Shilpa Vir

As product manager roles are transmutating from a pure manager type role to a PM engineer type role, here's the checklist for you - 1. Everyday play and experiment with different AI tools, internally make a list on which model to use for what purpose (this step is critical, as this compounds). 2. Never use AI for the initial draft when you are writing something. Writing brings you detailed clarity and in this AI age, clarity is king. Finish up your draft with AI, but start manually. 3. Always pay and use the frontier model. Don't cut corners here. The output of an Opus 4.6 is drastically different from sonnet when it comes to complex tasks. Having said that, develop a mental map on which model to use for what complexity of tasks. Otherwise you will just burn tokens for simple tasks. 4. When learning or understanding a concept, be deliberate and progressive when using the AI tools as well. For example, start with ChatGPT, take that output, understand it, add your own thoughts and then go to claude. Again point number 3, do apples to apples. If you are using the free tiers, treat all the free tiers as equals. 5. Learn to write agent native specs. Agent native specs are living docs which live in the repo, which the agent has direct access to. Take care of the smaller nuances. For example - If your team is using a context window of 100k models, then don't write specs which are too large. Eventually the agent will run out of context and start hallucinating. 6. When you have developed a strong intuition about points 1-5, then and only then build. The world is moving away from a PRD driven build environment to an agent spec driven build environment. Internalise that change. Change your workflow to adapt to it. 7. Build prototypes with the speed of thought, but remember these are prototypes and not actual production code. The prototype to production code journey is a bit far along. But that doesn't mean, you don't build, build your ideas quickly. Again the idea here is for you to develop enough intuition and judgement so that you can keep up with the agent. 8. As we are shifting from "vibe coding" to "agentic engineering", please remember this shift is going to be chaotic. Remember the world required 1-2 yrs to fully understand what actually is an "agent". So don't get overwhelmed, don't get any FOMO. Remember there's still a lot of time for the world to make this transition. All you can do is prepare better. Finally, anyone who is transitioning from a traditional PM to an AI native PM builder, remember, "chaos is a ladder". Be curious, be eager to learn, be adaptable, be flexible. Spend a lot of your time with the AI tools, stress test them, understand their limits, understand their context window and memory. This is in no way any exhaustive list (in fact I would argue this is a beginners list). But as you climb each stair in this ladder, you will develop enough intuition to move even further.

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We love Lovable ❤️ From MVP ➜ MLP — this is the real shift in product building. ✨ Anyone can launch a Minimum Viable Product. But today, viable is not enough. Users want Minimum Lovable Products — products that feel good, look good, and create an emotional connection from day one. When you focus on lovable, everything changes: 🚀 Faster adoption 💡 Better feedback 🤝 Strong loyalty 🔥 Higher retention ✨ And users actually enjoy the experience The future belongs to products people love, not just tolerate. Ready to build your first AI MLP product ? https://lnkd.in/drsJq5Wj #ProductManagement #MLP #Innovation #DesignThinking #AI #SaeedAlHasanAiMaster

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🎉 Excited to share that we just crossed 740+ reviews for our Product Faculty's AI Product Management Certification. Here are the 6 patterns that show up again and again in what people love most about the cohort: 1. Miqdad’s (OpenAI's product lead & leader teaching this cohort) clarity, passion, and teaching style. This is the first thing almost every review mentions. Students consistently say things like these: “He makes complex AI concepts feel simple.” “This is the first time AI made sense.” “Miqdad teaches like someone who genuinely wants you to win.” You’re not just learning frameworks, you’re learning from the Product Lead at OpenAI, who teaches with genuine care, rigor, and intention. 2. The second thing they highlight is how complete and interconnected the entire ecosystem is. This isn’t a program that teaches one slice of the job. They’re learning every major skill an AI PM needs: from identifying real AI opportunities, to designing AI-native workflows, to prototyping and evaluating models, all the way to thinking through latency, safety, guardrails, architecture, and deployment. 3. Zero passive learning, everything is practical. This is where the AI Build Labs come in. In these labs you learn to: Build agents, chain tools, reason about RAG, prototype end-to-end workflows, use modern AI toolchains (n8n, Lovable, Base44, Claude MCPs, etc. You actually become a builder! 4. And then there’s the capstone, the part of the program that many call “the turning point.” By the time students graduate, they don’t just leave with notes; they leave with a working AI product or feature they built themselves. Something they can show to their team, their executives, or a future hiring manager. For many, it becomes the single most valuable asset in their portfolio. 5. CPO sessions with world-class product leaders. This is the piece people don’t expect — but end up loving the most. We bring in top product leaders from places like: Google, Atlassian, Walmart, Shopify, Menlo Ventures, etc. And they teach what it really takes to design, scale, and lead product at the highest levels... then connect those lessons back to AI. This is where decades of wisdom meet the next decade of technology. 6. A learning experience that feels like it was designed around you. We’ve spent years refining this hybrid system: 1. On-demand modules (to master fundamentals at your pace) 2. Live sessions (for the hard problems and deep discussion) 3. Open Q&A (to get personalized guidance) 4. Community mixers (to expand your network) 5. Support on every step We don’t waste time teaching basic AI live... when you could be spending that time asking Miqdad how to solve real problems. >>> If you'd also love it, go here for $500 off your enrolment: https://lnkd.in/giMERtYw

