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JUSTANOTHERPM

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Learn what to do and how to do it to excel as a product manager (or any professional) in the tech industry

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76 contributions to JUSTANOTHERPM
Week 1, Activity 1: Spot the Paradox in Real Products
Submit your analysis here. 👇 How to Submit 1. Fill out the template from the essay 2. Post your response in the comments below Then Read & Respond: Once you've submitted, read at least 2 other people's responses and leave thoughtful feedback. Let's go. 👇
0 likes • 11h
@Peculiar Ediomo-Abasi Thanks for sharing this. I am very happy to you picked a more traditional AI product (instead of the modern day stack which always includes LLMs) Really like how you summarised each section in the answer. A few follow up questions for you: 1. For the how it handles being wrong: it might make sense to go at least one level deeper. In the sense, think of some very concrete ways that you think Netflix is or should be handling this. Then think if you can translate that into an actual metric. In other words, what do you think are some objective ways for NF to know that this feature is not working. 2. Things traditional PMs might miss: some of the metrics you mentioned like CTR, watch time, might not be bad metrics to start with. Both are leading metrics and give a strong/confident signal of the user liking the recommendations. But I also agree that long term metrics/behaviour like engagement, retention is imp. And that is why thinking of success/fail metrics is a good exercise to do.
0 likes • 11h
@Manasa Shetty Thank you for sharing. (I am a big fan of Grammarly, and I think they've been doing a great job for a very long time.) Grammarly is a very interesting use case. It can use non-AI rule base algorithms for simpler grammatical errors, and use more complex ML models for other aspects like tone, sentence construction, etc. In other words, English language has a set of simple rules. But it also has a lot of nuances. Rules can be non-AI, and AI can help with nuances. You summarised this well: "The language is static, but its usage varies based on context, tone, country inter alia." +1 on Grammarly sharing suggestions/options and letting the user control what they choose. Also, if i remember correctly, Grammarly also gives a small description of what the error is or why it's recommending a specific change. That also helps the user feel in control. They're not only getting recommendations, they're also learning why their writing can be improved. Side note: when you build trust in your recommendations/product, users always feel better and in control.
Week 1, Activity 2: Personal Inventory
Submit your problem mapping here. 👇 How to Submit 1. Fill out the template from the essay 2. Post your response in the comments below 3. Read at least 2 other people's ideas and leave thoughtful feedback. Let's think this through. 👇
Welcome Aboard - Start Here - Introduce Yourself
Hey there, And a warm welcome to our vibrant community. This is where you start the journey towards making your dreams a reality. This community is not just about product management. Instead, it is about sharing your aspirations, your ambitions, your goals. And then learning the things that will help you achieve the same goals. And the best way to give back to those who helped you along the way is to pass it forward. Help others who are in similar situations as you were by guiding them and sharing the lessons that you learned in your journey So without further ado, let's do this. Let's do it together. Let's meet our professional goals and help others meet theirs. A short intro to this community: You will find three major sections: Community: where you can post and read all the posts on all topics (or choose to filter the ones that are of most interest) Classroom: this is where you will find all the courses and challenges. You will automatically have access to all the FREE resources and the paid courses that you've already bought. Events: this is where you can find a calendar of all the upcoming (and past events) you can RSVP, get access to sign up links and recordings. With that said, enough about the community, let's know you a little bit more. Tell us: - Where you’re from - What you do - What you’re looking to learn or achieve here - A fun fact about yourself Excited to grow and learn with you!
0 likes • 6d
@Manasa Shetty Hey Manasa, very nice to have you join us. Looking forward to learning together
0 likes • 6d
@Masahiro Teramoto Hey Masa, very nice to meet you (again). And looking forward to learning together.
Questions About Getting Started with AI PM Accelerator?
Confused about something? Don't know how Skool works? Not sure what to do next? Have a technical question about the course? This is the place to learn about it. Drop your questions in the comments below. No question is too basic. No detail is too small. Examples of Questions That Belong Here: - "How do I submit an activity?" - "What's the deadline for Week 1?" - "I don't understand the template for the activity—can you clarify?" - "Do I have to do all the pre-work before Jan 17?" - "I'm having trouble with Skool—how do I...?" - "When will I get the Slack invite?" - "What time are the live sessions?" - "I have a technical setup question..." We'll all questions (usually within 24 hours) Everyone benefits because the answer is here for others to find Don't overthink it. Ask away. 👇
1 like • 6d
@Pushkar Chhibber It's the AI PM paradox essay here
He Shouldn't Have Done This!
Last month, a PM friend told me he spent two sprints adding an “AI-powered” feature to his app. When I asked what it did, he said, “It summarizes user feedback.” I asked if users were asking for that. He paused and said, “Well... not really.” Sound familiar? Most PMs are using AI even when it doesn’t make sense. They want to stay relevant but end up chasing the buzz. The biggest mistake they make is starting with “How do we use AI?” instead of “Should we use AI?” Here’s a simple checklist to answer that second question 👇 ✅ Use AI when... ✚ The problem is ambiguous... there’s no single right answer. Example: writing ad copy ✚ You have lots of data to learn from. Example: recommending products, ranking content ✚ The task needs human-like judgment or creativity. Example: suggesting designs, reviewing resumes ✚ The system can tolerate small errors. Example: auto-suggesting captions, drafting emails ✚ AI can make it 10× faster, smarter, or more personal. Example: chat-based help desks, content assistants 🚫 Don’t use AI when... ➖ The task is deterministic... there’s one correct answer. Example: calculating tax, generating invoices ➖ You have little or no data. Example: brand-new apps, small internal tools ➖ The problem can be solved with clear rules or formulas. Example: filtering spam with keywords ➖ Mistakes are high-risk. Example: approving loans, medical diagnosis ➖ AI adds complexity without clear value. Example: replacing simple forms with generative chat I understand this can be overwhelming. Everything around you seems to need AI, and it’s easy to feel like you are missing out if you don’t add it. But the truth is not every problem needs AI. The real skill is knowing when it actually makes sense. Want to see this in action? We are running a FREE masterclass next week: 🗓️ 15th Nov | ⏰ 4:30 PM IST / 11 AM GMT 💰 Free entry | 🎟️ Limited seats Learn how to decide if your product idea really needs AI and get your AI Fit Checklist to test it yourself. Sign up HERE
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Sid Arora
5
280points to level up
@sid-arora-8035
Product Manager

Active 11h ago
Joined May 17, 2024
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