Going from a team of product marketers to be the first dedicated PMM for a tech startup was a big transition for me. I knew I needed help from someone who had done something similar to navigate my role successfully. Yi Lin brought in amazing qualities as a coach—perspective, wisdom, and empathy (to name a few)—that propelled me to a new phase of my career and job where I felt empowered to tackle opportunities and challenges . I would strongly recommend her to other product marketers who want to learn how to grow in their PMM careers, harnessing the value of their experience in a new environment. Angelea Ennamorato Product Marketing Lead Yi Lin provided tremendous value to me as I moved from an individual contributor to a director role within product marketing. Her wealth of insights and best practices helped me quickly stand up and refine our PMM team processes, and gave me the framework I needed to build the most important bridges across our organization. She was an invaluable sounding board and coach as I built my confidence as a leader. I'm so grateful to have worked with her! Carley Stugelmayer Director of Product Marketing I had the pleasure to work with Yi Lin as one of her career coaching clients. Yi Lin was so helpful throughout the process - her communication was great, she was very empathetic to my specific career journey and she gave really great insights throughout the entire process. Working with Yi Lin, I was able to find a job within 3 months. Also, job searching is never easy, and I felt that her guidance helped to make the process a little less daunting. I have recommended her to friends and would certainly work with her again in the future. Carrie Silver Social Media Manager "I decided to work with Yi Lin after following her and getting significant value from her content on LinkedIn. This turned out to be one of the best decisions I have made for my career, as I landed my dream role I am super excited about, within 2.5 months after working with her, even in a tough job market! What I loved about working with Yi Lin is that her materials and instructions were value packed, straight to the point with zero fluff. This helped me articulate the value I brought and tell a cohesive story. It also ensured I focused on the most impactful activities in the job search process - allowing me to be efficient and conserve energy. One unique element of the program is that Yi Lin also has a supportive private community that provided an opportunity to connect with and learn alongside other talented individuals at all levels of seniority. And to top it off Yi Lin holds incredible group coaching sessions on a regular basis which supported me both with my job search and as a marketer. Some of the workshops she hosted include AI in product marketing, positioning/messaging, GTM strategies, to name a few. All in all, I received significantly more value than the investment, and the ROI is well worth it. Having worked with other coaches, I will say her coaching is far more valuable than standard programs which would not offer you the opportunity to refine your skills in such a way and learn with industry peers. I 100% recommend working with her if you need a helpful, empathetic guide along your job search and growth journey!" Cecilia Makinde Marketing Programs Manager, GTM Before I connected with Yi Lin, I felt overwhelmed by the prospect of my next job search. I knew I wanted a new challenge, but I wasn't sure where to start. Yi helped me gain clarity through insightful coaching sessions, asking powerful questions that helped me define my ideal role and career goals. Her one-on-one approach felt personalized and supportive, like having a cheerleader in my corner. She asked insightful questions about prior products that helped me completely revamp my resume, highlighting my strengths and achievements in a way that resonated with recruiters and hiring managers. She's also cracked the code for writing cover letters that land interviews; she helped me craft compelling narratives that showcased my unique value proposition. Yi Lin's library of resources and templates made my search process smoother and less daunting. The connections I made with other product marketing professionals in her community allowed me to build a valuable network that continues to offer support and advice as I prepare to dive into a new role. I am grateful to Yi for empowering me to take control of my career and navigate the journey with clarity and confidence. She was a game-changer for me, and I can't recommend her services highly enough. Christine Moore Director of Product Marketing, Forj "I chose to work with Yi Lin because of her sheer knowledge in the field as well as her genuine desire to help her clients work towards landing their dream roles. Despite it being a tough time in the job market, Yi Lin never once doubted that I would find a great role, which truly helped me maintain my confidenc e and calm as I continued my job search. With her help, I have been able to land a great role and I am truly excited to continue working with Yi Lin moving forward as I progress in my journey." Deepa Pillalamarri Customer Enablement Specialist As someone who has been managed and coached by Yi Lin, I’ve experienced first-hand her genuine commitment to my growth and transformation. Yi Lin hired me while at Teachable, and she has since been my biggest advocate, providing me with strategic expertise and coaching through complex situations and tasks. As a result, I continued seeking advice from her when she became a full-time coach. As a coach, Yi Lin masterfully blends clear communication, refreshing transparency, highly specific advice, and a positive mindset. After every session, I can better see the bigger picture, walk away with clear next steps, and--not to be underestimated--benefit from much-needed emotional guidance. In my view, Yi Lin’s effectiveness as a coach derives from a truly unique point of view informed firstly by her background as a career pivoter, not only once, but multiple times, which provides her with a deep well of empathy for people of diverse backgrounds who often experience myriad challenges on their journey; and secondly, her varied interests and backgrounds as an artist, consultant, and someone who has lived in many places, all of which make her keenly observant of people’s specific needs and superpowers. If you want to grow in your PMM career, I can’t recommend her highly enough, no matter your background. Don Atkins Product Marketing Manager Yi Lin’s coaching program transformed my job search. Her expert guidance taught me effective methods to focus my efforts for maximum impact. Working closely with Yi Lin on interview techniques was invaluable. Unlike other resources that simply give you questions and example answers, Yi Lin took the time to work through questions with me and helped me to understand how my experience could translate into answers that showcased how I was the best candidate for the role. This totally changed the game for me when interviewing. Thank you, Yi Lin, for equipping me to succeed! Gwen Kessinger Senior Product Marketing Manager Harry Dhaliwal Product Marketing Manager More specifically, I started working with Yi Lin after a layoff— she provided me with instant relief from our very first call. It was her expert understanding of the field and concrete strategy that helped to lift some of the weight off of my shoulders. I credit the ease with which I was able to land a new role that I love— within the time frame I set out for myself— to her coaching. She helped me identify my strengths and impactful stories to focus on in interviews, gave me feedback on my materials, created a supportive community of tech folks, and is my most trusted advisor. In fact, I have enrolled to work with her again as I enter a new phase as a product marketer. I highly recommend working with Yi Lin in any stage of your career. Attention anyone looking for expert support in their tech career: Like many others, I first came across Yi Lin's content on LinkedIn and noticed her name circulating as an influential voice in tech and product marketing. As I considered reaching out, I remember being uncertain of the level of support I would receive from a tech career coach -- would this be similar to prior job placement services that were too general to be useful to me? Absolutely not. As someone who has now completed a full coaching cycle and various workshops with Yi Lin I am 100% sure I made the right decision to schedule that initial call with her. Jordan Adler Product Marketing Manager, KickUp I am thrilled to share my experience working with Yi Lin - as her guidance played an instrumental role in helping me secure a coveted Product Marketing Director role that aligned perfectly with my goals. The journey was challenging, but the payoff