Source: Post by Rakesh Gohel on Linkedin AI Agent trends have drastically changed from 2024 to 2025 Here are the new trends driving innovation this year.... The Agentic AI field is constantly moving forward with new innovations and products. I'll share with you a few notable trends that are driving the market in 2025. Note: I've also included a few Langgraph codebooks if you want to build some of these solutions yourself. 📌 Agentic RAG - AI Agent workflow for reasoning-based real-time data retrieval and generation. - Agentic RAG is not limited to one use case but rather used in health care as well. - Used by companies like Perplexity, Harvey AI and Glean AI. 📌 Voice Agents - Intelligent agents that interact with users through natural spoken language utlizing a wide range of TTS and STTS embedding and Retrieval. - Used by companies like ElevenLabs, Cognigy, Vapi and Deepgram. 📌 AI Agent Protocols - Streamlining Multi-Agent Communication that supports communication between Agents built in different frameworks. - Used by Companies like Accenture, the top players include A2A, ACP, SLIM and others. 📌 CUA(Computer Using Agents) - AI agents that can interact with a computer the way a human does utilizing tools like a browser, CLI and even a mouse's cursor. - Used by Companies like OpenAI for their Operator, Claude's Computer Use, Runner H by H-Company and Manus AI. 📌 Coding Agents - Multi-Agents for building and debugging applications 10x faster with the help of clever tool use and LLM-based code gen. - Used by companies like Windsurf, Cursor and GitHub Copilot. 📌 Deepresearch Agents - Collaborative Multi-Agent system to build extensively researched reports from a large number of sources. - Popular products include Gemini DR, OpenAI DR and You(.)com DR. 🔗 Few Langgraph Codebooks to build some of the trending solutions 1. Agentic RAG: https://lnkd.in/gdqWyP3r 2. CUA: https://lnkd.in/gCdxpUBi 3. Deepresearch: https://lnkd.in/gexsW5qh 4. Code Gen Agents using RAG: https://lnkd.in/gDnsBFuM 📌 After months of feedback and iteration, we are finally releasing our first technical cohort, "AI Agent Engineering" 🔗 Enrol here: https://lnkd.in/gDEPcXBB If you are a business leader, we've developed frameworks that cut through the hype, including our five-level Agentic AI Progression Framework to evaluate any agent's capabilities in my latest book. 🔗 Book info: https://amzn.to/4irx6nI Save 💾 ➞ React 👍 ➞ Share ♻️ & follow for everything related to AI Agents https://www.linkedin.com/posts/rakeshgohel01_ai-agent-trends-have-drastically-changed-activity-7343981787842297858-PJkS #agenticrag #voiceagents #aiagentprotocols #cua #codingagents #deepresearchagents #langgraph #elevenlabs #cognigy #perplexity #harveyai #gleanai #openai #cursor #githubcopilot #geminidr #youcom #windsurf #a2a #acp #slim #tts #sts #rag #multiagent #aiagents #llm #browserautomation #aicoding

MGX (MetaGPT X) is a multi-agent AI platform designed to automate software development using real-world software development processes. It uses AI agents, such as a leader, product manager, architect, and engineer, to generate various development artifacts. These artifacts can include user stories, competitive analyses, requirements documents, and more, all achievable with a single line of code. The platform facilitates the creation of websites, shops, and even games. https://mgx.dev/ #MGX #MetaGPTX #MultiAgentAI #AISoftwareDevelopment #AIAgents #SoftwareAutomation #CodeGeneration #DevOps #AIProductManager #AIArchitect #SingleLineOfCode #WebsiteDevelopment #ShopDevelopment #GameDevelopment #GitHubCopilot #Tabnine #MutableAI #AIWorkflow #AutomatedSoftwareEngineering

Check this Repo out ! Shubham Saboo's GitHub repository hosts a collection of LLM Apps. These applications leverage large language models (LLMs) from various providers, including OpenAI, Anthropic, and Google, and open-source models. The apps incorporate Retrieval-Augmented Generation (RAG), AI agents, multi-agent teams, and voice agent technologies. This curated list is a valuable resource for exploring the capabilities and applications of LLMs in different contexts. #AwesomeLLMApps #LLM #LargeLanguageModels #OpenAI #Anthropic #GoogleAI #RAG #RetrievalAugmentedGeneration #AIAgents #MultiAgentTeams #VoiceAgents #GitHub #MachineLearning #NLP #AI #Langchain #LlamaIndex #DeepLearning #AISolutions https://github.com/Shubhamsaboo/awesome-llm-apps

