. But to build a trustworthy agent at enterprise scale that is durable, long-running, optimized, contextually aware, and autonomous, the right infrastructure is required. At DevCon 6 we introduced the Agent Stack, the culmination of learnings gathered over years of agentic implementations. Orchestrator, Agent Engine, Agent SDK, Agent Builder, Agent Manager, AIP Evolve, SuperRepo, and so much more. All built on the Ontology, to power agents that actually work in production.

Anyone can build an agent. But to build a trustworthy agent at enterprise scale that is durable, long-running, optimized, contextually aware, and autonomous, the right infrastructure is required. At DevCon 6 we introduced the Agent Stack, the culmination of learnings gathered over years of agentic implementations. Orchestrator, Agent Engine, Agent SDK, Agent Builder, Agent Manager, AIP Evolve, SuperRepo, and so much more. All built on the Ontology, to power agents that actually work in production.

Palantir

80,948 Aufrufe • vor 14 Tagen

I vibe-coded an AI agent for making presentations 🤖🖼️ - accessible to everyone and open-source! You can upload both your context files, as well as a style template (a file that captures the style of the presentation you want to create). Then you launch a prompt and watch the agent one-shot your presentation. After the presentation is generated, you can edit the text inline, chat with the agent to add/modify/delete slides, and export to Powerpoint or PDF. Built with Claude Code, powered by Claude Agent SDK + LlamaParse. Hosted on Vercel/Render. To use it, you do need to specify your LlamaCloud API key and Anthropic API key (see below). App: Repo: Sign up to LlamaCloud:

I vibe-coded an AI agent for making presentations 🤖🖼️ - accessible to everyone and open-source! You can upload both your context files, as well as a style template (a file that captures the style of the presentation you want to create). Then you launch a prompt and watch the agent one-shot your presentation. After the presentation is generated, you can edit the text inline, chat with the agent to add/modify/delete slides, and export to Powerpoint or PDF. Built with Claude Code, powered by Claude Agent SDK + LlamaParse. Hosted on Vercel/Render. To use it, you do need to specify your LlamaCloud API key and Anthropic API key (see below). App: Repo: Sign up to LlamaCloud:

Jerry Liu

21,073 Aufrufe • vor 6 Monaten

New short course: Serverless Agentic Workflows with Amazon Bedrock. Learn to build and deploy serverless agents in this course created with Amazon Web Services and taught by Mike G Chambers, a Senior Developer Advocate at AWS specializing in GenAI. (Disclosure: I serve on Amazon's board.) Generative AI applications are becoming more complex, sophisticated, and agentic. Agentic applications have workloads that can be hard to predict in advance -- for example, what tools will it decide to call? -- and a serverless architecture helps you efficiently providing on-demand resources. This course teaches you to build and deploy a serverless agentic application. You’ll learn to create agents with tools, code execution, and guardrails, and build responsible agents for business use cases: - Build a customer service bot for a fictional tea mug business that can answering questions, retrieve information, and process orders. - Connect your customer service agent to a CRM to get customer info and log support tickets in real-time. - Explore how you invoke the agent, and see the trace to review the agent’s thought process and observation loop until it reaches its final output. - Attach a code interpreter to your agent, giving it the ability to perform accurate calculations by writing and running its own Python code. - Implement guardrails to prevent your agent from revealing sensitive information or using inappropriate language. By the end, you will have built a sophisticated AI agent capable of handling real-world customer support scenarios. Please sign up here!

New short course: Serverless Agentic Workflows with Amazon Bedrock. Learn to build and deploy serverless agents in this course created with Amazon Web Services and taught by Mike G Chambers, a Senior Developer Advocate at AWS specializing in GenAI. (Disclosure: I serve on Amazon's board.) Generative AI applications are becoming more complex, sophisticated, and agentic. Agentic applications have workloads that can be hard to predict in advance -- for example, what tools will it decide to call? -- and a serverless architecture helps you efficiently providing on-demand resources. This course teaches you to build and deploy a serverless agentic application. You’ll learn to create agents with tools, code execution, and guardrails, and build responsible agents for business use cases: - Build a customer service bot for a fictional tea mug business that can answering questions, retrieve information, and process orders. - Connect your customer service agent to a CRM to get customer info and log support tickets in real-time. - Explore how you invoke the agent, and see the trace to review the agent’s thought process and observation loop until it reaches its final output. - Attach a code interpreter to your agent, giving it the ability to perform accurate calculations by writing and running its own Python code. - Implement guardrails to prevent your agent from revealing sensitive information or using inappropriate language. By the end, you will have built a sophisticated AI agent capable of handling real-world customer support scenarios. Please sign up here!

