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Product Managers Face AI Identity Crisis

Key Points

  • AI is creating a uniquely severe identity crisis for product managers, more disruptive than the impacts felt in engineering, sales, marketing, or customer success.
  • While other functions have predictable AI roles—CS for ticket triage, sales for call coaching and email drafting, marketing for creative assets—PMs confront multiple, overlapping threats across product definition, insight generation, and execution.
  • AI can automate many PM deliverables such as PRDs and other documentation, but delivering quality still demands deep product sense, storytelling, and precise prompting to retain thoughtful, creative output.
  • Building AI‑driven products adds a layer of complexity because these products are inherently probabilistic, requiring PMs to manage uncertain behavior and edge‑case scenarios unlike traditional software.
  • Executives often push for rapid AI releases, while engineering teams are hesitant to commit to fixed deadlines on probabilistic systems, creating tension and further compounding the PM crisis.

Full Transcript

# Product Managers Face AI Identity Crisis **Source:** [https://www.youtube.com/watch?v=nQcy-YlYpng](https://www.youtube.com/watch?v=nQcy-YlYpng) **Duration:** 00:12:44 ## Summary - AI is creating a uniquely severe identity crisis for product managers, more disruptive than the impacts felt in engineering, sales, marketing, or customer success. - While other functions have predictable AI roles—CS for ticket triage, sales for call coaching and email drafting, marketing for creative assets—PMs confront multiple, overlapping threats across product definition, insight generation, and execution. - AI can automate many PM deliverables such as PRDs and other documentation, but delivering quality still demands deep product sense, storytelling, and precise prompting to retain thoughtful, creative output. - Building AI‑driven products adds a layer of complexity because these products are inherently probabilistic, requiring PMs to manage uncertain behavior and edge‑case scenarios unlike traditional software. - Executives often push for rapid AI releases, while engineering teams are hesitant to commit to fixed deadlines on probabilistic systems, creating tension and further compounding the PM crisis. ## Sections - [00:00:00](https://www.youtube.com/watch?v=nQcy-YlYpng&t=0s) **AI Sparks Identity Crisis for PMs** - AI is rapidly assuming core product‑management functions—like PRD drafting and strategic decision support—creating a multifaceted threat that leaves product managers uniquely unsettled compared to the more predictable AI impacts seen in sales, marketing, and customer success. - [00:03:10](https://www.youtube.com/watch?v=nQcy-YlYpng&t=190s) **PM Role: Glue Amid AI** - The speaker argues that product managers have historically served as the connective glue between engineers and stakeholders, yet AI advancements and expanding duties—such as prototyping and even coding—are blurring and stressing this already ambiguous role. - [00:06:29](https://www.youtube.com/watch?v=nQcy-YlYpng&t=389s) **Finding Meaning in Product Management** - The speaker urges PMs to use AI tools like ChatGPT for learning, prioritize projects that genuinely move the needle, and secure autonomy to prevent burnout and maintain motivation. - [00:10:14](https://www.youtube.com/watch?v=nQcy-YlYpng&t=614s) **Human Conviction Over AI Automation** - The speaker stresses that AI can assist with drafting documents and prototyping, but it cannot replace the leader’s personal judgment, stakeholder alignment, and responsibility in guiding projects and meetings. ## Full Transcript
0:00AI is causing a crisis for product 0:02managers. I don't think it's too far to 0:04say that PMs are the worst off of the 0:07job families around AI right now. And I 0:10say that being very aware that there are 0:13colleagues of mine in engineering, in 0:15customer success, in sales who would 0:18disagree with me in marketing who would 0:20disagree with me. That's okay. I want to 0:22talk about PM partly because I know it 0:24well. Done PM. I've managed PMs. I've 0:27led PMs. But partly because AI is doing 0:32more of the heavy lifting in the PM 0:35domain than most PMs expected and that 0:38is leading to a crisis of identity that 0:40is distinct and different from what I 0:42see when I talk to marketers to CS to 0:44sales to others who feel like their jobs 0:46are impacted by AI. Let me explain what 0:49I mean. If you're in CS, it's a very 0:51clear engagement model for AI. The AI 0:54comes and whatever your feelings about 0:56it, it's picking up triage tickets. 