was worth every effort invested. My objective was to transition from an enterprise setting to a startup. However, given the tough job market, I found myself facing a lot of rejections despite my experience. The turning point came with Yi Lin’s guidance on targeting only companies that fit my background and domain. Then, using her PSAR frameworks and highly personalized messaging house, my value was able to shine and I was able to stand out. Additionally, her program and community also allowed me to transform into a better product marketer. The exposure to diverse product marketing perspectives allowed me to improve my strategic thinking and point of view - an unexpected but welcomed outcome of this journey. The comprehensive support I received—from group meetings and guest speakers to practice interviews—was pivotal in preparing me for the challenges of my new role. I express my deepest gratitude to Yi Lin and her client community for their unwavering support, invaluable tips, and encouragement throughout this journey. Job searching can be isolating, but with this team, I never felt alone. Josh Porter Director of Product Marketing, Kore AI Yi Lin and I worked together when I was searching for my latest role and I would and have recommended her to anyone in the hunt who'd like an expert set of PMM eyes to help give them a leg up on the competition. I'm a very seasoned PMM leader, but she is a framework master and was instrumental in helping me clarify what I was trying to say. She was pivotal in taking my work from good to great and my investment in working with her has definitely already proven to have a positive ROI. Kelsey Kamp Director of Product Marketing, Marin Software TESTIMONIALS My Clients Say

Get the Ultimate Job Search Guide for Product Marketers to help you land more interviews, position yourself as the best candidate, stand out, ace assignments, and navigate the entire job search process with confidence. Looking to land a PMM role in 2026? Download this 20-page guide for concrete frameworks and tactical guidance to navigate each stage of your job search. Take charge of your job search with 20 pages of insights distilled from thousands of hours spent coaching over 150 clients. By providing your email address, you'll also subscribe to my newsletter. You can unsubscribe at any time, and I respect your privacy. Valentina Llinas Sr. Product Marketing Manager @ Cornerstone OnDemand "I had been in the hunt for 6 months already without luck, and by meticulously following Yi Lin’s process (trust her process!), I was fortunate to secure a role that checked all of my boxes within just 2 months! The confidence that Yi Lin’s approach provides is priceless and game-changing." What You'll Learn How to tailor your search to your unique strengths, values, and competitive advantage. How to position yourself as the best candidate and understand the most strategic way to apply. How to ace your interviews and take-home assignment based on what hiring managers are looking for. Get Instant Access to the Ultimate Job Search Guide for Product Marketers Now By providing your email address, you'll also subscribe to my newsletter. You can unsubscribe at any time, and I respect your privacy. Why I created this guide Waves of tech layoffs have made it more important than ever to stand out in the job market. If you’ve been applying to dozens of roles and haven’t heard back or you keep getting passed up for more experienced candidates, it’s time to get more strategic. This ebook consolidates insights from hundreds of hours helping clients land product marketing roles. I hope it can help you avoid pitfalls and build confidence as you navigate your search.

Download the first-ever report built by PMMs, for PMMs, based on insights from over 200 working product marketers. Inside, you’ll uncover how PMMs are actually using AI today: how often, for what tasks, and which tools they rely on most. You’ll also see how AI is reshaping core responsibilities, where the real risks and limitations lie, and where the field is headed next. Plus, get real prompts and use cases straight from the people doing the work. Download this report, the first of its kind, built by PMMs, for PMMs. Based on insights from 200+ product marketers , this isn’t your typical industry report. Inside, you’ll find: How PMMs are really using AI How often and for what The tools they rely on Impact on core responsibilities Risks, limitations, and what’s next Real prompts and use cases , straight from PMMs More than data and charts, this is a no-fluff guide to help you take action, whether you’re a new PMM, a seasoned leader, or somewhere in between. You'll also receive my monthly newsletter, with occasional updates full of practical tips and insights you care about. Unsubscribe anytime. State of AI in Product Marketing 2025 Report + Guide How is AI really changing the work of PMMs?

Sponsored by: GetWhys Why great products still lose deals PMMs are often asked to sharpen messaging, improve competitive positioning, and give Sales better tools. But most buyer feedback only captures what happened, not why it happened. GetWhys analyzed thousands of interviews with real B2B buyers to uncover the hidden forces behind complex purchasing decisions: internal pressure, risk, stakeholder vetoes, trust, and the need for a defensible story. This guide will help you look beyond surface-level loss reasons, uncover the real barriers to change, and learn how to turn buyer insight into stronger messaging, competitive strategy, and sales enablement. → Download it to understand how B2B buyers buy Nobody can find anyone “I know I’m qualified. So why have I lost out in FIVE final rounds?” I’ve heard some version of this from PMM job seekers all year. At the same time, I’ve heard the opposite from many of the startups I recruit for: “We know what we need. So why can’t we find the right candidate?” There’s a huge disconnect in this market: candidates can’t seem to land jobs, and companies can’t seem to find talent. The broader data reflects that disconnect. LinkedIn’s latest U.S. workforce report showed hiring down 7.5% from a year earlier. Indeed found that the average time from posting a role to making a hire had reached 49 days, the longest timeline since early 2019 – and even longer for tech roles (roughly 57 days) It seems impossible, but there are two reasons for this misalignment from my observations: Mismatch in talent and environment: employers take longer to fill roles because the experience available in the market doesn’t always match their hiring needs. Some startups want one PMM to do research, positioning, launches, enablement, and measurement with almost no infrastructure. That’s a very different job from being a specialist on a large team. Carta’s hiring data shows an additional complication: venture-backed companies are hiring far fewer people than they were at the peak, and later-stage startups are deliberately operating with smaller teams. Cautious hiring: Economic uncertainty, rapid AI-driven change, leaner teams, and risk-averse hiring have made companies more skittish, so even highly experienced PMMs are struggling to land a role. Marketing is feeling this especially hard. Indeed’s CMO recently reported that marketing job postings were about 25% below pre-pandemic levels. Through my PMM Job Search System, I’ve helped more than 100 PMMs navigate the hiring process, along with another 250 through earlier programs. I also see the market from the employer side through my recruiting company, 3AM Recruiting. Together, these perspectives give me a unique view into where candidates and companies keep getting stuck, and three roadblocks come up again and again. With the PMM Job Search System now open for Q4 enrollment till September 30, the timing felt right to share them. Today’s issue will help you identify what may be blocking your own PMM job search and what to do to land your next role. Even if you’re happily employed, these are useful questions to ask now, because the worst time to figure things out is after you suddenly need a job. So let’s dive in. Roadblock #1: Your positioning is too broad I see this all the time with experienced PMMs. They’ve done a lot, so they try to show all of it: research, positioning, launches, every possible keyword, and their ability to be a jack-of-all-trades. It may all be true, but the person reading their resume or LinkedIn is still left wondering: “Why is this person right for this particular role?” That’s especially difficult in this market. Hiring teams are being much more cautious, and many roles are being built around a very specific problem. They’re not simply asking whether you’re a strong PMM. They’re asking whether you’re the PMM they need for this particular company, stage, product, and team. If your story sounds broad enough to