But most companies still need Automation first. Over the past few months, I've seen countless discussions about AI Agents, MCPs, autonomous workflows, and the latest AI models. The technology is impressive. But here's the reality: Many organizations are still struggling with basic operational workflows. 📊 Reports are created manually. 📧 Emails are routed manually. 📋 Data is copied between systems. 🔧 Maintenance records are updated by hand. ⏳ Teams spend hours on repetitive tasks every day. Before asking: "How can we deploy AI Agents?" Ask: "Have we automated the process yet?" Because AI Agents perform best when they operate on top of: ✅ Structured workflows ✅ Clean and accessible data ✅ Well-defined business rules ✅ Standardized processes ✅ Measurable outcomes Without that foundation, AI doesn't solve the problem. It simply automates the chaos. In many cases, a well-designed automation workflow can deliver more business value than an advanced AI Agent. The future is not: Automation OR AI Agents. The future is: Automation → AI → AI Agents Build the foundation first. Then scale intelligence. What's your experience? Are companies rushing into AI Agents before fixing their underlying processes? Decoding Data Science DDS Business Circle Mohammad Arshad #AI #AIAgents #Automation #ArtificialIntelligence #n8n #DigitalTransformation #BusinessAutomation #WorkflowAutomation #MachineLearning #DataDriven #Industry40 #IndustrialAutomation #TechLeadership

And I’m doing an emergency AI Builder Session today to break down what it means for developers, data scientists, and people building AI applications. This will be useful if you are: - Exploring LLMs and AI agents - Building AI apps or prototypes - Participating in the Build AI Application Challenge - Trying to understand how the latest AI tools can speed up development As a special gift for our active Skool community, I’m giving free access to this session today. https://nas.com/artificialintelligence/events/emergency-session-claude-fable-mythos Comment CLAUDE below and I’ll DM you the coupon code. The session is happening today, so comment now if you want access.

Recently Yesterday! I attended an incredibly insightful "Emergency Session" on the new Claude models hosted by @Arshad Ahmad. If you are actively building and deploying AI applications, the landscape just shifted. 🚀 🤖We moved past the release notes and straight into Python notebooks to see how to actually implement Fable 5. We didn't just look at benchmark scores; we got under the hood to see exactly how Anthropic's new Claude Fable 5 actually impacts the systems we build. For anyone developing autonomous agents or practical AI solutions, this session was pure gold.🌟 💪Here are my biggest takeaways on turning these updates into production-ready solutions: ⫸ Smart Model Routing is Everything: We explored a Model Routing Decision Framework that proves the winner is not always the most expensive model. We mapped out when to use Haiku 4.5 for speed, Sonnet 4.6 for default tasks, Opus 4.8 for depth, and Fable 5 for premium, long-context tasks. ⫸ Fable 5 as a Senior Architect: Instead of just treating it like a chatbot, we looked at deploying Fable 5 as a senior AI application reviewer. It's incredibly powerful for spotting missing risks, finding architecture weaknesses, and assessing production readiness. ⫸ AI as a Judge: We broke down a Model Evaluation Flow where Fable 5 acts as a judge, merging outputs from Haiku, Sonnet, and Opus to generate a comprehensive evaluation report. ⫸ Adaptive Thinking & Cost Control: We analyzed the tradeoffs between "medium" and "high" effort prompting—balancing faster responses and lower costs against deep architectural thinking. We even tracked real-time API token usage and costs directly in a Colab notebook.🐍 Building practical AI is all about choosing the right tool for the job. Huge thanks to Decoding Data Science for an event that focused on real-world execution rather than just theory! #ClaudeFable5 #Anthropic #AIArchitecture #GenerativeAI #AICommunity #Developers #DecodingDataScience #DDSBusinessCircle #aiGuild #AiResidency #MachineLearning #Python

That is true, but it is only the surface layer. The bigger shift is this: MCP helps us think about AI systems as structured, context-aware architectures, not just prompt-based applications. A useful way to understand it is through four layers: 1. Memory Layer Keeps track of past interactions, user context, state, and history so the system does not start from zero every time. 2. Protocol Layer Standardizes how data, tools, systems, and models communicate with each other reliably. 3. Routing Layer Decides which tool, workflow, or agent should handle a task based on the current context. 4. Agent Layer Enables autonomous execution, where agents can perform specific roles and complete tasks with the right context. This is why MCP matters. It is not just about connecting an AI model to external tools. It is about creating a foundation for interoperable, context-aware, and agent-ready AI systems. As AI applications become more complex, the real challenge will not be only “which model should we use?” The bigger question will be: How do we design the architecture around the model? Curious to hear your thoughts. What would you add or change in this MCP architecture view? Comment below, and share this if you found it helpful.

🔹 Anthropic Urges Mandatory Safety Testing for Frontier AI Models Anthropic called on U.S. lawmakers to require independent safety evaluations for the most powerful AI models and warned against overriding state AI regulations without a strong federal framework. The proposal highlights growing industry focus on AI governance, model risk assessment, and responsible deployment. 🔹 Apple Expands AI Strategy with Next-Generation Siri Apple unveiled a significantly upgraded AI-powered Siri with deeper context awareness and tighter integration across its ecosystem. The update signals a shift from AI demos to real-world productivity applications, strengthening competition with OpenAI, Google, and Anthropic in consumer AI. 🔹 OpenAI Moves Closer to Public Markets Following its confidential IPO filing, OpenAI is positioning itself for one of the most anticipated technology listings in recent years. A successful public offering could reshape AI investment flows and accelerate spending on foundation models, agents, and AI infrastructure. 🔹 Anthropic Secures Massive AI Infrastructure Expansion Anthropic announced a $35 billion compute expansion backed by Apollo, Blackstone, and Broadcom. The initiative will significantly increase AI training and inference capacity, reflecting the industry's race to secure large-scale infrastructure for next-generation AI systems. 🔹 AI Policy Debate Intensifies Around Public Benefit and Regulation U.S. policymakers are exploring new approaches to ensure the public benefits from the AI boom, including discussions around government participation in AI-driven economic gains. The debate underscores increasing attention on AI’s impact on jobs, economic value creation, and long-term societal outcomes. Happening today at 7:30 PM GST: Emergency Session: Claude Fable Mythos 📌https://nas.com/aiguild/events/emergency-session-claude-fable-mythos Join change: Building AI Application 📌https://nas.com/artificialintelligence/challenges/building-ai-application-jun