Something happened last Sunday that I've never seen before and I can't stop thinking about it. I hosted a 90 minute free masterclass showing how I build AI Agents. 90% of those who joined stayed until the end. Almost no one dropped off. That has never happened to me. And I've been doing this for almost 5 years. Here is what happened: 𝗪𝗵𝗮𝘁 𝗵𝗮𝗽𝗽𝗲𝗻𝗲𝗱. ~100 people showed up to watch me build an AI agent from scratch. In 90 minutes we built 4 agents: 𝗔𝟭: 𝗩𝗼𝗶𝗰𝗲 𝗿𝗲𝗽𝗹𝗶𝗰𝗮𝘁𝗼𝗿 An agent that learns your writing voice, style, rhythm from old emails. The goal: it writes like you and not like a robot. 𝗔𝟮: 𝗖𝗮𝘁𝗲𝗴𝗼𝗿𝗶𝘇𝗲𝗿: An agent that reads all incoming emails, categorises them, uses embeddings (so it understands what a message means instead of matching keywords) finds past similar emails. The goal: ↳ categorise new emails (sales, course, pricing, etc.) ↳ find past examples to use as benchmark 𝗔𝟯: 𝗗𝗿𝗮𝗳𝘁𝗲𝗿 An agent that does 3 things: ↳ Refers to A1 learning ↳ Finds older similar emails ↳ Refers to knowledge dot md to ensure it's stating only facts 𝗔𝟰: 𝗥𝗲𝘃𝗶𝗲𝘄𝗲𝗿 An agent that works as a pair with A3, and focuses on ensuring A3 has done a good job, and not deviated from any of the guidelines. It also checks facts and tone before anything reaches you. All of this in about 90 minutes. Work that used to take a team of engineers and weeks. 𝗪𝗵𝘆 𝗜 𝗰𝗮𝗻'𝘁 𝘀𝘁𝗼𝗽 𝘁𝗵𝗶𝗻𝗸𝗶𝗻𝗴 𝗮𝗯𝗼𝘂𝘁 𝗶𝘁. That was the free session. And it was good enough to hold a room full of busy people for 90 minutes on a Sunday afternoon. I keep thinking why that happened. It's not because I'm a great teacher. Five years of doing this and I've never had a response like it. The real reason is simpler: Everyone in that room knew that the real power is KNOWING HOW TO BUILD products with real value. And that anyone can do it. This wasn't true a year ago. It is now. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗻𝗲𝘅𝘁: I plan to do this more often. I am always building, and I plan to share my process instead of completed projects. The next showcase is on Sunday. 5th July. This time I'm building the content engine that runs my own social channels, newsletter, and all content needs. Live. Five agents that find the best-performing posts in your niche, rank them on real engagement, generate angles, and write the scripts. Then analyse what worked and get better every time. The content engine is just the example. The real lesson is how to build AI Agentic Systems You'll walk away with a detailed step by step guide to setup your own content engine. • Same as last time: live only, no replay. • Sunday, July 5. Free. 430PM IST • Put it in your calendar. Come build. • Link in the comments. (Here is exactly how the email agent system works. I use it for all my emails.)

Most AI product managers, AI buildersbuilding AI products, don't know what is context rot, why it happens, and how to prevent it. #1 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝗥𝗼𝘁 Your AI works well on short prompts and conversations. The longer your conversation gets, the worse the answers get. This drop happens even when you're still under the model's allowed context limit. So it's not a hard limit problem. It's a quality drop inside the limit. This is called Context Rot.

Most PMs ask: "How do we add AI to this?" The right question is: "Should we?" The 5-Check Framework helps you decide: 1. Is there a real problem? 2. Is this a problem AI can solve well 3. Do you have the data? 4. Is it okay if your product makes mistakes? 5. Will adding AI 10x the user experience? If you fail any check, reconsider adding AI to the product.

