PMstack

𝐂𝐨𝐦𝐦𝐨𝐧 𝐭𝐞𝐫𝐦𝐬 𝐚𝐧𝐝 𝐜𝐨𝐧𝐜𝐞𝐩𝐭𝐬 𝐢𝐧 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐀𝐈—𝐬𝐢𝐦𝐩𝐥𝐢𝐟𝐢𝐞𝐝 🧠 • Agents are autonomous AI systems capable of perceiving, deciding, and acting in environments to achieve specified goals without continuous human control • Agency refers to the decision-making capability of an AI system to act autonomously and influence its environment based on its objectives and limitations • A Reasoning Engine is the central part of an AI system that processes information, applies logic, and determines actions using various reasoning methods to solve problems and make decisions • Tool Use is an agent's capacity to intelligently leverage external functions, APIs, or services to enhance its abilities, access data, or execute tasks beyond its inherent functions • Planning is the process by which an AI agent determines a sequence of actions to achieve its goals, including identifying steps, handling dependencies, and adapting to changing circumstances • Memory Systems are the mechanisms within an AI agent for storing, retrieving, and utilising past interactions, decisions, and knowledge to enable contextual understanding and continuous learning • ReAct is a framework that integrates reasoning traces with actions, allowing agents to verbalise their thought processes and interact with environments to find solutions • Agentic Workflows describe systems where multiple specialised AI agents work together in structured processes, exchanging information and coordinating to accomplish complex multi-stage tasks • Self-Reflection is an AI agent's ability to assess its own reasoning, outputs, and processes to detect errors, enhance iterations, and modify strategies without external guidance • Alignment involves ensuring that an AI agent's goals and behaviours are consistent with human values and intentions, considering safety, ethical implications, and intended purpose • Multi-Agent Systems are environments where several specialised AI agents interact, communicate, and collaborate to resolve problems that exceed the capabilities of individual agents • Sandboxing refers to security measures used to isolate AI agent operations within controlled environments to evaluate behaviours, prevent harm, and manage access to resources and permissions (credit to Brij kishore Pandey for this useful illustration; do follow him.) #agent #agenticai

𝐅𝐮𝐧𝐝𝐫𝐚𝐢𝐬𝐢𝐧𝐠 𝐢𝐬 𝐚𝐥𝐥 𝐚𝐛𝐨𝐮𝐭 𝐛𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐫𝐞𝐥𝐚𝐭𝐢𝐨𝐧𝐬𝐡𝐢𝐩 𝐰𝐢𝐭𝐡 𝐕𝐂𝐬 We often read stories about startups raising seed funding, some even at the idea stage, and we get excited to start up Many of us think, “If others—some even young and inexperienced—are raising funds, why not me?” ↳ But here’s the truth: fundraising is hard. It takes time, effort, and perseverance. ↳ Think of it from the VC’s perspective: they have limited capital and countless options to invest in. You might get on a call to pitch your idea or product, receive some questions, and maybe even a bit of feedback. But often, there’s no talk of funding or a follow-up meeting. Frustrating, right? ↳ So, where’s the disconnect? It lies in the unrealistic expectations fueled by success stories. Perhaps you’ve heard of a young startup raising seed funding—but they might already have some traction. Or someone secured funding at the idea stage—but they might have a team of serial entrepreneurs or individuals with proven 0-to-1 experience. ↳ 𝐌𝐲 𝐚𝐝𝐯𝐢𝐜𝐞: Reset your expectations and look beyond thepopular news stories. Here is what I would suggest: ✔️ Think of fundraising as a long-term game. The relationships you build now could lead to opportunities later. Stay connected with investors. ✔️ Ask VCs for help with warm introductions. It’s a great way to grow your network. ✔️ Share regular updates. Keep VCs in the loop on your progress—it might just spark their interest again. Fundraising is a journey, and patience is key. Focus on building trust and relationships over time. All the best with your efforts! I hope this was helpful. ------------ I post about my journey and thoughts about building a startup frugally. My goal is to guide and get fellow builders excited about building 🤝 𝐆𝐞𝐧𝐞𝐬𝐢𝐬 𝐏𝐨𝐬𝐭: https://lnkd.in/gdc8NrjM 𝐖𝐞𝐛𝐬𝐢𝐭𝐞 𝐃𝐨𝐦𝐚𝐢𝐧: https://lnkd.in/gUXqHFbC 𝐖𝐡𝐚𝐭 𝐚𝐦 𝐈 𝐛𝐮𝐢𝐥𝐝𝐢𝐧𝐠?: Pinnzo - A learning platform (releasing in early March🤞) ♻️ Share to help this post reach fellow builders #startup #leanstartup