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7 must read books for PMs and Aspiring PMs [1] Predictably Irrational: The Hidden Forces that Shape Our Decisions by Dan Ariely https://amzn.to/3veTeit → This book gives you a perspective on behavioral finance. Deep dive into the psychological aspects of users and build products that scale. [2] Start With Why by Simon Sinek https://amzn.to/3wO3UoS → Before you build anything, get into the why and understand why would anyone need the product you are building. Knowing your why can give you clarity that you would never thought. [3] The Art of Thinking Clearly by Rolf Dobelli https://amzn.to/4a6wY9j → User psychology concepts that you can apply in your real life as well as your product management career - gold mine to understand how to influence user behavior. [4] Hooked by Nir Eyal https://lnkd.in/dzv7GpHC → One of the finest books to understand and build networked effects in to your product. [5] Tech Simplified for PMs & Entrepreneurs by Deepak Singh https://amzn.to/3PgG8bv → Tech 101 simplified and understand the basic principles that you need to grow and become the top 1% PM. [6] Inspired by Marty Cagan https://lnkd.in/dxNhP7Zi → Understand how to create products that people love and how to create those products at scale. [7] The Lean Product Playbook by Dan Olsen https://lnkd.in/dhJ3CZeM → Understand how to get started with the product building - feature identification and prioritization the right way, decoding MVP and many more. Follow Vishal Bagla to get more insights into product management. Get access to my learnings and knowledge through this short and concise program - https://lnkd.in/dhQz8937 #ProductManagement #ProductManagers #Books #Learning

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Interviewing for a Product role at 𝐆𝐨𝐨𝐠𝐥𝐞? 👨🏻‍💻 🧰 Here are 8 insights that helped me get to the final round — and they apply far beyond Google, to any GM or leadership role. Google does not test frameworks. It is not retrospective on your CV. It tests your thinking, creativity, impact, and ability to lead through ambiguity. In senior roles, you need all of these attributes to succeed. Old generic playbooks won't work. Here's what I learned: 🔹 1. 𝐁𝐞 𝐏𝐫𝐨𝐮𝐝 𝐨𝐟 𝐘𝐨𝐮𝐫 𝐅𝐚𝐢𝐥𝐮𝐫𝐞𝐬 Great PMs fail-forward. If you've taken bold bets — like launching a startup that didn’t take off — 𝒕𝒉𝒂𝒕’𝒔 𝒂 𝒔𝒕𝒓𝒆𝒏𝒈𝒕𝒉, 𝒏𝒐𝒕 𝒂 𝒘𝒆𝒂𝒌𝒏𝒆𝒔𝒔. Impact comes from trying, failing, learning, and iterating. 🔹 2. 𝐃𝐨𝐧’𝐭 𝐎𝐯𝐞𝐫-𝐏𝐫𝐞𝐩𝐚𝐫𝐞 Burnout shows. You need calm and clarity, not a 50-page prep doc. Sleep > Stress. Lack of sleep ruins your buoyancy and ability to connect the dots creatively which is required for product sense. 🔹 3. 𝐒𝐤𝐢𝐩 𝐭𝐡𝐞 𝐅𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤𝐬. 𝐒𝐨𝐥𝐯𝐞 𝐭𝐡𝐞 𝐏𝐫𝐨𝐛𝐥𝐞𝐦. Google isn’t looking for case study robots. They want to see structured creativity — can you work on an ambiguous problem and make smart bets? Connect the dots backwards from the outcome by using deductive reasoning and evaluating assumptions. Rigid frameworks break down when you are hit with diverse problems. 🔹 4. 𝐓𝐡𝐢𝐧𝐤 𝐁𝐢𝐠𝐠𝐞𝐫. 𝐓𝐡𝐞𝐧 𝐁𝐢𝐠𝐠𝐞𝐫 𝐀𝐠𝐚𝐢𝐧. Small UX tweaks won’t cut it. Think $1-10B opportunities, underserved segments, or moonshots. Your value prop should be disruptive, not incremental. 🔹 5. 𝐍𝐚𝐢𝐥 𝐭𝐡𝐞 𝐔𝐬𝐞𝐫 𝐚𝐧𝐝 𝐭𝐡𝐞 𝐒𝐞𝐠𝐦𝐞𝐧𝐭 Whether it's Search, Android, or GCP — you must deeply understand your user and segment. Niche down to the segment, personas per segment, and their needs to really show your user-centricity in solving problems. 🔹 6. 𝐁𝐞 𝐁𝐨𝐥𝐝𝐥𝐲 𝐎𝐩𝐢𝐧𝐢𝐨𝐧𝐚𝐭𝐞𝐝 Don’t give the "safe PM answer." Share a view that’s distinct, defendable, and deeply yours. What belief do you hold that most PMs wouldn’t? You need a distinctive perspective to stand out. 🔹 7. 𝐌𝐚𝐤𝐞 𝐭𝐡𝐞 𝐂𝐚𝐥𝐥, 𝐃𝐨𝐧'𝐭 𝐚𝐬𝐤 𝐟𝐨𝐫 𝐏𝐞𝐫𝐦𝐢𝐬𝐬𝐢𝐨𝐧 Don’t ask what Google would do. Show what you would do. Take the decision. Lay out trade-offs, risks, and how you’d mitigate. Product leaders don’t wait for permission. 🔹 8. 𝐒𝐭𝐚𝐲 𝐏𝐨𝐬𝐢𝐭𝐢𝐯𝐞, 𝐄𝐯𝐞𝐧 𝐈𝐟 𝐘𝐨𝐮 𝐃𝐨𝐧’𝐭 𝐋𝐚𝐧𝐝 𝐈𝐭 (𝐘𝐞𝐭) Many people don’t get into Google on their first attempt. The bar is sky-high — less than 0.05% make it. If you make it to the "rounds" interviews, you’re already exceptional. Every round is a rep. Keep going. 🎉 --- 💬 I’d love to hear from others who’ve interviewed at top tech companies. What resonated with you? 📥 If you're prepping for a PM interview — DM me. Always happy to share more. ♻️ Repost to help others get ahead on interviews. #product #career #leadership