fit almost anywhere, the hiring team still has to connect the dots for you. Most won’t. This one is particularly interesting to think about through the lens of product marketing: would you ever be okay positioning your product to sound exactly like a competitor? You would never. But we do it to ourselves all the time, because we’re too close to our own skills and story. What to do: Get specific Fortunately, there are some objective ways to diagnose your own positioning and see spots for immediate improvement: Get targeted: Who’s your ICP? Determine the industry you want to work in, GTM motion to support, company size, skill set needed, and level of role. Define your unique value proposition: What can ONLY you bring to this company and role? What’s your particular human advantage that you’ve honed through a deep understanding of your strengths, values, and market needs? The result is that you begin to sound like a market of ONE. The goal isn’t to make yourself eligible for fewer jobs. It’s to make the right companies understand much faster why you belong there. The example below shows the difference between generic (candidate A) and targeted positioning (candidate B). If you were hiring for the candidate’s target company, which person would you choose? EXERCISE: Rate your current positioning How clearly can you explain why you’re the right PMM for a specific type of company? Use the scorecard below to rate your current positioning from 1 to 4. Key: 1 = You have no positioning statement at all. 2 = You’ve thought about it and perhaps used AI, but you aren’t confident in it. 3 = You’ve built something from a framework, but it still sounds like it could be applied to many others and doesn’t make your superpowers shine clearly. 4 = You have clear, differentiated positioning built from real ICP and background work. If you scored between 1 and 3, ask yourself: Which one or two types of companies are most likely to value my background, and why would they choose me over another strong PMM? If you can’t answer that clearly yet, your positioning probably needs another round of refinement. That’s normal. We’re often too close to our own experience to see what is most differentiated and relevant. Once your positioning is clear, the next challenge is communicating it effectively in interviews. Roadblock #2: Forgettable interviews It’s rare to meet someone who genuinely loves to interview. Interviews are generally nerve-wracking and most people don’t like them. As you grow in your career, they also become more challenging, because the more experience you have, the more it is really about how you communicate your expertise (not just having expertise). While it sounds counterintuitive, your experience can actually start to work against you: you begin to default to explaining what you did in a prior role vs. thinking through THIS company’s situation. This matters even more when companies are hiring cautiously. They aren’t only listening for evidence that you’ve done the work before. They’re trying to reduce risk. They want to understand how you think, whether you can diagnose their problem, and whether your judgment will transfer to an environment that may look very different from your last one. What to do: diagnose the business before answering Most candidates prepare for interviews by rehearsing questions. Yet there is much more to interview preparation than practicing answers to the same 20 to 30 questions with an AI coach. In order to succeed at interviews, you need to master three things at once: adopt a consultative approach, use a clear structure for your answers, and practice delivery. #1: Consultative-style approach Imagine that the company you’re interviewing with has already hired you as a consultant to come in and solve their problems. They’ve bought into your expertise and expect you to come in with a point of view on THEIR unique situation. Trying to spend hours predicting and practicing for every possible question they might ask is a losing game. Instead, do your research and determine why this role exists, what problem(s) they need this person to solve, and where the gaps might be. This will help you determine what facets of your experience matter most, and your answers will automatically be much more focused and relevant. What this looks like in practice: Research the company, role, and interviewers. Conduct a PMM audit: what can you tell about their current state of product marketing based on their website, LinkedIn, product reviews, and other publicly available information? Create your unique personal story based on the positioning that you nailed in the prior section. Prepare for the five to seven questions the team is most likely to ask. Use the PSAR framework to craft your answers. More on that below. Prepare objection handling. Prepare questions for each interviewer based on their role and what you’ve learned throughout the process. #2: PSAR structure for answering questions Once you have prepared and researched the company, your responses will automatically sound more relevant. But you also cannot just ramble on or word vomit. This is why using a framework to structure your responses is important. You’ve likely heard of the STAR method for answering interview questions: Situation, Task, Action, Results. This framework is actually not ideal for PMM interviews. For one thing, the “situation” and “task” pieces tend to take too long to describe and can usually be combined. For another, and most critical, it ignores the most crucial piece for PMMs: the process. I’ve developed a framework a few years back specifically for product marketers called the PSAR framework: Process, Situation, Action, Result. Let’s take a look at how this works, and what it might sound like in a real-life scenario for a question that lots of PMMs get and struggle with in interviews: “What metrics do you use to measure the impact of product marketing?” Step and explanation Real-life example Process: Start by walking through the process, which helps show systems-level thinking and makes it easier to follow along. “Lots of people think about attribution, but I prefer to measure my success based on contribution. I start with the business goal, then figure out where the biggest focus in the funnel is. From there, I determine which upstream marketing metrics I can influence, and then create that contribution story.” Situation: This combines the task, situation, challenge, project, goal, etc. – which should be a short statement. “At my last company, revenue was the top priority. When I dug deeper, it became clear that pipeline creation (middle of funnel) was the real bottleneck. My job was to show how PMM could help fill that gap.” Action: This is where you dive in to provide detail of how exactly you did it, by following the process you laid out earlier. Call out specific steps (1, 2, 3, or who, what, when), and a specific, memorable insight to show the WHY. “I partnered with Demand Gen on a tier-one launch focused on new AI capabilities, which I knew would bring in a lot of pipeline. We developed a highly innovative strategy centered on influencer activation. I then built messaging and assets for high-priority segments, as well as enablement for Sales and all our influencers. To measure my impact, I tracked: Content engagement (deck usage, webinar attendance) Sales and influencer feedback on assets And other channel metrics And I regularly shared updates on how this work supported pipeline goals.” Results: End with showing the impact and the result you generated, and any learnings. “The launch drove a 25% increase in marketing-sourced pipeline that quarter. Sales adoption of my assets was 80%+, and AEs called them out in all-hands as helping accelerate deals. The influencers gave me shoutouts in our Slack channel for having delivered a comprehensive prep doc. Beyond the numbers, I built a repeatable way to connect PMM contributions back to business outcomes.” You can clearly see from the example how this framework helps you stand out amongst candidates due to the focus on process, action, and results. #3: Deliver with presence and control Of course, preparing the content of your answers is only part of it. You need to be prepared to deliver those answers confidently. Because the best answers and examples in the world do you no good if you can’t communicate them effectively. Contrary to what some people believe, interviewing well is not a natural talent you have, or you don’t. Anyone can develop it. But it takes work. The advice sounds simple; the hard part is making it happen. While I can write another newsletter just about delivery, here are a few top tips for you: Lead with the main point. Don’t bury the lede. Give enough context, stay on topic, and then focus on the decisions and tradeoffs that actually mattered. Treat the interview like