Arpit Dhariwal

The U.S. IPO market is showing signs of revival in 2025, driven by strong investor appetite for high-growth, AI-powered software companies like Figma, whose blockbuster debut reflects renewed enthusiasm for quality tech listings. With robust institutional backing, surging public market interest, and a pipeline of enterprise-focused AI firms preparing to go public, the IPO landscape is shifting toward substance over speculation—though macroeconomic and valuation risks remain.

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🎙️ From Square to Mercury: How Rohini Pandhi became one of fintech’s top product leaders—and how velocity of learning at high slope companies shaped everything. Rohini dropped so many gems in our first episode of First Builders: 💎 Generalist → Specialist: In her early career, she was a generalist and tried everything. This led her to critical discoveries. She specialized in product and fintech when the “time was right” 💎 Follow the Engineers and Designers: Square was a high slope environment for Rohini, packed with talent density and learnings. She finds high slope environments by studying where smart engineers and designers are going. 💎 Fake News about PMs: PMs don’t just “move fast and break things.” Her team runs 30-50 customer interviews per quarter, providing rigor behind every decision. 💎 It’s Usually Too Early to Hire a PM: A top question she gets from founders is whether they should hire a PM. She usually says: “it’s too early.” 💎 Hiring a World Class Team is Like Tennis: When finding a tennis partner, you want someone a little better than you who can challenge you to improve your game. Give us a listen and leave a review on your favorite podcast location (see comments for links)! #FirstBuilders #StartupPodcast #ProductLeadership #TechCareers #Leadership

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Checked out Forerunner/Kirsten Green's "The Architects of Experience" piece (linked in comments). Sharing some thoughts below. Every 10-year platform shift resets consumer expectations (Web → Mobile → AI). Kirsten says the AI era belongs to products that feel effortless: proactive, predictive, always learning. It’s not about adding an LLM garnish; it’s about architecting the entire business around a compounding data loop. So, why does it matter? Moat ≠ code → The defensible layer is a proprietary data flywheel that learns faster than users can churn. Talent remix → Winning teams look less like pure engineers, more like “orchestrators” who weave off the shelf AI, data strategy, and distribution. Trust is the gate → Human in loop design and transparent governance are table-stakes for adoption, and eventual regulation. Questions to consider for consumer AI founders... 1. Moat depth: What makes your data flywheel unique, and how quickly does it compound vs. the big LLM platforms? 2. Distribution edge: When AI tooling is commoditized, what non-technical channel (community, brand, regulated access) gets you in front of users first? 3. Human-machine balance: Where does your product deliberately stop automating to preserve agency and delight? 4. Regulatory resilience: How will privacy portability rules affect CAC, margins, or data lock in? My counterview: Total automation can flatten delight. Some categories thrive on intentional friction (e.g. luxury, craft, serendipity). Winners will know when to keep a human in the loop.

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As I am coaching PMs, I often get the question on how I navigate alignment challenges between cross-functional partners. I spent many years at YouTube building products where safety and user value must coexist. Finding common ground when the stakes are high and opinions diverse felt draining but over time I’ve come to enjoy the process. There is both an art and science to aligning stakeholder. One of the key things I've learned is thinking of alignment at three levels - Problem, Principles, and Product. 1️⃣ Problem - Starting with the Right Question I can't tell you how many times I've been in a room where we've spent hours debating solutions only to realize we weren't even solving the same problem. I remember one particular project where our team had many meetings of increasingly tense discussion before someone finally asked, "Wait, what problem are we trying to solve here?" It was a weird question to ask and felt like we are going backwards. But in that moment we realized how misaligned we were on the problem itself. 2️⃣ Principles - Your North Star in Difficult Terrain Clear principles are non-negotiable, especially for products focused on Safety and Responsibility. They serve as guardrails when you hit those inevitable crossroads where all paths forward involve tough trade-offs. A good way to test whether the principles are written well is to see if they can help answer questions like "Do we delay launch to address this use case? Are we ok to miss the near term opportunity?" 3️⃣ Product - Where the Rubber Meets the Road This is where alignment gets really tested. In my experience, developing options is the secret weapon for driving alignment at the product level. I typically spend hours in 1-1’s trying to understand everyone's perspective before bringing the group together to review options. Something I learned listening to Lenny’s podcast with Ami Vora is that pushback often indicates the other person knows something you don't. So rather than getting defensive, try to approach disagreements as learning opportunities. In evaluating options, I've found that simple pros and cons lists don't help much. Every option will have pros and cons! Instead, I define a few key dimensions that matter based on our product principles and company priorities. Then I grade each option against these dimensions (e.g high/med/low impact). This approach leads to much richer trade-off discussions. It's very rare for one option to be "green" on all dimensions, and that's where the real alignment work happens - deciding what matters most to the company and what you're not willing to compromise on. 👉 Alignment isn't about getting everyone to agree with you. It's about creating a shared understanding of the problem, establishing clear principles, and facilitating informed decisions about the product. Thanks James Beser for coaching me on the art and science of driving Cross-Functional Alignment. Link to the detailed post in my comments.