Everyone I talk to says the same thing. "I want to be an AI Product Manager, but I don't know where to start?" That lack of clarity is costing you. It is holding you back. You won't get to work on AI products. You won't get shortlisted for AI roles. You will watch engineers make product decisions, because you don't know enough to make good decisions. The gap between "traditional PM" and "AI PM" is widening. And the longer you wait, the harder it gets to cross. I spent 3+ years building AI products. LLMs, agents, systems used by hundreds of thousands of users. And then, I took everything and packed it into a 6-day email course. This is what it includes: Day 1 – What Does an AI PM Actually Do? Day 2 – The Only AI Concepts a PM Needs Day 3 – The 5-Gate Framework: Does This Need AI? Day 4 – AI Product Sense: Decisions Under Uncertainty Day 5 – The Eval Mindset: How AI PMs Measure "Good" Day 6 – AI Product Strategy: 3 Questions To Answer One email a day. 5 minutes. It teaches you exactly what you need to know today. The price: free. Sign up below

Give me 6 minutes I will explain the real meaning of 𝗔𝗜 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 I've been an AI Product Manager for a few years, and I have seen the first hand all the confusion around it. Here is the simplest way to understand it as of today (and the definition might evolve with time): An AI PM is responsible to do the following: 1. Problem discovery 2. AI feasibility 3. Data strategy 4. Model development 5. Integration and UI design 6. Testing, Deployment, Production monitoring 7. Iteration and improvement Let's break each of these down:

I'm going to keep this simple. I'm starting the black friday sale early. Get flat 40% OFF on our hottest product management courses: 1) Fundamentals of Product Management Learn the *real* way of doing product management. The course gives you practical tricks and frameworks that real PMs use to build real products. Original price: $300 Buy here: justanotherpm.com/product/fu… Bonus: with this purchase you also get a 40% OFF on our upcoming AI PM course. 2) PM Interview Toolkit Learn how to build a resume that gets shortlists. And learn how to craft the perfect answer for product sense, execution, and behavioural questions in PM interviews. Know what hiring managers look for in candidates. And get access 60 FAANG PM solved questions Original price: $100 Buy here: justanotherpm.com/product/pr… Use code: JAPMBFCM

Fact: AI is enabling product managers to launch features 10x faster. But here is an important question…. Do users care about how fast they get access to a feature? Or do they care about how seamlessly the feature solves their real problem? The answer is obviously the latter. Then why do so many teams still focus on velocity? This is because: Figuring out 𝗪𝗛𝗔𝗧 𝘁𝗼 𝗯𝘂𝗶𝗹𝗱 is hard. It is tough to get in touch with thousands of users. User feedback is spread across multiple systems. Analysis takes weeks. By the time data makes sense, the moment to act has passed. So teams default to speed and "gut feel". But the best product teams are different. They build processes and use tools to quickly and accurately identify WHAT to build. This is what their process looks like: 𝗦𝘁𝗲𝗽 𝟭: 𝗨𝗻𝗶𝗳𝘆 𝗳𝗲𝗲𝗱𝗯𝗮𝗰𝗸 They consolidate all customer conversations (support tickets, surveys, reviews, Slack messages) into a single source of truth. This saves time and effort by eliminating the need to switch between multiple tools for data collection. 𝗦𝘁𝗲𝗽 𝟮: 𝗨𝘀𝗲 𝗔𝗜 𝘁𝗼 𝗳𝗶𝗻𝗱 𝘄𝗵𝗮𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 They use AI that actually understands YOUR product and YOUR users to extract the real learnings, problems, and pains. The same tools find contextual data for each of the feedback points like impacted accounts, account size, risk, usage patterns, etc. It uses all of this to finally quantify the impact and prioritise the most important feedback. 𝗦𝘁𝗲𝗽 𝟯: 𝗔𝗰𝘁 𝗼𝗻 𝗵𝗶𝗴𝗵-𝗶𝗺𝗽𝗮𝗰𝘁 𝗳𝗲𝗲𝗱𝗯𝗮𝗰𝗸 Once the system identifies and ranks themes by impact, it then pushes the learnings to downstream workflows where the work happens, like JIRA tickets, Slack alerts, dashboards, and closes the loop. The beauty of this system is that it allows you to focus your effort on the right problems. If you’re facing a similar problem with too much or too scattered data, check out @enterpret_ai the Customer Intelligence platform I’m partnering with on this post. It unifies every piece of customer feedback, understands it in your business context, and helps teams act on what matters. That’s why Canva, Notion, Linear, and Perplexity rely on it to stop guessing and start knowing what to build.