a conversation, not a memorized monologue. Remember the consultative style here: you’re sharing your point of view and expertise, and pausing to let the interviewer share their own thoughts. The seniority of your communication needs to match the seniority of the role. That means you need to demonstrate leadership presence and executive presence the higher up you go. EXERCISE: Diagnose what’s not working Here’s a quick exercise to assess your interview delivery. After each interview, reflect on where you rambled, where your thinking became unclear, which stories didn’t land, and when your confidence shifted. Use the questions below to identify what you need to practice: Your answers above will help you focus on where to practice instead of starting from scratch every time. The way you practice also matters a lot. Practicing with a friend or even someone else in product marketing probably won’t do much for you here since this person isn’t well-versed in what you’re trying to achieve. This is also why structured feedback matters. It’s very difficult to hear your own rambling, missing context, or shift in confidence while you’re in the middle of answering. Roadblock #3: Show, don’t tell Finally, remember: companies hire people to solve problems and grow the business. The person interviewing you cares about your background and experience through the lens of what it means for them: Can you solve their problems? Can you move the needle? That’s why the more you can SHOW the proof, rather than simply talk about what you’ve done, the easier it is for them to picture you succeeding in the role. This is where otherwise strong candidates can still lose out late in the process. They’ve explained their experience well, but the company is still left wondering: What would this person actually do here? Especially in a risk-averse market, a relevant piece of proof can close that gap and make the decision to hire you feel much easier. What to do: give them something concrete to react to This means choosing one useful, bounded way to demonstrate how you think about a problem the team has already told you matters. One candidate I was helping got to the final interview rounds for a role he REALLY wanted, so he used that last interview to show the company that he was exactly the person they needed. You can do the same. Use what you’ve learned: Throughout the process, my client had gotten information about the company, their gaps, and challenges. He remembered they struggled with the question of “build vs. buy” for their tools, so this is where he focused. Solve their problem for them: He built a tool to help them make these decisions, a vibe-coded ROI calculator they could apply in these situations. Show them how much they need YOU: He showed the calculator in his final interview with the CEO, who then shared it with the entire company right after the interview. THAT’S the kind of impression you want to make: the ability to solve problems even before day one. The example also demonstrated his AI fluency. Strong candidates explain where AI creates value, which work still requires human judgment, how they validate its output, and how the workflow improves the quality or speed of the work. AI should strengthen the proof of how they think, not become the hero of the story. EXERCISE: Rate your readiness Think about your interview process today and how prepared you are to “show vs. tell.” Use the following questions to assess where you are and see where the gaps are: The most useful proof helps the hiring team reach a specific conclusion: “This person understands our problem, and I can see how they would work here.” Want help putting this into practice (and finally land your next PMM job)? If this newsletter helped you spot where your search may be getting stuck, that’s a good place to begin. The harder part is looking at your own experience and deciding what to change: which roles to pursue, how to tell your story, what to say in an interview, and what proof would actually matter to that hiring team. That’s the work we do in the PMM Job Search System. You’ll have a process to follow, a 1:1 session with me, live group coaching, and other PMMs to learn alongside. For this Q4 cohort, I’m also adding an October workshop on how to demonstrate AI fluency and build a portfolio project that helps show how you think. Enrollment closes September 30. If you’re searching now and want support applying these ideas to your own situation, you can learn more and join here. You’ve got this! Yi Lin

Sponsored by GetWhys AI can create the content. GetWhys helps you validate it. AI can draft a blog post, campaign brief, or set of sales battlecards before your coffee cools. But speed doesn’t tell you whether the content reflects what buyers actually care about. That’s the gap GetWhys fills. It validates your positioning and content against a proprietary database of real buyer interviews, with citations included. You can bring GetWhys an early idea and leave with content grounded in buyer intelligence. Through an MCP, GetWhys can also work inside the AI tools your team already uses. That means buyer validation can become part of your existing workflow, without adding another tab or disconnected tool. → Explore GetWhys’ buyer intelligence I've gone quiet for the last two months, and I want to tell you why. I’ve been busy building the AI PMM Academy, which I introduced in my last newsletter and is now officially open for applications 🚀. I talked about protecting your moat (the thinking, judgment, and relationship-building that actually make you valuable) and shared a practical framework for applying AI to product marketing workflows. That newsletter led more than 100 of you to join the waitlist and complete my survey. I also spoke directly with several PMMs who were interested in the program. Gotta do my own buyer research, right? :) Those conversations have directly shaped what I’ve built. Today, I’m going to share three things: How I think AI should be applied to product marketing A look inside the AI systems powering workflows built by three experienced PMM leaders, who also happen to be the Academy mentors More information about the first AI PMM Academy cohort *A quick note before we dive in: the insights I'm sharing today are drawn specifically from the first two sessions of our 11-week program. This newsletter will give you the mental model and a few real examples. Inside the program, we'll go much deeper into how each component works, how to build it, and how to apply AI to your own PMM workflows, from research to launches and more. Let’s get into it. Why downloading another AI Skill usually doesn’t solve the problem Most of the advice about AI and product marketing falls into one of two categories. Highly prescriptive: here’s how to set up Cowork, here’s a content writing Skill, and here are the steps to follow. Highly conceptual: here’s why AI matters, the mindset shift you need to make, and what the future of product marketing might look like. Both are useful. But there is still a large gap between understanding what’s possible and making it work reliably inside your own company. I saw this problem in my own experimentation, so I asked my LinkedIn community a simple question: Are the AI Skills you’ve downloaded actually working for you? The post generated more than 100 comments and replies. The consensus was remarkably consistent: Out-of-the-box Skills are useful for inspiration only. They can give you ideas, expose you to a better process, or provide a starting point. But they rarely work perfectly inside someone else’s company. For any Skill or workflow to work well, it needs to understand your: Product, market, buyers, and internal language Existing processes and how work moves between people and systems (internal logic) Standards for what a trustworthy, useful output looks like Reliability comes from testing and refinement - Longer instructions don’t automatically lead to better outputs. They can consume more context, create confusion, and make the workflow harder to maintain. The PMMs getting the best results weren’t creating one enormous instruction file. They were testing their systems on real work, identifying where the outputs broke, tightening the instructions, and adding clear verification steps and human checkpoints. Successful builders begin with their own workflow - The most effective process I saw was: Choose a repeatable task you already understand. Build the first version around your existing process. Test it through actual use. Compare it with relevant third-party examples. Incorporate only the ideas that meaningfully improve your system. You need to understand the work before you can reliably turn it into a workflow. This is especially important in product marketing, where so much of the work depends on judgment. AI can help you