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"This space moves so fast that every quarter, everything you do can be obliterated," said Glean founder Arvind Jain. "We had to shift to a mindset of constantly rebuilding. Your moat is not your tech but the value you provide to your customer, those deep relationships you build, and the team that’s with you to build and execute in that kind of environment." An intimate, thoughtful gathering at last night’s AI Pioneers Summit by Decibel Partners and Latent Space Podcast with speakers that included (photo, left to right) Eric Simons (bolt.new), Behnam Neyshabur(Anthropic), swyx ​(inc a celebration of 10M downloads), Arvind Jain (Glean), and Laura Burkhauser (Descript). Simons: “We’re seeing more developer-adjacent product people building direct experiences.. that will lead to developers doing deeper thinking & reviewing PM work, as PMs also go deeper to shape the front-end.” Burkhauser spoke to the complexity of AI video editing, where context goes far beyond the script to understand how humans see, feel and sense, and uncover the reasoning behind what a viewer expects. Neyshabur's pursuit of creating an AI scientist is rooted in his curiosity about how a model learns from human interaction and the nature of learning itself. Our breakout session was insightful, inclusive, and energetic. Good to spend time with founders like Bella Liu (Orby AI - A Uniphore Company) and catch up with Ajay Singh. A great mix of technical depth and openness for conversations that stay with you.

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Onboarding isn’t a feature. It’s a first impression, a trust test, and a shot at creating real momentum. This piece lays out how behavioral design can shift onboarding from clunky to compelling. Worth a read if your product greets new users like a PowerPoint deck. https://lnkd.in/eHkYrH2U

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🚀 Figma’s Journey: From Acquisition to IPO Figma's shift from being acquired by Adobe to going public is a powerful story of resilience and adaptability. Originally valued at $20B, regulatory hurdles forced Figma to pivot to an IPO. Now, it’s on track to raise up to $1.5B in one of the largest tech IPOs of 2025, with a current valuation of $12.5B. This journey underscores the importance of pivoting when faced with challenges. For startups and founders, Figma’s story is a reminder that resilience in the face of setbacks and adaptability to changing circumstances can lead to even greater success. Excited to see where Figma goes next and how its journey will shape the future of design tools. #TechIPO #Figma #VentureCapital #StartupGrowth #Resilience #Adaptability #DesignTools #Innovation #InspireGlobalVentures

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I was CPO at Blend before their $4 billion IPO. We rejected the “forward deployed engineer” Palantir model that everyone is copying now. Here’s why: Blend could have followed the forward-deployed engineer approach. Both our CEO and CTO were early Palantir. They'd seen it work. Instead, we built a SaaS product with core components. Move fast, iterate, use data to learn. Not custom code for every client. That Palantir model is having a resurgence. Now Sierra, Decagon, and others are hiring forward-deployed engineers. But it’s not the right approach for every company. It’s fundamentally the wrong answer for Assembled’s customers. Here's what we understand about support teams and why we’re not going the forward deployed route: Customer Support teams are used to getting no resources and no support. On the surface, you'd think they'd be excited about engineers building custom solutions. "Finally, someone's offering us developers!" The reality is support teams are terrified of getting help they can't afford to keep. Support teams are wary because they know the math. They don't have budget for expensive, scarce resources. At some point the shoe drops. The engineers disappear when priorities shift. And custom solutions break. Support is left holding the bag with something they can't maintain. They're resource-starved by design. The idea of a dependency on resources they can't control is terrifying. So instead, the goal should be to give support teams the ability to manage, change, and solve their own problems. Not dependencies on engineers they can't keep. Smart, competent people who teach them to do it themselves. Palantir wasn't even a product company for years. They were a custom development shop with reusable components. Show up, build something bespoke, maybe extract learnings. That's not scalable for any but the largest support teams who need sustainability. Forward-deployed engineers are the new shiny object. I wasn’t a fan of it at Blend. And I’m not a fan today either. What I see in the customer support space is that teams need empowerment, not dependency. I want the teams we work with to be able to say: "I love that you’re partnering with me. And I love that I can do this myself too." That's the difference between building a product and building a consulting practice.