0:58That's just pretty much what it does. If 0:59you're in sales, the AI comes and it's 1:02listening in on calls and it's giving 1:03you coaching tips and it's maybe writing 1:05your out outbound emails, etc. Again, 1:07very predictable scope of engagement. If 1:09you are in marketing, the scope of 1:12engagement is similarly predictable, but 1:13it's about creative and asset 1:15generation. It is different with PM. And 1:18you guys give the PM you know a hug 1:20because for PMs there's multiple threats 1:23on multiple axes. Yes, we have the same 1:26thing that you guys have where it's 1:28about asset generation. So PRD 1:30generation, Clarvo has got a whole 1:32business around PRD generation and 1:34there's other assets that PMs are 1:36responsible for that AI helps with as 1:38well. So there's that whole skill set to 1:40master and by the way that is not an 1:42easy skill set because you have to 1:44retain your thinking, thoughtfulness and 1:47creativity but somehow work faster 1:49because of AI. There's product insight 1:53requires a mixture of data and 1:55storytelling genuine product sense 1:58product gut engineering competence. It 2:01was always hard and AI makes it faster 2:04but not necessarily better unless you 2:07really know how to prompt. So that that 2:09whole asset creation thing is very 2:10fraught for PMS but on top of that you 2:14have to build AI product which marketers 2:16don't have to do CS doesn't have to do. 2:18You have to figure out how to build AI 2:20product and AI product doesn't work like 2:22any other product guys. other products 2:24you can just sort of say this is what 2:27the product is and write the 2:28requirements and that's how we were all 2:30brought up if we were npm for a decade 2:32but not anymore now the product is 2:35probabilistic if you're building an AI 2:37product the product is it mostly does 2:40this but sometimes there are edge cases 2:42sometimes the product is we figured this 2:44out can you help us package it is not 2:48easy to build AI product especially when 2:50you couple that with the demands from 2:53executives where executives are 2:55expecting really rapid ships on AI. 2:58They're expecting deadlines and your 3:01engineering team is like not willing to 3:02give you deadlines on probabilistic 3:04products so often. So there's the 3:06product piece, there's the asset piece. 3:08Both of those are very tricky. There's a 3:10third piece that no other role has, 3:13which is that PM has always been a glue 3:17role. It has always been an in between 3:19role. In fact, it evolved out of the 3:21need to keep engineers out of meetings, 3:24which is why if your PM is in meetings, 3:25he or she is they're doing their job. 3:27But so much of that is now up for 3:31debate, isn't it? Because if it's just 3:34about giving information, can an AI do 3:36that? Yeah. If it's just about 3:39stakeholder management, can an AI do 3:41that? Maybe. Not really. If it's about 3:44persuading and aligning on a step 3:46forward with executives, can an AI do 3:48that? Definitely not. And so that 3:50there's this weird stakeholder 3:52management mess that PMs have always had 3:55to handle that they now have to handle 3:58with AI in ways that are not clear. And 4:01on the other side, it's getting 4:03increasingly blurry, too, because now 4:06PMs are expected not just to write 4:08specs, but to directly prototype. We're 4:11expected to write stuff up in lovable 4:14and show it. And maybe we don't write 4:16the PRDM, we just show the the 4:17prototype, right? Or maybe we go so far 4:20as to commit code using claude code and 4:23maybe an engineer reviews it or maybe 4:24codeex reviews or maybe claude code 4:26reviews it. But either way, we're 4:28writing code. We're vibe coding code. 4:30We're vibe coding our SQL statements. 4:32Maybe we're making small UX pieces we 4:34can just commit ourselves. PM has always 4:35been an ambiguous role. The fact that 4:38it's ambiguous is not new. The fact that 4:40it is under strain from so many 4:44different axes at once. The job itself 4:46is changing both with stakeholders and 4:48with engineering at the same time as the 4:51tools we use to do the job are changing 4:54at the same time as the definition of 4:56the role itself is changing as the same 4:58time as the products we build are 5:00changing. That is why PM is in crisis. 