execute, analyze, and scale, but it still needs a strong PMM process underneath it. The mental model behind the AI PMM Academy The LinkedIn discussion and my waitlist survey reinforced two conclusions for me. First, PMMs are experimenting with Skills, Cowork, connectors, Projects, and other tools, but many still lack a clear understanding of how these pieces work together. Second, the most useful AI systems have to be built progressively around your company, expertise, and way of working. That is the thesis behind the AI PMM Academy. We start by grounding you in the principles of good PMM work and showing you how the core Cowork building blocks fit together. Then you’ll build your own context layer and apply it across the actual PMM workflow, from research and positioning to launches, enablement, and measurement. Let me give you a preview of that foundational layer. Foundations of great product marketing Great product marketers bring together three types of capability: Core product marketing expertise Visibility, influence, and emotional intelligence Business judgment and strategic thinking But the reality of the job rarely matches that expectation. A significant amount of our time is consumed by busywork: meetings, coordination, context switching, formatting, information retrieval, and other repetitive work. That is the gray box in the visual below. The initial goal of using AI is to reduce that gray box, and then enhance the quality of the work in the other boxes. You want to move faster through the repetitive parts of your job so you have more capacity for the work that requires judgment, influence, creativity, and strategic thinking. As your system becomes more reliable, you can also extend it beyond your individual work. Your team, sales organization, or broader company can begin benefiting from the expertise you’ve made more accessible and repeatable. Why Claude Cowork is best for creating AI product marketing workflows I’ve always said the thinking matters more than the tool. I chose Cowork because it’s the best environment for applying strong PMM principles to real work. (ChatGPT Work operates similarly, and many Skills are interchangeable, but most PMMs have access to Cowork at work, so that’s what we’ll use.) Cowork helps move AI beyond a single conversation and makes what I described above possible through agentic workflows. Instead of relying only on prompts and responses, Cowork can work through multi-step tasks, access relevant files and tools, and take actions within a defined process. There are three core pieces to understand. Connectors - Connectors allow Cowork to reach the tools, files, and information you already use. This helps it work with your actual business context instead of operating in a vacuum. Skills - Skills are reusable sets of instructions that tell Claude how to perform a particular task or process. You don't have to explain the entire process again every time. Once the Skill has been built and tested, Claude can reuse those instructions and produce more consistent results. As mentioned above, many people get Skills wrong. The best Skills should be created from your manual workflow based on your context. Context engineering - Context engineering is the practice of deciding what information Claude needs to do useful work. That might include your ICP, personas, positioning, product information, competitive landscape, voice principles, internal terminology, or examples of strong previous work. The challenge is giving Claude enough relevant context without overwhelming it with information it doesn't need. The three foundational elements of Claude Cowork Together, these pieces give Claude a more consistent foundation for doing the work. But the building blocks alone don't create a good system. You still need to decide: - What problem is worth solving - What context is actually relevant - How the work should move from one step to another - What Claude needs to verify - Where human judgment still matters This is where your PMM expertise and specific needs become essential. How three experienced PMM leaders built their foundations The right setup will look different depending on your company, role, product, operating model, and personal way of working. That is why I don't believe there is one universal AI setup for product marketers. To demonstrate this, I'm going to show you how the three AI PMM Academy mentors have built their foundations. They use many of the same components, including context, Skills, and connectors. But their final systems look distinct because they were designed to solve their specific problems. A quick note on scope: I’ll be sharing just enough of the architecture to help you understand the business problem it solves, the reasoning behind the design choices, and the measurable impact it has delivered. During the Academy, the mentors will walk you much deeper into how the various pieces of their setups work together. Mara Taylor: Building around productivity and alignment Mara is an experienced founding product marketing leader who built the product marketing function at Kenjo, a workforce management platform that helps SMBs manage scheduling, time tracking, payroll preparation, and other HR operations. Her setup began with a very human problem: attention. Like many PMMs, Mara was moving between strategic projects, stakeholder requests, Slack conversations, meetings, collateral, and constant follow-up. The information existed, but it was distributed across too many places. Every time she returned to a project, she had to reconstruct what had happened and where she had left off. The logic behind her setup Mara built two connected layers. The first is a personal productivity system that helps her capture and retrieve the context behind her work. The second is a company-wide marketing brain that makes Kenjo’s strategy, ICP, positioning, product information, and collateral more accessible and consistent across the organization. This dual setup allows her to both improve her personal productivity and set up PMM workflows that can scale to other parts of the company. Context At the company level, the “Marketing Brain” contains: ICP and market context Marketing strategy Positioning and messaging Product information Customer and sales insights Approved collateral and brand standards A screenshot of Kenjo's Marketing Brain Example Connectors Mara's setup has 20+ connectors. Here are a few: ClickUp: Acts as Mara’s operating system for projects, tasks, and project context. Slack: Provides the requests, conversations, and decisions behind the work. Confluence: Houses the company-wide Kenjo Brain, including the marketing strategy, ICP, positioning, and other core PMM context. HubSpot: Provides sales, pipeline, and win-loss data for strategic analysis. Product code and roadmap: Help Mara understand product capabilities and represent them accurately in messaging and collateral. Figma: Connects working files and final deliverables back to the original project context. Example Skills Mara's system has dozens of skills that are personal and shared. Here are a few. Getting Things Done: Creates and updates ClickUp tasks while preserving the relevant source links, decisions, and project context. End-of-Day Review: Summarizes completed work, upcoming priorities, and time spent on versus outside current projects. Copywriting: Applies Kenjo’s brand standards, banned language, and “anti-slop” patterns to new content. Kenjo Brain: Retrieves approved company, product, and marketing context from Confluence for use across new projects. What this unlocks Her productivity workflows allowed her to save a significant amount of time and reduced her context switching. This allowed her more time to make better strategic decisions for her organization. For instance, while reviewing Kenjo’s ICP, Mara connected Claude to HubSpot data and did some quick win-loss analysis that showed that the company’s planned focus on one specific sector was underperforming, while another sector was showing much higher win rates. She successfully brought the evidence to sales, marketing, and leadership to reconsider the company’s direction. What we’ll explore inside the Academy Mara will help us explore how to reduce context switching, build sustainable personal AI systems, and decide which parts of our work should remain intentionally human. We’ll also examine how these systems can extend beyond individual productivity into stronger team output, cross-functional alignment, AI adoption, and data-informed strategic decision-making. Natalie Marcotullio: Building around repeatable problems Natalie Marcotullio is the VP of Marketing at Navattic, a demo automation platform that helps SaaS companies create interactive and AI-guided product experiences for buyers. She has helped build the marketing organization from the company’s