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I rarely make predictions, but... No company founded after 2026 will organically grow to more than 10k FTEs. The leverage of rapid iterative decision loops by teams using best-in-class AI has reached escape velocity over traditional economies of scale.

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Storytelling might be the most underutilized skill in product building. The best builders don’t just ship features; they shape belief. Across teams, investors, and customers, a compelling product story can be the difference between momentum…and noise. Yuhki Yamashita (CPO at Figma) put it well: “The act of synthesizing a lot of things into a cohesive story itself… stories are your vehicle for motivating people, for capturing your customer’s imagination… it’s still kind of an underrated capability.” More from Yuhki in this Building One episode: ► Watch on LinkedIn: https://lnkd.in/erHyMmPf ► Watch/Listen on Spotify: https://lnkd.in/d3yEWpux  ► Listen on Apple: https://lnkd.in/d6W-uqbM 

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Confidence might be the most underrated skill in product marketing. In the latest episode of Embracing Erosion, I sat down with Jason Oakley - founder of Productive PMM and DemoDash - to unpack how confidence (or the lack of it) shapes everything for PMMs. We talked about how founders can unintentionally erode confidence with unclear feedback or shifting priorities, and why protecting a PMM’s confidence directly impacts speed, clarity, and execution. We also got into: ⚙️ How to build systems before layering on AI and automation 🎯 Why interactive demos are some of the highest-intent assets in B2B 💪 What it really takes to thrive as a founding PMM in 2025/26 If you’ve ever been the “first marketer” or a PMM trying to do it all, this one will hit close to home. Link to the full pod in the comments 👇

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Having spent the past 15+ years as a Product Designer in tech in the San Francisco Bay Area, I’ve seen the whole arc from joyous optimism in making products that change the world, to fearful pessimism from the threat of layoffs, ironically from being directly or indirectly involved in creating products that change the world… and now our livelihoods. I’m hearing from a number of former co-workers who are telling me how their working environment has changed drastically; more fear, more anxiety, feeling the pressure to work longer hours and produce more impact, all while compensation and benefits are being squeezed and the goalposts for promotion seems to keep moving. And yet, for all the skills and experience we’ve accumulated, it doesn’t increase career options and mobility; in reality, the workplace squeeze along with precious equity vesting schedules keep a lot of people feeling even more stuck than ever before. Layer on the threat of layoffs, and you’re now trapped in a gilded cage that keeps shrinking, and shrinking, and you’re running out of time and bandwidth to figure out what to do about it. What options do I have? What alternatives are out there? (Will those alternatives pay the same as what I currently make?) What time do I have to explore these alternatives? The truth is: there is time; either time you allocate now to be proactive about your explorations, or time that will be allocated for you when you’re not ready for it, for example, if you’re on the side of a layoff. I know from first-hand experience what that feels like, and I don’t wish that and the feelings that come with that on anyone. What I wish I had in those moments were the mindsets and methods from Designing Your Life; then I wouldn’t feel stuck to my seemingly “one best option”, even embrace these curveballs because I’ve prepared for multiple scenarios, all of which I could be taking baby steps to explore and gain clarity and confidence towards being layoff-proof. If you’re feeling stuck with no good options in sight, feeling like there’s no time to prepare or just want someone to think out loud with, type "OP" in the comments; we can chat over 3 short calls, and get you on a path towards clarity, confidence and coherence.