I'm documenting answers to 50+ most frequently and recently asked interview questions at Google, Meta, Uber, Netflix, and many more... This will be part of the Product Management Interview course. Available for $50 now. Goes up to $100 on Monday. This is the highest quality database of PM interview questions and answers you will find on the internet. These are the exact answers I would give in a real interview. Don't believe me. Check out a sample answer before buying (link in comments)

Here is everything I know about the PM role in one document. It is yours forever, for free, no email required: docs.google.com/document/d/1… If you have questions on any aspect, leave a comment. I will respond to each one.

An offer no PM can refuse...

𝗬𝗼𝘂 𝘄𝗼𝗻’𝘁 𝗹𝗼𝘀𝗲 𝘆𝗼𝘂𝗿 𝗷𝗼𝗯 𝘁𝗼 𝗔𝗜. You’ll lose it to the product manager who knows how to use these tools better than you. I say this with love — and urgency. Most PMs are stuck doing work that 𝘴𝘩𝘰𝘶𝘭𝘥’𝘷𝘦 𝘣𝘦𝘦𝘯 𝘢𝘶𝘵𝘰𝘮𝘢𝘵𝘦𝘥 𝘮𝘰𝘯𝘵𝘩𝘴 𝘢𝘨𝘰. → Rewriting PRDs → Chasing customer feedback → Making the same deck 4 times → Sorting through user interviews → Creating A/B test plans from scratch And then wondering why they don’t have time to think strategically. I’ve put together a list of 14 AI tools that can help you: ✔ Analyse customer feedback faster ✔ Design better presentations ✔ Automate market research ✔ Run better experiments ✔ Prep for interviews ✔ Write better PRDs ✔ And much more This is not another AI Tools List. This is the AI STACK I use EVERY DAY! Save this post. Share it with your team. And most importantly, try at least ONE this week. Because the gap between “PMs who use AI” and “PMs who don’t” is getting wider by the day. -- P.S. Comment and share which AI tools you're using to make life easier. P.P.S. If you found this useful, you’ll love my newsletter. Every week, I share practical strategies to grow faster as a PM — with real examples, tools, and frameworks. 𝗝𝗼𝗶𝗻 𝟭𝟱,𝟬𝟬𝟬+ 𝗣𝗠𝘀 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝘀𝗺𝗮𝗿𝘁𝗲𝗿 𝗰𝗮𝗿𝗲𝗲𝗿𝘀 (Link in comments)

Over the last week, I got 100+ DMs from product managers. All asking some version of the same question: “How do I get my resume shortlisted?” So instead of replying to everyone individually… I built something better (and free). 👇 It’s a 2-part system: 1) 7 AI prompts to revamp your resume, make bullet points impactful, tailor to JDs, write better cover letters & outreach messages 2) A 6-day email course that shows you exactly how to build the resume that gets interviews And it is completely free. Here’s what the 6-day email course covers: 📩 Day 1: Why your resume gets ignored 📩 Day 2: How recruiters actually scan resumes 📩 Day 3: A formula make every bullet point more impactful 📩 Day 4: Four resume myths that are killing your chances 📩 Day 5: What hiring managers want to see 📩 Day 6: A proven 3-step framework to stand out It’s short. Tactical. No fluff. If you're job hunting, it’s the best 10 minutes/day you’ll spend. And yes—it’s free. Like this tweet, comment "resume", and I'll DM it to you. (Must be following)

Most product managers (no matter how senior) struggle to understand the real meaning of product strategy. They confuse it with product vision or roadmap or both. As a result, their career stops growing much sooner than they wish for. I've struggled with the same problem too. Over the last 2 years, I spent a lot of time learning about product strategy. And even more time applying those learnings to the real world. Today I'm sharing everything I've learned so far. Here is a collection of the top 70 resources that include The resources I consumed Detailed guides on real-world application Collection of templates that I use even today You can get all of them for free! Link in comments.