Why RICE is broken for AI features and how to use DIVES instead

Better Than GPT-5? We Try ERNIE X1.1, Baidu’s Latest AI Model Is AI hype finally meeting genuine utility? 🤔 Baidu’s ERNIE X1.1 is generating serious buzz, and for good reason. Unlike some of the flashy AI demos we’ve seen, this model is being positioned as a “reasoning-first” approach – a crucial shift towards reliable, predictable performance. As professionals building agentic workflows (think automation, intelligent assistants, and streamlined processes), this focus on behavior is incredibly valuable. 🚀 The article from Analytics Vidhya highlights how ERNIE X1.1 prioritizes practical reliability over pure spectacle. It’s about building AI that *works* consistently, not just impresses. This could significantly impact how we integrate AI into our daily operations and unlock new levels of efficiency. 💡 What are your thoughts on this move away from purely impressive demos and towards practical AI capabilities? Would you consider integrating ERNIE X1.1 into your workflow? Let’s discuss! 👇 #AI #ERNIE #Baidu #ArtificialIntelligence #Innovation 🤖 Original article: https://lnkd.in/dPG52QFX Automatically posted. Contact me if you want to know how it works :-)

🚀 Enterprise AI doesn’t fail because the models are weak. It fails because the context isn’t engineered right. Prompts and RAG were a good start but they don’t scale. Once you design the information environment around the model with hybrid retrieval, structured memory and smarter integrations, AI finally becomes reliable, trusted and adopted. That is the power of context engineering. It is the real foundation of enterprise AI. 👉 Full article link in the comments. #AI #EnterpriseAI #ContextEngineering #Innovation #IWConnect

Souvik Ta explains how to build robust, transparent AI agents with LangGraph and the ReAct framework, turning clever prompting tricks into real-world applications. Learn how to debug with LangSmith and build stateful, intelligent systems. #LangGraph #ReAct #LangSmith #AIagents #AI #this_post_was_generated_with_ai_assistance #responsibleai https://lnkd.in/eeNXaP5T

AI tools sometimes produce inaccurate or "hallucinatory" outputs. This can be a major problem for developers building AI-powered products. A new guide shows how to mitigate this using n8n's Eval Node. This powerful feature lets you verify and correct AI-generated data, boosting the reliability of your applications. The post provides a clear, practical example, making it easy to implement this crucial step in your AI development workflow. Improve the accuracy and trustworthiness of your AI projects today! #AI #ArtificialIntelligence #n8n #SoftwareDevelopment #AIdevelopment 🔗 Read more: https://lnkd.in/gy-4vBWG

AI’s big leaps are slowing. That could be a very good thing. The WSJ reports that progress on models like GPT5 and Llama 4 is leveling off. This is not a setback. It is an opportunity. Most companies have not fully unlocked the value of the AI tools that already exist. Slower progress gives businesses time to focus on adoption, integration, and measurable results instead of chasing hype. The winners will not be the ones moving the fastest. They will be the ones moving the smartest. 🔗https://lnkd.in/emaxrasF

GPT-5 comes with a new feature: scheduled notifications. Until now, AI interactions were linear and synchronous — I asked a question, it answered. With notifications, I can set it to operate asynchronously, delivering something independently on a schedule. For example, I’ve scheduled one for 7:00 each morning. GPT-5 generates a fresh insight on one of my ongoing projects, drawn from the body of work we’ve been building together. It might highlight a blind spot, suggest a connection across projects, or surface a thread I had set aside. This marks a meaningful shift in how AI can be used. It’s no longer just a tool I query, but an autonomous partner integrated into my workflow, helping to sustain momentum.

One thing I’ve learned while experimenting with AI automation is that context matters more than anything else. Automation on its own can handle repetitive steps, but when paired with vector databases and AI models, it transforms into something much more powerful. Instead of just following instructions, it can understand documents, extract meaning, and give accurate, context-based responses. This combination is what turns simple workflows into intelligent systems. #AI #Automation #n8n #VectorDatabases #FutureOfWork

What got my attention in 𝙏𝙝𝙚 𝙒𝙚𝙚𝙠 𝙏𝙝𝙖𝙩 𝙒𝙖𝙨? This week at a glance: 🔹𝗔𝗜 𝗶𝘀 𝗲𝘃𝗲𝗿𝘆𝘄𝗵𝗲𝗿𝗲. In a longer-form post, “What is AI?”, I lay out my current framework for understanding the space based on Five Groupings (or classes) of AI - based on their roles and capabilities - and 10 “Flavors” of the technology. Feedback, as always, is appreciated. 🔹Graham and I discussed this topic, as well as his 𝗼𝗯𝘀𝗲𝗿𝘃𝗮𝘁𝗶𝗼𝗻𝘀 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗥𝗘+ 𝗖𝗼𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲 (𝘄𝗵𝗶𝗰𝗵 𝗴𝗮𝘁𝗵𝗲𝗿𝗲𝗱 ~𝟰𝟬,𝟬𝟬𝟬 𝗽𝗲𝗼𝗽𝗹𝗲 𝗳𝗼𝗰𝘂𝘀𝗲𝗱 𝗼𝗻 𝗼𝘄𝗲𝗿 𝗶𝗻 𝗟𝗮𝘀 𝗩𝗲𝗴𝗮𝘀 𝘁𝗵𝗶𝘀 𝘄𝗲𝗲𝗸) 𝗶𝗻 𝗼𝘂𝗿 𝗖𝗼𝗳𝗳𝗲𝗲 𝗖𝗵𝗮𝘁. Read it all here: https://buff.ly/RrarQOZ

🌟 Excited to share an in-depth look at DeepSeek’s V3.1 AI model on my blog! 🚀 This open-source powerhouse features a significant 128K token context window, hybrid inference modes, and advanced agent capabilities, pushing AI boundaries. Whether analyzing extensive documents or optimizing coding tasks, V3.1 is a game-changer for developers and businesses. Curious how this tool can transform your workflows? Delve into the complete article for insights, code snippets, and practical advice drawn from my hands-on AI implementation experience in corporate settings. 💡 Pro Tip: Explore V3.1 on Hugging Face to unlock its full potential for your projects. ❓ How are you leveraging AI to innovate in your work? Share your thoughts below! 🔗 Check out the full article: [https://lnkd.in/grq7viaj] #AI #MachineLearning #DeepSeek #OpenSource #TechInnovation

MCP isn't just another API or a collection of tools; it's the crucial seam connecting non-deterministic AI planning with reliable, deterministic execution, as Jim Clark explains. Discover how to avoid common pitfalls and build robust AI systems by understanding the full potential of MCP's tools, resources, prompts, and elicitations. #MCP #AI #Agents #Tools #API #ModelContextProtocol #LLM #Observability #this_post_was_generated_with_ai_assistance #responsibleai https://lnkd.in/ebFC8xqQ