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Most companies still treat product partnerships as “ship the integration, issue a press release & move on to the next.” Asher Mathew and I had a great convo with Erika Wool - who leads Product & Strategic Partnerships at industry-leader Stripe - about how to counteract that mindset and drive real ecosystem-driven growth. Here are a few insights from our convo 👇 🔹 1. Product partnerships should create businesses not just applications. Stripe builds products that literally cannot exist without partners: payment methods, banks, financial infrastructure, AI experiences, and more. If your partnerships don’t meaningfully shape how your product drives value, it’s not strategic. It’s a logo. 🔹 2. Launch is the starting line, not the finish line. Erika talked about the “care and feeding” after launch: SLAs, QBRs, joint roadmaps, new markets, new features, constant recalibration. If your integration degrades as products evolve from benign neglect, your partnership won't keep paying dividends. 🔹 3. The best partner leaders speak “product,” “strategy,” and “finance.” You must connect market trends, user data, and long-term economics into a story that executives (especially CFOs) can get behind. If you can’t articulate the financial arc of a partnership, you’re flying blind and you won't maintain internal support. 🔹 4. Saying “no” is a superpower. Partnerships generate endless opportunities. The leaders who win are the ones who stay focused and keep their product teams focused. 🔹 5. Internal bridges matter as much as the external ones. Engineering, product, sales, channel, CS, marketing: everyone touches the same partner for different reasons. The job isn’t to “own” the partner … it’s to prevent the org chart from being what the partner experiences and fracturing customer value. 🔹 6. AI is turning every company into a tech company and partnerships will only get more central. As Erika put it, we’ll need to watch not just the traditional tech ecosystem, but retail, airlines, healthcare, etc., because product partnerships are becoming the infrastructure beneath all modern business and consumer experiences. This conversation is one of the clearest explanations I’ve heard of what strategic product partnerships actually look like: messy, cross-functional, multidimensional, and essential now more than ever. If your company is trying to move from “we launched an integration and a press release” to “we built a business around an integrated ecosystem driving customer value,” check out the full convo with Erika here: https://lnkd.in/ewJgn32f (Also hat tip for Glen Roth for the intro to Erika after I read his interview of Erika in Glenn's newsletter - I've been a subscriber for 5 years - it's a must read if you are in partnerships 💰)

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✨Reimaging org design in the new AI world - a new thought proving article by Susie Hall, InsideOut Design Leader Community. TL/DR - key takeaways • Role pendulum is swinging from specialists to generalists Many organizations are looking for flexible skill sets in their talent • Organization structures are evolving towards end-to-end customer journeys Aligning teams with business value and impact work streams • Beware of the shiny object Some organizations have a shiny AI mandate without a clear strategy on product, talent or tools https://lnkd.in/g2AZz_z9 #OrgDesign #Talent #AI #Leadership #Business #Impact #Design #DesignOps

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Conventional wisdom holds that startups function as a safety net in times of layoffs. As large companies shed workers, fast-growing newcomers are expected to absorb displaced talent, whether immediately or over time. That narrative resurfaced as Big Tech layoffs extended into early 2026, with more than 26,000 employees affected across 59 companies in January. Data from an Ascend survey of startups suggests the picture is more complicated. Among the VC-backed startups in our survey, nearly nine in 10 CEOs report actively using AI in the operation or building of their companies. Many say they are planning to hire smaller teams than they would’ve needed just a few years ago. To understand how those choices are being made, Ascend surveyed ~70 CEOs of VC-funded startups that are small and overwhelmingly early stage. The average company was founded in 2022, most are pre-seed or seed, and they are typically building their first 10 to 15 roles. These companies have always represented a small share of the labor market, but they are often where new roles are created first. Amazon was once a startup, too, which is why shifts at this stage matter. Opportunities certainly still exist, even in this economy! Later-stage startups continue to hire, new companies are being formed, and early-stage founders are looking for strong talent. Many people affected by layoffs will find a great landing, and some will start companies of their own, as has happened after nearly every downturn. But at the same time, hiring dynamics are changing in quieter ways. At large companies, AI-driven efficiency gains tend to surface through layoffs that make headlines. At early-stage startups, they appear to surface earlier, through hiring plans that never materialize and roles that may never be filled. Founders remain builders and job creators, while also operating under intense pressure to extend runway and move quickly with lean teams. In many cases, they are navigating the same forces as their larger peers, just earlier in the company’s life. *Layoffs and tight job markets still suck!* I’ve seen the impact firsthand, especially on people with families, visas, and very little margin. None of this should undermine the skills and humanity of those impacted. What this survey is intended to capture is a shift in how startups are being built from the beginning. AI is shaping team design long before those changes show up in headline job numbers, influencing when new roles appear and how many emerge. Startups may still create the next wave of jobs, as they always have. The path looks different this time, though, and it’s worth being clear-eyed about that, especially for the people living through the transition. If you’re a founder who is hiring, feel free to link your job board in the comments. 👉 Swipe through the carousel for the data and breakdown.

