Prasanna V
@Prasan09V
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Tech. Strategy. Stories. AI strategist & ex‑strategy consultant 🤖
Chennai, India
Joined June 2012
Claude Skills vs. Copilot Studio — old wine, smarter bottle?? 🍷 I built the same customer-support workflow in both systems, side by side. Different tools. Same logic. Identical results. 🎥 Here’s the demo 👇 #CopilotStudio #ClaudeSkills
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Claude Skills load modular “capabilities” when needed. Copilot Studio does the same through multi-agent orchestration. Same architecture, different packaging. The takeaway? Modularity scales. Call them skills, agents, or capabilities - it’s all composable AI.
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There’s going to be a huge gap in execution velocity for the foreseeable future between the individuals, teams, and companies that adapt (or create for the first time) their workflows to work with AI agents vs. those that don’t. In the past few months I’ve talked with a number
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It's not about AI replacing us, but augmenting our work. This demo shows how we can shift from data drudgery to high-value human insights. Read more here:
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From weeks of secondary desk research to UNDER 7 MINUTES?! I put OpenAI's ChatGPT Agent to the test on a real consulting challenge: a micro-market assessment for a luxury jeweller in Chennai. See the speed in action! @OpenAIDevs @OpenAI 👇 #ChatGPTAgent
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These aren't just cool demos; they're tools I'm using every day to work smarter, and build more effective solutions. We're moving from simple chatbots to sophisticated agents. What AI agents are changing your daily workflow? Share your experiences! #AI #AgenticAI #MSFTCopilot
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3 agents blew me away: Teams Interpreter: Natural, real-time voice translation in Japan. Breakthrough! Microsoft Researcher: Cuts days of docs to minutes. My daily go-to. My Agent Navigator: Compares deep reports vs. live data. Keeps me current!
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Okay, I had to share this! My mind's been blown by recent AI agent advancements, and the last few weeks have been particularly fascinating. These aren't just tech updates; they're personal game-changers in how I work! 👇
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New Anthropic Research: Project Vend. We had Claude run a small shop in our office lunchroom. Here’s how it went.
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Imagine AI agents understanding your plain-English data requests, autonomously writing Python, & generating charts. It's about becoming a "Data-Empowered Boss," guiding the analysis, not getting lost in the weeds. The future of data work is conversational & agent-driven! #AI
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See how AI agents use tools like Code Interpreter for practical data analysis. 📊 This demo shows them processing data and generating insights. @OpenAIDevs #AIAgents #CodeInterpreter #DataAnalysis
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Magentic-UI's magic is its "human-in-the-loop" design. 🧑💻 With Co-Planning, you approve the AI's strategy, and with Co-Tasking, you oversee execution. It's about becoming an "Agent Boss," guiding your AI team to amplify your work, not just delegating to a black box.
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The AI landscape is buzzing with "super agents"! 🤖 But how do we stay in the driver's seat? I went hands-on with Microsoft's research prototype, Magentic-UI from @pyautogen, to see how it helps orchestrate these powerful tools while keeping humans in control. Check out the demo!
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3/ Inspired by Microsoft’s A2A vision, @Prasan09V experimented with a multi-agent setup 🚀 Microsoft's AutoGen & Google ADK agents discover each other via A2A, extract key metrics from a quarterly report, benchmark vs. industry, & draft a 1-page doc https://t.co/URqXtKJ5xU
Inspired by Microsoft’s A2A vision, I experimented with a multi-agent setup! 🚀 Microsoft's AutoGen & Google ADK agents discover each other via A2A, extract key metrics from a quarterly report, benchmark vs. industry, & auto-draft a 1-page exec summary. Demo Video👇 #A2A
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The result? A fully auto-drafted 1-page executive summary! Each agent plays its part - data extraction, industry benchmarking, insight generation, all orchestrated by A2A. True multi-agent power!
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What does this mean in practice? 🤔 Imagine AI agents, regardless of their origin (Google, Microsoft, etc.), seamlessly collaborating. The A2A protocol acts as a universal translator, allowing them to: 1️⃣ Dynamically find each other's capabilities. 2️⃣ Exchange information &
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Inspired by Microsoft’s A2A vision, I experimented with a multi-agent setup! 🚀 Microsoft's AutoGen & Google ADK agents discover each other via A2A, extract key metrics from a quarterly report, benchmark vs. industry, & auto-draft a 1-page exec summary. Demo Video👇 #A2A
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As I build & experiment with AI, I prioritize opps identified via top-down value mapping for identifying quick wins and long-term potential opps.
💡 Flip the AI Conversation: From “What’s the ROI?” to “Where Does Value Live?” Seeing lots of excitement for AI/Copilot pilots, but proving value later is tough. The "show me the ROI" question is real! A better way? Focus on core business value drivers first. 👇 #AI #ROI
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Why this works: ✅ Value tied to metrics from Day 1 (CFO-friendly!) ✅ Clear Exec Sponsorship emerges ✅ Aligned impact across teams (shared data/goals!) Takeaway: Ask "What value can AI unlock?" not "Where can we use AI?" Watch the demo & share: How are you tackling the AI
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Here's a value-first approach (honed in my consulting days using frameworks like Enterprise Value Maps): 1️⃣ Start w/ Shareholder Value 2️⃣ Break down pillars (Revenue, Costs…) 3️⃣ Drill down to daily tasks & KPIs 4️⃣ Spot where AI can improve KPIs/save time 5️⃣ Prioritize: Quick
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