early stages. Her setup reflects the way she approaches AI: she experiments, identifies problems that keep recurring, and then decides which ones are worth turning into reusable systems. The logic behind her setup Navattic has several products, personas, and types of launches. Creating a new piece of content often requires pulling information from product documents, finding the right customer evidence, identifying the relevant persona, and applying the company’s brand guidelines. Natalie created a central Marketing Strategy Skill that brings this context together and provides a consistent foundation for the rest of the team. Screenshot of part of her Marketing Strategy Skill Context The most important contexts are all saved within the company's Notion site, and they include: Company and marketing strategy Product information and launch messaging The relationship between each product and target persona Brand voice and writing guidelines Approved customer quotes and stories More than 1,000 G2 reviews Much of this information stays in the Notion systems where the team already maintains it. The Skill retrieves the most current context rather than relying on one large, static document. Example Connectors Natalie's system connects to more than 30 different tools. Here are a few: HubSpot: Leads and MQL data. Salesforce: Opportunities, customer records, and event contacts. Linear: Product tickets, launch information, completed features, and internal demo requests. Slack: Lead activity, event notes, internal updates, and drafted team communications. Navattic: Demo performance, top-performing demos, and newly created demos. Sanity: Navattic’s CMS, including customer quotes, case studies, blog content, and article updates. Customer.io: Launch emails, in-app messages, and existing campaign automations. These connections allow the system to work with real product and customer information while reducing the risk of inventing quotes or using outdated messaging. Example Skills Natalie's system has 15 skills. A few examples of what Natalie has built: Marketing Strategy brain: Pulls live product messaging from Notion and customer proof from Sanity and G2, giving her other workflows a consistent foundation. Weekly Pipeline Analysis: Cross-references Ahrefs, Profound, HubSpot, and Salesforce to calculate weekly changes and flag significant swings. SEO and GEO Report: Reviews search and AI visibility, identifies underperforming content, and drafts recommended updates for Natalie’s approval. P2 Launch Creator: Duplicates an existing Customer.io campaign and drafts the email and in-app messaging for a new feature. Event Follow-Up: Finds event contacts across Vitally and Salesforce, then drafts customer emails or internal CSM notes for review. Customer Newsletter: Pulls recent product updates from Notion and Linear, lets Natalie select the stories, and turns them into a monthly or quarterly draft. What this unlocks Natalie’s system allows people across the marketing team to create stronger work without needing to begin with an empty chat or ask product marketing to locate every piece of context. It also gives Natalie more time for creative experimentation. That reclaimed time creates room for projects like Navattic’s digital customer scrapbook to be used for their upcoming major agentic product launch. Natalie used AI to plan the experience, structure the customer data, help build the website, and create a working prototype. Screenshot of one page of the Digital Customer Scrapbook created by Natalie for a Tier 1 Launch The value of the system shows up in both directions: routine execution becomes easier, and the team gains more capacity for work that is creative, differentiated, and difficult to standardize. What we’ll explore inside the Academy Natalie will help us explore how to identify recurring team-wide problems that are worth systematizing, build reusable Skills around them, and apply AI across launches, customer storytelling, content creation, and cross-functional execution. Her role as marketing leader gives a unique lens into where we can amplify results beyond PMM to the entire marketing team. We’ll also examine how to preserve experimentation and creativity as more of the repeatable work becomes easier. Natalie has built a really strong and authentic personal brand around the innovative product marketing and marketing work she has done. Mike Hetrick: Building for trust and quality at scale Mike brings more than 20 years of experience across engineering and product marketing. He previously led the global PMM team for Tableau’s $1B enterprise analytics platform at Salesforce. Today, he is building product marketing from the ground up as a founding product marketing leader at Meta Integration Technology, Inc., an enterprise metadata management provider that helps organizations connect, catalog, govern, and understand data, analytics, and AI. He also began his career as a data engineer, which becomes very obvious when you look at how he has approached his AI setup. 😉 The logic behind his setup Mike’s central problem was how to build an AI system that has the right guardrails in place. His company had decades of knowledge distributed across different files, and outdated information could easily find its way into new AI-generated work. He approached the solution like infrastructure: create a governed source of truth first, by building a really strong context layer, then designing workflows on top of it. Context Mike keeps what's true (facts), what's allowed (process/rules), and what it sounds like (voice) in different documents, because each changes on a different cadence and breaks in a different way if it drifts. Company facts and business strategy Marketing strategy and 12-month plan Positioning, messaging, and platform narrative Personas and audience-specific context Launch plans and narratives Voice, style, and editorial standards Mike stores this context in a version-controlled repository using Github, which allows him to update information at the source and track what has changed. He then uses Obsidian to provide him a visual map of how the different parts of the marketing brain (i.e., the context layer) relate to one another. Mike's Marketing Brain visualized in Obsidian Example Connectors Google Drive and Notion provide access to working documents. Exa supports deeper web research and voice-of-the-practitioner analysis. Firecrawl monitors and compares competitor websites. Example Skills An editorial process audits content against approved claims, banned language, required terminology, embargoed names, and brand standards. A Persona Council reviews content from the perspective of four different buyers. Additional Skills use the company context to produce and refine content consistently. What this unlocks With this foundation in place, Mike can scale his content without lowering the quality bar. He is building an entire content engine capable of producing one substantive blog every week through the end of the year, with every piece checked against the company’s approved messaging, editorial standards, and buyer personas. The same system also helps him monitor more than 200 companies and identify when competitors change their positioning, messaging, or website language. What we’ll explore inside the Academy Mike will help us examine how to build a trustworthy context layer and apply it across competitive intelligence, positioning, messaging, persona validation, and scalable content creation. Summary Mike, Natalie, and Mara use many of the same building blocks, but they have created three different systems. Their systems emerged from the work they were already doing. They were created from asking questions such as: - What problem in my work is worth solving? - What context does AI need to help me solve it? - What part of the process should become repeatable? - Where does a human checkpoint matter? - What should I deliberately keep manual? - How will I know whether the system is improving my work? That is the kind of AI fluency I want to help PMMs develop. It means knowing how to design the right system around the work you're actually trying to do, even as the tools continue to change. You don’t have to AI alone: Join the AI PMM Academy I hope these examples have piqued your curiosity and given you a glimpse into what we’re going to cover in the AI PMM Academy. I also hope they’ve inspired you to think about AI for product marketing the way I teach it: by starting with the core product marketing principles and problems to solve, and determining your AI strategy from there. I built the AI PMM Academy very deliberately to be small, cohort-based, and example-driven, because however advanced someone’s setup is, this IS still new, and we ARE still all learning, and the best way to do that is to learn from one another. I say it all the time, but it bears repeating: AI is the tool, not the outcome. Its purpose is to offload the busywork so you can focus on the best parts of being a product marketer. And that’s exactly what this program will do. In just a few months, you could be operating in a setup like Natalie’s, Mara’s, or Mike’s – and the AI PMM Academy will get you there. Yi Lin 💜