5:03That is why I know a lot of PMs who are 5:05walking away because it is just too 5:08hard. Don't worry, the first half of 5:10this video is all about how bad it is. 5:12But the second half is hope. The second 5:14half is words of wisdom from someone who 5:17knows AI pretty well and who knows PM 5:18pretty well on how we start to navigate 5:20through this as product managers, as 5:23product leaders. Number one, we need to 5:25start to get real comfortable with the 5:29technical aspects of LLMs. Increasingly, 5:32the career risk is hitting non-technical 5:35PMs harder. And I will go farther. It is 5:38hitting technical PMs who are not AI 5:40technical fluent. And that is different 5:43from saying I need to be a PM who can 5:45manage an AI product release. I'm 5:47talking about be a PM who understands 5:50when to enforce schema validation or 5:53not. When to have a library of tools 5:57versus having a large prompt in your 5:59agent. You want to be really familiar 6:01with the tradeoffs that go with building 6:04AI products. And in particular, you want 6:06to have a highfidelity mental model of a 6:08large language model and how it works, 6:11how agents work so that you can be 6:13helpful when you are in the room with 6:15engineers talking about tradeoffs 6:17because that is how you actually move 6:18the ball forward on product and 6:20eventually come back with relevant 6:23deadlines. So I think the first piece is 6:25you got to get technically fluent. 6:27There's I'm sorry there's no substitute. 6:29The good news is chat GPT is a great 6:30teacher. Uh it really is like you can 6:32ask ask chat GPT to give you a technical 6:35AI lesson every morning and schedule it 6:38and it will do that. Number two, make 6:40sure that what you are building matters. 6:42I say that because I think that another 6:45reason why burnout happens and 6:47frustration happens is that PMs are put 6:50especially now on projects that are 6:52unlikely to move the needle. And if you 6:54think, oh that's the nonI products, I've 6:56got news for you. AI products don't 6:59always move the needle either. In many 7:01cases, what burns PMs out is being asked 7:03to do an AI product that the CEO came up 7:06with on LinkedIn and they have no 7:07autonomy to manage that and they just 7:09have to push it through and good luck. 7:12So, get yourself into a space where you 7:14have a product that actually matters. It 7:19might not be an AI product and I'm going 7:21to tell you that that's okay. But it 7:23needs to be a product that you believe 7:25can move the needle. Even if it doesn't 7:26yet, you believe your involvement is 7:29enough to move the needle. And if that 7:31sounds like it's meaning making, it is 7:33meaning making. But that's the art of 7:35PM. If you're not motivated, if you're 7:37not energized, if you don't feel like 7:38there's meaning here, you can't convince 7:40your stakeholders. You can't sell the 7:42product, you can't believe in the 7:43product, you can't roadmap the product, 7:44and you cannot convince engineers on 7:46that. So yeah, it does. And I think it 7:48especially matters in the age of AI 7:50because so many of these AI products 7:52that PMs are being asked to PM. They 7:54tell me and I see are just AI washing. 7:58They're they're not any good. And that's 8:00so demoralizing. It doesn't help with 8:02your resume. It doesn't build value. It 8:04doesn't move the needle for customers. 8:06It discourages your engineering team. It 8:07doesn't teach you good AI best 8:09practices. So build what matters. Number 8:11three, make sure that you don't lose 8:14your product intuition. So AI is going 8:17to help you go faster. You're going to 8:19be asked to go faster and you're going 8:20to feel split between five, six 8:23different ways. How many ways can I 8:24write a Slack update? Can I use the AI 8:26to write the PRD for me, etc. The best 8:29PMs are basically treating AI as a way 8:33to extend their attention on less 8:35important tasks and they are keeping the 8:38things that matter, the taste, the 8:40judgment for themselves. They are not 8:43outsourcing that. If you have a hunch 8:45about your product and you're an 8:46experienced PM, follow that hunch. Take 8:49it seriously. Yes, AI can listen to and 8:53read through all of the transcripts from 8:55all of