And of course someone just had .. just had to try it out ! This guy literally recreated the entire system usng N8N ! Check this out ! The article explains how the author recreated Anthropic’s recently published multi-agent research system entirely with the low-code automation platform n8n, eliminating the need for traditional software engineering. Central to the solution is a clearly separated set of AI agents—Customer Support, Lead (Orchestrator), multiple parallel Search Subagents, and a Copywriter—that collaborate through n8n workflows, external APIs, and structured JSON outputs to turn a vague user request into a polished, PDF research report in about seven minutes. By sharing the architecture, tools (e.g., Brave Search, ScrapingAnt, OpenRouter, Markdown Master), and a ready-to-use template, the author encourages product managers to develop AI intuition, automate knowledge-heavy tasks, and build impressive portfolio projects. #n8n #anthropic #multiagent #lowcode #automation #zapier #makecom #aiagents #orchestrator #bravesearch #scrapingant #openrouter #markdownmaster #workflowautomation #nocode #aiworkflow #productmanager #airesearch #pdfgeneration #jsonoutput #aiportfolio #knowledgeautomation #aicollaboration #workflowbuilder #aiintegration https://www.productcompass.pm/p/multi-agent-research-system

The ever-so careful Anthropic ! Meticulously daling with the fundamentals the complete exact opposite of OpenAI (Oh wait they are ex-OpenAI emplyess by the way .. right ?) Anthropic’s new Research feature adopts a multi-agent architecture where a lead Claude model orchestrates specialized subagents that search the web and other tools in parallel, enabling dynamic, breadth-first investigations that outperform single-agent approaches. Achieving dependable performance required careful prompt engineering—teaching agents how to delegate, scale effort, choose tools, and think aloud—as well as bespoke evaluation methods that combine LLM-as-judge metrics with human review. While the system delivers significant accuracy and speed gains, it also introduces engineering and economic challenges such as heavy token consumption, stateful error handling, and complex deployment, all of which demand rigorous observability, iterative testing, and robust production safeguards. #claude #anthropic #research #multiagent #airesearch #webresearch #perplexity #searchgpt #tavily #aiagents #promptengineering #llmasajudge #aiorchestration #parallelprocessing #breadthfirst #tokenoptimization #aiobservability #productionai #aitools #aievaluation https://www.anthropic.com/engineering/built-multi-agent-research-system

Building complex, production-ready AI agents, especially multi-modal or multi-agent systems, can be challenging. Introducing the Agent Development Kit (ADK), a new open-source project from Google designed to simplify this process based on Google's internal experience. ADK provides a powerful, open foundation (model-agnostic, deployment-agnostic, interoperable) that makes agent development feel like software development, complete with native multi-modal streaming and easy local debugging via a built-in UI. Watch Product Manager Anand Iyer, Tech Lead Bo Yang, and Developer Advocate, Ivan Nardini introduce ADK and demo building a multi-agent, multi-modal travel planner quickly using the SDK. Learn about the core design principles and see how you can get started building your own sophisticated AI agents today. Resources: Get Started → https://google.github.io/adk-docs Sample Agents → https://goo.gle/3Rbdo4s Subscribe to Google for Developers → https://goo.gle/developers #ADK #AgentDevelopmentKit #GoogleAI #OpenSource #AIAgents #MultiModal #MultiAgentSystems #AIDevelopment #AIWorkflow #GenAI #LangChain #AutoGen #AIInfrastructure #SoftwareDevelopment #DebuggingUI #TravelPlanner #Python #AICommunity #ModelAgnostic #DeploymentAgnostic

Building complex, production-ready AI agents, especially multi-modal or multi-agent systems, can be challenging. Introducing the Agent Development Kit (ADK), a new open-source project from Google designed to simplify this process based on Google's internal experience. ADK provides a powerful, open foundation (model-agnostic, deployment-agnostic, interoperable) that makes agent development feel like software development, complete with native multi-modal streaming and easy local debugging via a built-in UI. Watch Product Manager Anand Iyer, Tech Lead Bo Yang, and Developer Advocate, Ivan Nardini introduce ADK and demo building a multi-agent, multi-modal travel planner quickly using the SDK. Learn about the core design principles and see how you can get started building your own sophisticated AI agents today. #ADK #AgentDevelopmentKit #GoogleAI #AIAgents #MultiModal #MultiAgentSystems #OpenSource #SoftwareDevelopment #AIDevelopment #AIWorkflow #AItools #AutoGen #LangChain #AIPlanning #Debugging #BuiltInUI #TravelPlanner #AgentFramework #ModelAgnostic #DeploymentAgnostic https://youtu.be/zgrOwow_uTQ

Vy is a native Mac app that uses advanced interaction capabilities and reasoning agents for human-computer interaction. It aims to eliminate the need for clicking, memorizing shortcuts, or navigating menus by allowing users to directly instruct the app. Vertex AI Agent Builder is another tool, that helps to create multi-agent experiences by building on existing processes. https://vercept.com/ #VyApp #MacApps #HumanComputerInteraction #AItechnology #VoiceControl #NoClickNeeded #AIAgents #VertexAI #MultiAgentSystems #AIBuilder #Automation #TechInnovation #FutureOfAI #SmartSolutions