Introducing: The AI PMM Academy I'm launching the AI PMM Academy: a program for PMMs to hone their craft alongside peers and learn how to use AI in a way that amplifies, not replaces, their expertise. I'll share more at the end of the newsletter. ​ AI anxiety I've spent the last few weeks traveling to events and meeting PMMs, leaders, VCs, and founders. Everywhere I've gone, the conversation eventually turns to AI. There have been thoughtful discussions about how AI is changing our roles, GTM motions, and the way work gets done. But one thing has become increasingly clear: nobody has it all figured out. Even at the largest companies, people are navigating uncertainty with little guidance, evolving expectations, and very few established playbooks. Beneath all the excitement, there's a shared concern that we're somehow missing something important. Of course, that doesn't stop the AI hype machine from churning. This LinkedIn post I wrote resonated with many people, perhaps because it acknowledged the importance of AI without stoking fear. The message was simple: the skills that matter most haven't disappeared. Storytelling, judgment, relationship building, workflow design, and business acumen still matter. In many ways, they matter more than ever. That observation has only become stronger the more people I talk to. The PMMs getting the most value from AI aren't necessarily the ones chasing every new tool, building the most sophisticated workflows, or spending all day on social media. They're the ones with strong fundamentals who are using AI intentionally. I’ve written about AI before (here and here), but for this issue, rather than give you another list of tools or templates, I want to share the framework I've been using to think about using AI to become a better PMM. It starts with two principles: Protect your moat. Protect your human intelligence. It then walks through exactly how I think about applying AI in product marketing today. But first, let's start with what matters most. Principle #1: Protect your moat Before we talk about AI, we need to talk about something more important: why your role exists in the first place. Companies don't pay PMMs to generate content. They pay PMMs to create clarity and help products succeed in the market. That's your moat. And contrary to what some people fear, AI doesn't diminish that moat. If anything, it makes it more valuable. As AI becomes more capable, the quality of your human judgment matters even more. Here's what that moat looks like in practice: Telling the best stories - AI can't decide which customer insight matters most, which narrative will resonate, or how to connect a product to a larger business problem. That's why even AI companies are hiring storytelling leaders. I've seen the same thing in recruiting: the best PMMs now command up to $50K in salary increases due to their storytelling/positioning abilities. Setting the bar for quality - The flood of AI-generated content has made judgment more important, not less. Your value isn't producing more content. It's knowing what's worth publishing, what's incomplete, what's misleading, and what will actually resonate with customers. When there is more and more slop on the market, the role of the “quality checker” becomes more important. Being the strategist - You can ask Claude to build a launch plan in seconds. The problem is that it won't know your internal dynamics or how to be original in reaching your customers. That’s why we end up with many cookie-cutter, checklist-based launches that don’t move the needle. Strategy requires context and first principles thinking. Being the connector - This may be the most important moat of all. Companies are made of people, and people are messy. AI can't tell you which AE is the right partner for a pilot program, convince your CPO that a roadmap change is necessary, or navigate the complex stakeholder dynamics that make or break great work. Influence remains one of the most valuable skills in business because it is one of the hardest to automate. Principle #2: Protect Your Human Intelligence Understanding your moat is only half the equation. The next challenge is protecting the thing that powers it: your human intelligence. Something nearly everyone brought up with me is the AI brain rot. While the risk of AI replacing your job is real, the risk that your brain’s function will decline over time is significantly more dangerous, with lifelong consequences. This is because your skills in storytelling, judgment, strategic thinking, and influence aren't fixed traits. They are capabilities that strengthen through practice and weaken through neglect. If we outsource too much of our thinking to AI, we risk outsourcing the very skills that make us valuable. To avoid that: Use your brain first, AI second - Multiple studies (like this one) have shown that thinking critically first and then turning to AI for assistance helps preserve learning and decision-making skills. So, resist the urge to solve strategic or challenging problems with AI first. Instead, try your best to come up with your own approach, then use AI to critique and enhance it. Invest in craft development - Nobody went to school for product marketing, and there is no universally accepted benchmark for excellence. Most of us are learning on the job. That's exactly why you can't let AI do all the heavy lifting. Push yourself to understand the reasoning behind recommendations instead of blindly accepting them. Get human feedback - One of the dangers of AI is that it's endlessly supportive. It rarely tells you your positioning is weak, your strategy is flawed, or your messaging isn't landing. Humans do. Whether it's a peer, mentor, manager, coach, or someone you admire, seek out people who will challenge your thinking instead of simply validating it. Seek first-hand insight - AI is trained on existing information, but your best insights come from living in the analog world. Talk to customers. Listen to sales calls (and I mean, actually watch the calls instead of just using AI transcripts). Pay attention to stakeholder reactions. The more AI becomes part of your workflow, the more important it becomes to stay connected to the messy, human realities that generate original thinking. I learned this lesson when I tried to build an automated workflow for my LinkedIn content. I spent days feeding AI my past posts and more context, hoping it could generate new ideas for me. The results were terrible. It’s because my best content doesn't come from old content. It comes from coaching conversations, client work, travel, and observations I make in the real world. A Practical Framework for Applying AI Once you've protected your moat and your human intelligence, the next question becomes: Where should AI actually fit into your work? This is where you need a very clear plan to maximize the value out of it (while protecting your moat/brain). So let’s dive in. Step 1: Understand the Three Types of AI Workflows Over the past year, I've found it helpful to think about AI workflows in three categories. The category determines not only the workflow you build, but also the role AI should play. Level 1: Execution Workflows This is repetitive, reviewable, shippable work such as repurposing content, aggregating data, summarizing research, writing release notes, and coordinating information across teams. This is where the biggest time savings live, and it's where almost every PMM should start. The work is relatively low risk, the gains are immediate, and the time savings compound quickly. Level 2: Thinking Workflows This is where AI becomes a thought partner. You might use it to sharpen messaging, synthesize patterns, pressure-test positioning, refine a launch strategy, or explore different options. Unlike execution workflows, these tasks require conversation and iteration rather than automation. For many PMMs, this becomes a daily companion (like Chat) rather than a fully automated workflow. Level 3: Scaling Workflows This is where many people get AI strategy wrong. There's a belief that advantage comes from building increasingly complex agents or massive end-to-end workflows. In reality, autonomous agents are often quite poor at PMM work because PMM work is full of nuance, judgment, stakeholder management, and context. The strongest PMMs aren't necessarily using the most advanced tools. They're thinking clearly about work design. Take content creation as an example. Instead of building one giant