How to test agentic AI with behavioral boundary mapping

Agentic AI comes with an increased set of risks -- learn how organizations are offsetting those risks with rigorous planning and testing, drawing on new evaluation techniques. #AgenticAI #AITesting

EAGLET, a new framework by researchers from Tsinghua and Peking University, is tackling the long-standing challenge of "longer-horizon tasks" for AI agents. By dynamically generating custom, high-quality plans, EAGLET significantly boosts agent reliability, directly addressing a core limitation of current LLMs in multi-step reasoning. This innovation is a crucial step toward fully autonomous, intelligent agents that can execute complex, multi-day, or multi-week workflows in real-world environments. The ability to autonomously plan and adapt complex sequences is the next frontier for agentic AI adoption across enterprise and R&D. #AI #AIAgents #AutonomousAI #LLMs #EAGLET #WeeklyVentures

Good insights on agentic AI by Deloitte — not every automation should be agentic. Start by qualifying whether a process truly needs autonomy, multistep reasoning and continuous learning; then prioritise opportunities (where agentic AI gives real competitive edge). #AgenticAI #AIGovernance #GTM

🤖 Wondering how to take advantage of AI in your business? AI, like Copilot, can elevate your operations in countless ways! From summarising documents to drafting emails and analysing data, AI is a game-changer. The best part? It's a massive time-saver and drives efficiency. https://lnkd.in/ex83zgPd #AIAdoption #BusinessEfficiency #AItools #TechInnovation #ProductivityBoost

The era of prompt engineering is fading. We're in a major mindset shift: from Prompting to Planning. Instead of giving AI step-by-step instructions, we now define a high-level goal. The AI, utilizing frameworks such as LangGraph, functions as an autonomous agent. It can: -> Break down the goal into a clear plan. -> Use tools flexibly (such as Agentic RAG for real-time data). -> Reflect, analyze, and self-correct to stay focused and on track. Essentially, we've moved from commanding a tool to collaborating with a partner. Our role evolves from operator to strategist. We set the destination; the AI system charts the course and executes the journey. This is the shift to Goal Orchestration—and it's unlocking the ability to solve vastly more complex problems with greater reliability and creativity. #AI #LLMs #AgenticAI #LangGraph #FutureOfWork

🔥 AI leaders, take note. Dynatrace dropped a major innovation in the Agentic AI series—and it’s a game-changer for enterprise LLMs. 💥 AI Model Versioning + A/B Testing This isn’t theory. It’s real-time, production-grade intelligence for optimizing generative AI at scale. 🔍 Imagine: Testing multiple LLMs side-by-side—live Automatically routing traffic to the best-performing model Driving measurable outcomes with zero guesswork 📊 This is how AI becomes accountable, autonomous, and enterprise-ready. If you're building AI services, scaling LLMs, or driving digital transformation—this is the future of AI governance. 🔗 Dive into the blog: https://lnkd.in/g32PkZhf 👀 Let’s make AI smarter, faster, and more accountable—together. #AI #LLM #AgenticAI #Dynatrace #AIBusiness #AIModelVersioning #AIBTesting #EnterpriseAI #Observability #DigitalTransformation #GenerativeAI #AIInnovation #TechLeadership #CIO #CTO #CloudComputing #AutonomousCloud #AIgovernance #FutureOfAI #AIatScale #Dynatrace #OpenAI #Anthropic #ChatGPT #OpenTelemetry #Token #TokeCost #CostOptimization #Tracing

After years of watching AI tools struggle with construction terminology, I've realised why most construction AI keeps missing the mark—it doesn't speak our language. When Google's AI told people to put glue on pizza, it was embarrassing. When construction AI flags RAMS documents for mentioning "dead loads" or blocks safety docs discussing "striking formwork," it's dangerous. In my latest blog, I explore why generic AI fails construction and how domain-specific tools that actually understand our industry—from "gobbos" to "making good"—are the real solution. It's not about better prompts; it's about building AI that knows a "kicker" is concrete upstand, not a footballer. The future isn't chatbots. It's intelligent workflows that understand construction processes and know exactly when to escalate decisions to humans.  Link in comments 👇  #ConstructionTech #AI #PropTech #DigitalTransformation #WorkflowAutomation #ConstructionAI #DomainSpecificAI

🚀 LangGraph + LangChain = The Future of AI Agents AI is moving beyond prompts : it’s about agents that think, act, and adapt. With LangGraph (by LangChain), you can now build: ✅ Long-running & stateful AI agents ✅ Resilient workflows with checkpoints ✅ Prebuilt agent patterns (Supervisor, Swarm, LangMem) ✅ Tool-integrated state updates ✅ One-click deployment via LangGraph Platform If you’re building AI for production, LangGraph gives you control + reliability while LangChain ensures scalability + integration. 👉 2025 is the year of Agentic AI. Don’t just use AI , orchestrate it.

Is LangGraph the Future of AI Agents? 🤔 AI is evolving fast — from simple chatbots to intelligent, goal-oriented agents that can reason, plan, and remember. That’s where LangGraph is making waves. It’s designed to help developers build smarter, more autonomous AI systems. Key Features of LangGraph: Stateful Memory: Keeps track of past interactions and context. Multi-step Reasoning: Handles complex, sequential tasks efficiently. Tool & API Integration: Connects with external tools for real-world actions. Graph-based Workflow: Visualizes agent logic as nodes and flows. Customizable Agents: Build domain-specific, task-oriented AI systems. Do you think frameworks like this are shaping the next generation of AI?