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Repeat after me:  Board meetings are not status updates.   They’re more of a mid-term test — for you, your team, and your strategy.  So what separates the high-quality GTM sections of board decks from the rest when it comes to prep? Here’s some of the best practices I look for that I shared with Pavilion for the best practices guide: https://lnkd.in/gYiys2SJ 1️⃣ Build a self-contained GTM pack. Make it self-explanatory, with accurate numbers and a narrative that's completely aligned with Finance. No translation or follow-up clarifications needed. Treat it as a document executives could circulate without you in the room — and be understood.  2️⃣ Cover 5 must-have sections in every update: 1) Revenue & Efficiency: Top-line numbers, unit economics, and how you’re trending against plan 2) Pipeline: Opportunities by stage, conversion rates, deal velocity, and lead volumes and CAC by channel  3) Team Capacity: Productivity metrics, and resource gaps 4) Customer Outcomes: Retention, expansion, health scores — anecdotes + quantitative data 5) Experiments & Lessons: What’s been tested, what worked, what didn’t—and what’s next 3️⃣ Drive a unified GTM narrative. Ensure Sales, Marketing, and Customer Success are laddering up to a common story for each board meeting.  Unify your metrics, share context, and don’t silo your commentary for one GTM function. Pre-align your narrative and numbers so the board hears how you're working as ONE TEAM to drive revenue. 4️⃣ Facilitate a conversation, don't just report. Master the underlying data so you can go deep: explain variance, hypothesize, and discuss root causes — not just talking to what's on the slides. Your goal should be to drive a forward-looking discussion, not providing a backward-looking  status update. 5️⃣ These are my personal pet peeves, but I’d avoid:   • Data dumps or decks with no storyline   • Inconsistent metrics, or changing templates, meeting-to-meeting   • Not distributing the deck as a pre-read – if you’re looking for engagement, give people time to absorb the content and come with questions  • Sharing (bad) surprises or critical info for the first time in the meeting   • Having the CEO handle all the GTM questions   • Vague explanations for GTM issues — "the market’s tough," "leads aren't high enough quality" doesn’t cut it. Get specific and outline what you're going to do about it. Board meetings are a lot of work, and great board meetings create clarity and momentum. Make sure you’re getting the ROI from your board by equipping them to help, anticipate, challenge, or think through issues.  What did I miss? It might be covered in the free Pavilion report. #BoardMeetings #startups

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