Andrew Ng

81,048 Aufrufe • vor 1 Jahr

A 100% open-source alternative to n8n! Sim is a drag-and-drop open-source platform to build and deploy Agentic workflows. - Runs 100% locally - Works with any local LLM I used it to build a finance assistance app & connected it to Telegram in minutes. The workflow is simple: - You ask a finance question through Telegram - An Intent Classifier figures out if it's finance-related - If not, you get a polite redirect - If yes, the Finance Agent kicks in Here's what's happening under the hood: The Finance Agent uses Firecrawl for web searches and accesses stock data via Alpha Vantage's API through MCP servers. A Response Agent compiles the info and delivers it. In Sim, every tool or agent you need is available as a block. Just drag them onto the canvas and connect them. Sim agents also support integration with MCP, which is exactly what we did to connect our agent with Alpha Vantage's API. And it's simple to extend. If you want to track crypto or need portfolio analysis, you can just add another Agent. Sim allows easy feature additions without disrupting existing functionality. I have shared the link to Sim's official, open-source GitHub repo in the replies!

A 100% open-source alternative to n8n! Sim is a drag-and-drop open-source platform to build and deploy Agentic workflows. - Runs 100% locally - Works with any local LLM I used it to build a finance assistance app & connected it to Telegram in minutes. The workflow is simple: - You ask a finance question through Telegram - An Intent Classifier figures out if it's finance-related - If not, you get a polite redirect - If yes, the Finance Agent kicks in Here's what's happening under the hood: The Finance Agent uses Firecrawl for web searches and accesses stock data via Alpha Vantage's API through MCP servers. A Response Agent compiles the info and delivers it. In Sim, every tool or agent you need is available as a block. Just drag them onto the canvas and connect them. Sim agents also support integration with MCP, which is exactly what we did to connect our agent with Alpha Vantage's API. And it's simple to extend. If you want to track crypto or need portfolio analysis, you can just add another Agent. Sim allows easy feature additions without disrupting existing functionality. I have shared the link to Sim's official, open-source GitHub repo in the replies!

Avi Chawla

115,578 Aufrufe • vor 10 Monaten

We built an AI agent that lets you vibe-code document extraction - high accuracy and citations over the most complex documents. Our latest release lets you upload documents as context. All you then have to do is describe what you want extracted in natural language. 💡 Our agent will then read the document with file tools to infer the right schema, validation rules, and other pre/postprocessing logic. ✅ It will give you back a workflow that can extract over thousands/millions of documents at scale. You can still of course review and edit every output before approving. Stop handling paperwork manually; just upload files, describe your task, and let our agent handle the rest. Our vision for LlamaAgents is to provide the most advanced and easy-to-use way for you to orchestrate document work. Walkthrough: Check it out: If you’re interested in reducing the operational burden of document extraction (invoices, claims, onboarding forms), come talk to us!

We built an AI agent that lets you vibe-code document extraction - high accuracy and citations over the most complex documents. Our latest release lets you upload documents as context. All you then have to do is describe what you want extracted in natural language. 💡 Our agent will then read the document with file tools to infer the right schema, validation rules, and other pre/postprocessing logic. ✅ It will give you back a workflow that can extract over thousands/millions of documents at scale. You can still of course review and edit every output before approving. Stop handling paperwork manually; just upload files, describe your task, and let our agent handle the rest. Our vision for LlamaAgents is to provide the most advanced and easy-to-use way for you to orchestrate document work. Walkthrough: Check it out: If you’re interested in reducing the operational burden of document extraction (invoices, claims, onboarding forms), come talk to us!

Jerry Liu

20,857 Aufrufe • vor 5 Monaten

So Google has just released its own agent builder?! You can now add the agent block in Google Opal and "program it" in plain English. And it has natively: - Tool call (with Nano Banana, Veo, web search...) - Memory to save infos between sessions - Conditional logic Probably the easiest way to build AI agents I've seen so far.

So Google has just released its own agent builder?! You can now add the agent block in Google Opal and "program it" in plain English. And it has natively: - Tool call (with Nano Banana, Veo, web search...) - Memory to save infos between sessions - Conditional logic Probably the easiest way to build AI agents I've seen so far.

Paul Couvert

560,884 Aufrufe • vor 5 Monaten