the customer calls, and that's 8:56great. And maybe it will surface some 8:58things you didn't see, and that's 8:59amazing. You have a product gut for a 9:01reason. And it is demoralizing to ignore 9:04it. It's death to your product gut. It's 9:06damaging to your future career. This is 9:08this is a craft skill, right? It's a 9:10fingertippy skill. That's something you 9:12learn in the shop. Don't lose your 9:15touch. Don't lose your product 9:16intuition. If you think it needs to 9:18launch now, it probably does. Just go 9:21with it. And I think that we sometimes 9:23misunderstand what AI is. We sometimes 9:25think because AI is something we're 9:27building something we're building with 9:29and also like apparently an AI colleague 9:31and also apparently involved in our 9:33meetings and stakeholder management that 9:35we should give it a lot more deference 9:37or trust then I think we should 9:40especially in product where you are 9:42responsible for setting direction and 9:43autonomy don't do that trust your gut 9:46trust your intuition you will get less 9:48burned out the product is going to be 9:50better and you will put AI in its right 9:53place as an assistant not a colleague 9:55that calls the shots. I'll tell you one 9:57more thing. Your job to drive alignment 10:00between engineering and leadership has 10:03not gone away, not eroded one bit. AI 10:05can't help you with it. And if you can't 10:07keep direction there and clarity there, 10:10your career isn't worth a plug nickel. 10:12That is the value. That is what you 10:14can't substitute any other way. And so 10:17make sure if you're working on something 10:19meaningful that you are putting the 10:21human work in to keep alignment with 10:23leadership and your technical teams that 10:26you can't have AI just write the deck 10:28and assume it's going to be right there. 10:30Right? You you can't have AI give the 10:33presentation. You are going to have to 10:35go in you are going to have to write the 10:37docs and the decks that work for you. 10:39And can AI help? Yeah, actually AI can 10:42help. But there's no substitute for your 10:44conviction that this is the right angle 10:46to approach an important meeting with. 10:48There's no substitute for your 10:49conviction that the agenda needs to be 10:50shorter because of X or Y stakeholder. 10:53There's no substitute for your 10:54conviction. The technical team needs two 10:57weeks more time and you have to go and 10:59get it. That's your job. And so when you 11:01look back and you look at sort of where 11:03you are now, the things that I'm 11:05emphasizing are things that you can 11:07trace a through line for the last decade 11:09plus. These are things we've always had 11:11to do, but I think they're things we've 11:13started to forget because AI is 11:15incredibly loud and in our faces all the 11:18time. I'm not saying don't use AI. AI 11:20tooling is great. If you can use AI to 11:22help you write better PRDs and one 11:24pagers and write better SQL and get into 11:26prototyping, that is all great skills 11:29that you can demonstrate that move the 11:31ball forward for your customers. Do it. 11:34Don't lean out, lean in. But you are 11:36leaning into AI to become a PM with 11:40these core skills that don't change like 11:43working with stakeholders, like aligning 11:45with leadership, like working on 11:46something that matters in a way that's 11:48new. AI is a tool in the toolkit. You 11:52are a craftsman and you can use AI as a 11:54tool in your toolkit and you should and 11:56you need to and the ones who don't are 11:58in trouble. But don't mistake that need 12:00to lean in for a need to lean away from 12:03these core values. Those don't change. 12:06And I think that I feel like this is 12:08missing. I feel like we don't have 12:09enough conversations about the core 12:11values in the job family. And that's why 12:13I'm putting this out there. They haven't 12:15changed. The things that make PM 12:17successful over time have not changed. 12:19AI is just a tool that we're using to 12:21get there. I hope this has helped. Best 12:23of luck with product. Well, if you 12:25stayed this long, you want to check out 12:27my product manager dice. I have I can 12:29roll this, right? And it says on the 12:30road map. It says no. It says plan for 12:34Q5. That's my favorite one. And uh it 12:36depends. I love that. So anyway, have 12:39fun, keep chuckling and uh stay in 12:41product is worth