𝐖𝐡𝐚𝐭 𝐢𝐬 𝐁𝐚𝐜𝐤𝐥𝐨𝐠 𝐑𝐞𝐟𝐢𝐧𝐞𝐦𝐞𝐧𝐭 𝐚𝐧𝐝 𝐡𝐨𝐰 𝐭𝐨 𝐩𝐞𝐫𝐟𝐨𝐫𝐦 𝐚 𝐛𝐚𝐜𝐤𝐥𝐨𝐠 𝐫𝐞𝐟𝐢𝐧𝐞𝐦𝐞𝐧𝐭. ✔️ Backlog refinement is the art of keeping your product backlog sharp, efficient, and aligned with your goals. Here’s why it’s a must-have practice:   ✔️ User stories are clear and understood.   ✔️ Priorities align with business objectives.   ✔️ Stories are properly sized for sprint planning.   ✔️ Dependencies and risks are identified early.  𝐖𝐡𝐚𝐭 𝐡𝐚𝐩𝐩𝐞𝐧𝐬 𝐢𝐧 𝐫𝐞𝐟𝐢𝐧𝐞𝐦𝐞𝐧𝐭? - Break down complex tasks into smaller ones.   - Clarify acceptance criteria to avoid confusion.   - Remove outdated or low-priority items.   - Reorder stories as priorities shift.  I hope this was helpful 🤝 𝐄𝐱𝐩𝐞𝐜𝐭 𝐚 𝐩𝐨𝐬𝐭 𝐝𝐚𝐢𝐥𝐲 𝐨𝐧 (Follow  PMstack): 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐚𝐭 11:30 𝐀𝐌 𝐈𝐒𝐓  𝐌𝐨𝐭𝐢𝐯𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐥𝐢𝐟𝐞 𝐥𝐞𝐬𝐬𝐨𝐧𝐬 𝐚𝐭 8:00 𝐀𝐌 𝐈𝐒𝐓 #BacklogRefinement #Agile #ProductManagement

𝐌𝐞𝐭𝐫𝐢𝐜𝐬 𝐟𝐨𝐫 𝐏𝐌, 𝐄𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫𝐬 & 𝐌𝐚𝐫𝐤𝐞𝐭𝐞𝐫𝐬 🎯 It is imperative to measure the right metrics to see your product succeed 𝑹𝒆𝒂𝒅 𝒎𝒐𝒓𝒆 𝒊𝒏 𝑷𝑷𝑻 🖥️ 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐢𝐨𝐧 𝐑𝐚𝐭𝐞 A conversion rate records the percentage of users who have completed a desired action. E.g. 1000 users land on a Loan enquiry landing page. Out of 1000, 100 users submit loan enquiry form. Here the conversion of Loan Enquiry form would be 10% 𝐂𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐀𝐜𝐪𝐮𝐢𝐬𝐢𝐭𝐢𝐨𝐧 𝐂𝐨𝐬𝐭 (𝐂𝐀𝐂) Money a company spends to acquire a new customer E.g. If Swiggy acquires 10,000 customers in a day at a cost of INR 5,00,000. Out of 10,000 customers 2,000 customers made a purchase. Here, the customer acquisition cost would be INR 250 Here the user acquisition cost would be INR 50 (5,00,000/10,000). Earn Good karma !! Like ❤️ and share 🤝 so that this post can reach others #productmanagement #productmanager #metrics #conversion #CAC

Trying to get hands-on with LLMs... but don't know how to get started? These incredible AI tools are reshaping how we work, communicate, and solve problems. Imagine having a super-smart assistant that can help with almost any task—explore what they’re all about in the deck. Looking for more—register for the session on AI for Product Managers. #ai #LLM