workflow that handles everything, start with a process you already understand deeply and perform manually today. Break it into pieces. Understand where the friction points are. Then identify where AI can improve the work at each stage and connect those pieces intentionally. Step 2: Find the Right Use Case The next challenge is choosing the right use case. The most helpful way to determine your initial use case is by tracking how you are spending your time. Many of us spend time on things that don't add a ton of value (e.g., spending way too long rewriting similar Slack messages). Map out your week and estimate where your time goes. Most PMMs will find their work falls into a handful of broad buckets: Content creation Admin and coordination Research and analysis Customer and market understanding Strategy and planning Stakeholder management Then compare that to how you'd ideally spend your time. The biggest gap often reveals your best AI opportunity. For many PMMs, the highest-leverage opportunities tend to sit inside content creation and admin work because these areas contain a lot of repetitive, time-intensive tasks where the thinking has already happened. Once you've identified the category where you spend the most time, the next step is selecting a specific use case within it. For example, if "content creation" is consuming too much of your time, you need to identify the specific workflow within that category. That might be: Turning launch briefs into sales enablement assets Repurposing webinars into social content Drafting release notes Creating customer-facing emails Formatting competitive intelligence updates A good way to pick a good use case from your list (such as from the one above) is to check it against 3 key filters. If you can say “yes” to the three questions below, then it’s likely the best place to start: Does it recur frequently? Weekly, monthly, quarterly; the more it repeats, the more your workflow compounds over time. Is quality limited by time, not thinking? Many tasks look like they're limited by time, but when you dig deeper, the real bottleneck is judgment. For example, AI can summarize ten customer interviews in minutes. But deciding which insight matters most, how it should influence your positioning, or whether it reflects a broader market trend requires judgment. If the thinking has already happened, AI can create significant leverage. If your judgment is what drives quality, AI is more likely to play a supporting role. Can it be done without significant relationship context or political judgment? This filter can also be hard to discern, but it’s incredibly important because the nature of product marketing work is uniquely relationship-based. Take something like positioning and messaging: you can feed April Dunford’s framework into AI, but you’re going to fail if you can’t get stakeholders aligned around it. Your uniqueness doesn’t lie in your ability to spit out a document; it comes from bringing stakeholders together, resolving any conflict, and actually moving forward with something everyone agrees on. Example: One PMM’s Slack Intelligence Digest A client of mine is one of many PMMs at an 5,000-person company with 20+ products. Staying on top of eight relevant Slack channels, including global sales regions and industry news feeds, was consuming a huge amount of time every morning. Only a small percentage was relevant to her product area, while the rest was just a distraction. So she built a Cowork-scheduled digest that runs daily at 9 am, reads her specific channels, filters for what's relevant to her product area and key competitors, and returns three categories: what to read first, what to skim, and what to skip entirely. The best part is that if she's been offline for multiple days, it adjusts automatically to give her a consolidated summary instead of stacking up 20 individual outputs. She isn’t asking AI to make decisions; she’s having it triage so she can. And while this might not seem like a big deal because it didn’t take much effort to build, this is saving her a TON of time and helping her focus on what matters. It’s a great example of simple, recurring, high-leverage execution. Step 3: Choose the Simplest Tool That Works One thing I've noticed is that people often assume they need the most advanced tool to get the best results. They'll spend hours debating whether Claude is better than ChatGPT, whether Gemini is catching up, or whether they need to learn coding and agents to stay relevant. The reality is that these differences matter far less than most people think. Your success with AI will be driven much more by choosing the right use case and designing the right workflow than by picking the perfect tool. In fact, I've seen many PMMs get distracted by shiny tools when a much simpler solution would have solved the problem perfectly well. Using Claude as an example, most PMMs will spend the vast majority of their time in just three modes. Chat is where thinking happens. This is where you brainstorm, refine messaging, pressure-test ideas, summarize information, and work through problems. For many PMMs, this alone will account for a significant portion of their AI usage. Projects become useful when you need persistent context. This is where I would store things like messaging frameworks, positioning documents, competitor information, brand guidelines, and other context that you don't want to re-explain every time you start a new conversation. Cowork is where recurring execution lives. These are workflows that happen on a schedule and can run automatically without you manually triggering them each time. And honestly, that's where 95% of product marketing use cases live. And very little product marketing work requires code. More importantly, using a more advanced tool doesn't automatically produce a better outcome. A simple workflow that gets used every week is infinitely more valuable than an impressive workflow nobody trusts, understands, or maintains. Step 4. Iterate, don't perfect Now we come to the last point. The first version of anything I’ve ever built was not very good. And that’s okay. The only way to learn this stuff is by doing it. The best way is to start with something small, learn from it quickly, refine it, and keep going. Here's what that looks like in practice: Deploy fast, learn faster. Your first prompt, your first workflow, your first output is data to learn from, not a deliverable. Treat it that way. Incorporate human checkpoints. Know exactly where a person needs to review before anything goes anywhere external. If the output touches sales or another function, those people need to be in the loop from the beginning, not brought in after the fact to validate something they didn't help shape. Build in public. Post your workflows, demo at an all-hands, and create a shared prompt library. The PMMs becoming known as AI champions in their orgs are the ones building in public, sharing successes and failures. This will get you organizational buy-in, which makes every future workflow easier to launch. Ultimately, AI isn't a test you pass. It's a skill you develop. The more you experiment, the better your judgment becomes, and judgment is what creates the real advantage. How to approach each project: Use AI to become a better PMM: The AI PMM Academy If this newsletter resonated with you, you're exactly who I'm building the AI PMM Academy for. Every week, I talk to PMMs who know AI matters but feel overwhelmed by where to start. They're tired of the hype, tired of the fear-based messaging, and tired of generic AI advice that has nothing to do with product marketing. They don't need another list of tools. They need a practical way to combine strong PMM fundamentals with AI workflows that actually help them do better work. That's what the AI PMM Academy is designed to do. Together, we'll strengthen your core PMM skills like positioning, research, and product launch that works for today’s world, then layer AI on top in a way that actually makes sense for product marketing. We'll also focus on leadership, influence, and productivity so you can create more space for strategic work. You'll learn alongside other PMMs navigating the same challenges, see real workflows from practitioners successfully using AI on the job, and build systems you can apply immediately in your own role. This isn't a course full of talking-head videos and a certificate at the end. It's a hands-on learning program for PMMs who want to improve their craft, use AI thoughtfully, and grow alongside smart peers. If that sounds like what you've been looking for, I'd love for you to join the waitlist and get early access when the program launches. Yi Lin 💜 P.S. This newsletter was written human-first by me, edited by my amazing editor Christine Moore, and then proofread and polished with the help of AI.