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AI is changing faster than most of our org charts, but we are also changing on the inside - and that second part is where the real opportunity lives. I’ve been reading and re-reading Maya Shankar’s new 2026 book, “The Other Side of Change,” which looks at who we become when life forces us into a “before” and “after.” If you’re feeling the pace of change right now, especially around AI, this book The Other Side of Change is a timely companion. It won’t slow the curve, but it might change how you travel it. Her core idea: big change doesn’t just alter our circumstances; it reshapes our capabilities, our values, and even how we define ourselves. If we pay attention to those internal shifts, change can actually expand us instead of shrinking us. We often restrict our imagination more than necessary when change arrives. A powerful question is: ‘Who else can this person be? We forget that we won’t be the same person on the other side of change; we’ll be someone with new abilities, perspectives, and values That lens feels essential in this moment with AI. In 2026, many leaders are no longer asking whether to use AI, but how to redesign work around it - agentic systems, autonomous workflows, and AI‑native functions are moving from pilots to the operating model. The technology curve is steep, but our identity curve as leaders is just as steep: what we’re good at, the questions we ask, and the value we create are all in flux. Instead of framing AI as “how do I catch-up with this fast pace change in AI?”, Shankar’s work nudges a better question: “Who am I becoming on the other side of this change and what new value can that version of me unlock?” That reframing moves us from fear and defensiveness to design and intent. For those leading AI transformation, I’d offer three reflection prompts inspired by the book: 💪 💪 💪Where have past disruptions already expanded what you’re capable of? 💪 💪 💪 What parts of your leadership identity are you willing to let evolve as AI takes on more of the routine work? 💪 💪 💪 If you met your “post‑AI” self three years from now, what would you hope they had the courage to try?

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Meta for better or worse has fairly prescriptive interview practices from the questions from which we’re supposed to choose, the dimensions against which we assess each type of interview, and the way in which we rate performance. Most questions now have write ups for interviewers to make sure we assess similarly. Of course there is variation in how people apply this, how much they help or sit silently while a candidate struggles but it’s all pretty standardized. In some ways that’s good and in some ways it’s bad but it’s the most consistent process I’ve seen anywhere. I’ve done a lot of interviews and most failures are simply the quality of thinking that’s happening. One thing that I’ve seen a fair bit though is people get attached to some framework and stick so rigidly to it they don’t actually think about what’s being asked so answer in weird ways. If a frameworks helps you, great, use it. If it’s not appropriate it’s not helping you to hit ten different steps on an irrelevant list. It actively hurts you. Beyond that there’s some definite luck as with any interview. You get a question that clicks or one that totally baffling. You get an interviewer with whom you’re relaxed and helpful or one that makes you nervous and sits there as you flail. Not much to be done about that. There isn’t any magic though and as flawed as our interview process is (I have lots of issues with it) it’s the fairest, or strives to be the fairest and most objective, of any I’ve seen over multiple companies. You have to remember there are an enormous number of people many of whom are quite good competing for not that many slots so there has to be a winnowing of some type. It’s worth noting you can also request a coaching session. Or at least recruiters have signed me up for these. I don’t know id they all mention it but when I’ve been asked to provide coaching I’m pretty open about what we look for. I don’t know if everyone is as transparent as me but if you’re worried about the interview I’d ask your recruiter about this. #meta #interview #productmanager #jobs https://lnkd.in/eyA8xECN

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A great read for people struggling with Whatsapp Business due to operational constraints. It highlights how an Org's DNA restricts it from solving genuine user problems. https://lnkd.in/djfimqBT

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Sharing my latest post on 🚀 Product Discovery: The Art of Grounding Your Team in Customer Voice Too often, teams build products based on gut feel and quickly realize it’s not sustainable. The real magic happens when discovery is structured, customer-driven, and anchored in a clear product strategy. In this post, I break down: ✅ Opportunity Discovery — How we validate the real customer problem, market size, and willingness to pay before investing. ✅ Solution Discovery — How we explore and test solutions that balance customer needs and business goals. ✅ Go / No-Go Decision — Why this critical pause saves teams from wasting time and money on ideas that don’t deliver value. ✅ Planning — How we align the entire team to build with confidence. ✅ AI’s role — How tools like Dovetail, M365 Copilot, and ChatGPT are transforming discovery, making it faster and smarter. 📌 Check out the full post and let’s discuss how you’re embedding discovery in your teams! I’d love your feedback or questions. https://lnkd.in/dvtf7u_e #ProductManagement #ProductDiscovery #CustomerVoice #ProductStrategy #AI #ProductDesign #BuildTheRightThing

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