OKR vs KPIs 📊 Unlocking progress and driving success relies on effective performance measurement and management. Two powerful tools have emerged to streamline this process: OKRs and KPIs. 𝐁𝐮𝐭 𝐡𝐨𝐰 𝐝𝐨 𝐭𝐡𝐞𝐲 𝐝𝐢𝐟𝐟𝐞𝐫, 𝐚𝐧𝐝 𝐰𝐡𝐢𝐜𝐡 𝐨𝐧𝐞 𝐬𝐡𝐨𝐮𝐥𝐝 𝐲𝐨𝐮 𝐮𝐬𝐞 𝐭𝐨 𝐚𝐜𝐡𝐢𝐞𝐯𝐞 𝐲𝐨𝐮𝐫 𝐠𝐨𝐚𝐥𝐬? 𝐎𝐊𝐑𝐬 (𝐎𝐛𝐣𝐞𝐜𝐭𝐢𝐯𝐞𝐬 𝐚𝐧𝐝 𝐊𝐞𝐲 𝐑𝐞𝐬𝐮𝐥𝐭𝐬) focus on setting ambitious goals and the measurable outcomes that will help you achieve them. On the other hand, 𝐊𝐏𝐈𝐬 (𝐊𝐞𝐲 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐈𝐧𝐝𝐢𝐜𝐚𝐭𝐨𝐫𝐬) track specific metrics to assess ongoing performance and operational health. Let's explore how to make these frameworks work for you! Credits to Jeroen Kraaijenbrink for this superb comparison infographic I hope this was helpful 🤝 𝐄𝐱𝐩𝐞𝐜𝐭 𝐚 𝐩𝐨𝐬𝐭 𝐝𝐚𝐢𝐥𝐲 𝐨𝐧 (Follow  PMstack): 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐚𝐭 11:30 𝐀𝐌 𝐈𝐒𝐓  𝐌𝐨𝐭𝐢𝐯𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐥𝐢𝐟𝐞 𝐥𝐞𝐬𝐬𝐨𝐧𝐬 𝐚𝐭 8:00 𝐀𝐌 𝐈𝐒𝐓 #okr #kpi

Curious about "AI" and its application at work? Here is a quick starter on AI Product Management Learn... What does it mean to do product management for AI product? What kind of products are AI-driven? What skills are required to become an AI product manager? #productmanagement #ai

𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬: 𝐀𝐧 𝐢𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝: What are AI agents? How are are they different than AI models? ✔️ AI agents are dynamic applications that go beyond static models by autonomously observing, planning, and acting to achieve specific goals—without constant human intervention required.  𝐖𝐡𝐚𝐭 𝐦𝐚𝐤𝐞𝐬 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬 𝐬𝐭𝐚𝐧𝐝 𝐨𝐮𝐭? Unlike traditional models that rely solely on training data and single-response outputs, AI agents:  ✔️ Use tools to access real-world data, enabling informed decisions.   ✔️ Manage session history for smooth, multi-turn interactions.   ✔️ Plan, execute, and adjust, just like a chef preparing the perfect dish.  𝐇𝐨𝐰 𝐝𝐨 𝐭𝐡𝐞𝐲 𝐚𝐜𝐡𝐢𝐞𝐯𝐞 𝐭𝐡𝐢𝐬? AI agents leverage a powerful cognitive architecture made up of:   ✔️ Generative AI models for reasoning.   ✔️ External tools (e.g., web APIs) as their "keys to the world."   ✔️ An orchestration layer to structure decisions and actions.  I hope this summary was helpful. Read the atttached guide further for detailed information. 𝐄𝐱𝐩𝐞𝐜𝐭 𝐚 𝐩𝐨𝐬𝐭 𝐝𝐚𝐢𝐥𝐲 𝐨𝐧 (Follow  PMstack): 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐚𝐭 11:30 𝐀𝐌 𝐈𝐒𝐓  𝐌𝐨𝐭𝐢𝐯𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐥𝐢𝐟𝐞 𝐥𝐞𝐬𝐬𝐨𝐧𝐬 𝐚𝐭 8:00 𝐀𝐌 𝐈𝐒𝐓 #AIAgents #GenerativeAI #AI

PM Interview Prep: 𝐇𝐨𝐰 𝐭𝐨 𝐚𝐧𝐬𝐰𝐞𝐫 𝐆𝐮𝐞𝐬𝐬𝐭𝐢𝐦𝐚𝐭𝐞 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬? Steps to follow while answering guesstimate questions: 1. 𝐂𝐥𝐚𝐫𝐢𝐟𝐲 𝐭𝐡𝐞 𝐏𝐫𝐨𝐛𝐥𝐞𝐦:   - Ensure you fully understand the question.   - Ask for clarification if needed to define the scope or assumptions. 2. 𝐁𝐫𝐞𝐚𝐤 𝐃𝐨𝐰𝐧 𝐭𝐡𝐞 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧:   - Divide the problem into smaller, manageable components.   - Identify logical steps to reach the final estimate. 3. 𝐌𝐚𝐤𝐞 𝐀𝐬𝐬𝐮𝐦𝐩𝐭𝐢𝐨𝐧𝐬:   - Use reasonable, relatable assumptions to fill in any gaps.   - State these assumptions explicitly to show transparency. 4. 𝐄𝐬𝐭𝐚𝐛𝐥𝐢𝐬𝐡 𝐊𝐞𝐲 𝐕𝐚𝐫𝐢𝐚𝐛𝐥𝐞𝐬:   - Define the critical variables that influence your calculation.   - Connect them to form a structured approach. 5. 𝐔𝐬𝐞 𝐁𝐞𝐧𝐜𝐡𝐦𝐚𝐫𝐤𝐬 𝐚𝐧𝐝 𝐑𝐞𝐚𝐥-𝐖𝐨𝐫𝐥𝐝 𝐃𝐚𝐭𝐚:   - Reference widely known figures or relatable analogies for accuracy.   - Compare with real-world scenarios to support your estimates. 6. 𝐏𝐞𝐫𝐟𝐨𝐫𝐦 𝐒𝐭𝐞𝐩-𝐛𝐲-𝐒𝐭𝐞𝐩 𝐂𝐚𝐥𝐜𝐮𝐥𝐚𝐭𝐢𝐨𝐧𝐬:   - Calculate each component systematically.   - Show how the smaller parts contribute to the overall estimate. 7. 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐞 𝐘𝐨𝐮𝐫 𝐓𝐡𝐨𝐮𝐠𝐡𝐭 𝐏𝐫𝐨𝐜𝐞𝐬𝐬:   - Explain each step clearly to highlight logical reasoning.   - Focus on demonstrating your structured approach, not just the final answer. 8. 𝐒𝐮𝐦𝐦𝐚𝐫𝐢𝐳𝐞 𝐭𝐡𝐞 𝐅𝐢𝐧𝐝𝐢𝐧𝐠𝐬:   - Present your final estimate.   - Highlight key takeaways from your process. 9. 𝐀𝐜𝐤𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 𝐋𝐢𝐦𝐢𝐭𝐚𝐭𝐢𝐨𝐧𝐬:   - Mention any assumptions or areas where the estimate could improve.   - Show openness to refinement or feedback. Here is a good eamples to apply the priciple with a top-down approach. Thanks to Aryan Sharan for sharing this solved example. I hope this was helpful 🤝 𝐄𝐱𝐩𝐞𝐜𝐭 𝐚 𝐩𝐨𝐬𝐭 𝐝𝐚𝐢𝐥𝐲 𝐨𝐧 (Follow  PMstack): 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐚𝐭 11:30 𝐀𝐌 𝐈𝐒𝐓  𝐌𝐨𝐭𝐢𝐯𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐥𝐢𝐟𝐞 𝐥𝐞𝐬𝐬𝐨𝐧𝐬 𝐚𝐭 8:00 𝐀𝐌 𝐈𝐒𝐓 #guesstimate

𝐖𝐡𝐚𝐭 𝐢𝐬 𝐁𝐚𝐜𝐤𝐥𝐨𝐠 𝐑𝐞𝐟𝐢𝐧𝐞𝐦𝐞𝐧𝐭 𝐚𝐧𝐝 𝐡𝐨𝐰 𝐭𝐨 𝐩𝐞𝐫𝐟𝐨𝐫𝐦 𝐚 𝐛𝐚𝐜𝐤𝐥𝐨𝐠 𝐫𝐞𝐟𝐢𝐧𝐞𝐦𝐞𝐧𝐭. ✔️ Backlog refinement is the art of keeping your product backlog sharp, efficient, and aligned with your goals. Here’s why it’s a must-have practice:   ✔️ User stories are clear and understood.   ✔️ Priorities align with business objectives.   ✔️ Stories are properly sized for sprint planning.   ✔️ Dependencies and risks are identified early.  𝐖𝐡𝐚𝐭 𝐡𝐚𝐩𝐩𝐞𝐧𝐬 𝐢𝐧 𝐫𝐞𝐟𝐢𝐧𝐞𝐦𝐞𝐧𝐭? - Break down complex tasks into smaller ones.   - Clarify acceptance criteria to avoid confusion.   - Remove outdated or low-priority items.   - Reorder stories as priorities shift.  I hope this was helpful 🤝 𝐄𝐱𝐩𝐞𝐜𝐭 𝐚 𝐩𝐨𝐬𝐭 𝐝𝐚𝐢𝐥𝐲 𝐨𝐧 (Follow  PMstack): 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐚𝐭 11:30 𝐀𝐌 𝐈𝐒𝐓  𝐌𝐨𝐭𝐢𝐯𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐥𝐢𝐟𝐞 𝐥𝐞𝐬𝐬𝐨𝐧𝐬 𝐚𝐭 8:00 𝐀𝐌 𝐈𝐒𝐓 #BacklogRefinement #Agile #ProductManagement