Shawn Gong

In a yet another interesting episode by Dan Shipper (https://lnkd.in/gpjwThRU), this time interviewing Reid Hoffman, there's some gems shared. Theme is predicting how AI/ Agents adoption will pan out in 2026. At minute 18 of the conversation, Reid's prediction hit home for me when he claims how access and adoption of (real) AI Agents would increase by 100x than what we saw in 2025. This would be fueled by - 1. AI Agents being rapidly adopted by builders beyond developers and, 2. Tools that will boost access to 'real' Agents. As Reid puts it well - its not just conversations with LLMs, but offloading entire workflows to these AI agents - that can operate your machine on your behalf - to complete tasks. Stoked to be contributing to (and believing in) this prediction. At UiPath, our continued research on releasing agent frameworks for computer-use agents as well as launches and incubation of true action agents is promising! More on this space soon.

9

1 Comment

"How would you launch this product?" This question makes most PM candidates freeze. The problem? GTM questions feel overwhelming because they span pricing, distribution, positioning, metrics, and more. The solution? A right mental model and a lot of practice. I just published a comprehensive guide on answering GTM questions in PM interviews using the C-T-P-D-M framework: → Clarify context before diving in → Target the right customer segments → Position your value and set pricing → Distribute through optimal channels → Measure success with clear metrics Read the full guide: https://lnkd.in/gffMSYgd ... The post includes: - Step-by-step breakdown of each component - Real examples with tradeoff analysis - 20 practice questions (beginner to advanced) - Common pitfalls to avoid Whether you're prepping for FAANG, a startup, or your first PM role - this framework will help you stand out. ... This is my 8th deep-dive on essential question types. Find the previous deep-dives in the comments below. I share practical guides on cracking PM interviews every week. 👉 Follow me (Amit Mutreja) to stay in the loop. ♻️ Repost to help someone in your network. #ProductManagement Crack PM Interview #PMInterview #GTM

12

5 Comments

On March 25th, the founders of Sonos, Inc., Seek Thermal, and Santa Barbara Venture Partners will share their stories with the Ventech • Emerging Venture and Technology Forum. I'm looking forward to hearing what made each founder decide to start — and what kept them going. Link in the original post. #Entrepreneurship #HowIBuiltThis #SantaBarbara

23

3 Comments

🚀 The 5-Hour PRD: Streamlining Product Requirements in the Age of AI Fellow PMs: how long does it take you to move from a fuzzy idea to a validated PRD and wireframes? I recently tested an AI-driven product workflow that did it in just 5 hours - and the results were eye-opening. Here’s how it went 👇 🧩 My AI-Powered Product Workflow (End-to-End in 5 Hours) 1️⃣ Define the Audience & Problem I have defined detailed personas for my Notion AI Agent: David (CISO), Rachel (Security Engineer) and James (Risk Manager). Then I asked Notion AI to analyze our current reports (all the knowledge is in Notion), identify the key data gaps, and outline the specific questions each persona would ask. After a few iterations and scoping, I had a clear, persona-driven problem statement and out of scope. 2️⃣ Move from Text to Visuals Next, I switched to Google Stitch [https://lnkd.in/d7cmSc7c], gave it the problem statement as a prompt and included a couple of screenshots from our Figma design library for inspiration. With a few structured prompts, I generated three high fidelity wireframes: dashboard overview, stats view, and object-level drill-down. 3️⃣ Validate with AI I dropped those wireframes back into Notion and asked AI: “Do these visuals answer the personas’ questions?” It gave a detailed, point-by-point validation: and the alignment was spot on. 4️⃣ Finalize the PRD With validation complete, I asked the agent to write the high-level solution and detailed user stories describing interactions (think: “click this, then that happens”). All in: five hours, start to finish. ⚙️ The Bottleneck This speed is incredible: I could almost hand the PRD and wireframes to an AI dev tool like Claude Code/Codex and say “build it.” But here’s the problem: engineering velocity hasn’t caught up. If PMs can deliver fully fleshed PRDs in hours, yet development still takes weeks, the bottleneck has shifted. 🤔 The Question for PMs When product can move this fast, how do we enable engineering to keep up: leveraging AI, automation, and smarter workflows to match product’s new pace? Would love to hear how other PMs are tackling this balance between AI-accelerated product design and AI-assisted engineering execution.

32

7 Comments

Time-to-value is the real growth metric. If it takes 2 weeks for a clinician to see value from your product, most won't make it to week 2. Time-to-value isn't "when they understand your product." It's when they achieve something meaningful that makes their life better. Most healthtech products make users jump through hoops first: → Sign up → Wait for demo → Attend training → Configure settings → Try to use it → See value (maybe) That's 2-3 weeks. You've already lost them. Instead, ask yourself: can someone get a win in their first 5 minutes? Not "complete setup." Not "watch tutorial." Actual value. That's your activation moment. Track how many users reach it. Celebrating signups while losing users before they see value is just expensive theatre. How long does it take a new user to get value from your product? 👇 P.S. If you're celebrating signups but losing users before they see value, let's talk about activation. I'm offering free coffee chats to healthtech founders (Hale House or Zoom, my treat). DM me.

6

A decade in Product has taught me that prioritizing fundamentals leads to compounded outcomes. Key areas include focus, clarity, decision-making, and customer success. I have documented 10 principles that I rely on, which are practical, repeatable, and applicable for both building new products and scaling existing ones. For more insights, visit the link: https://lnkd.in/eCWrb5re

29

1 Comment

🚀 Built to Ship – Hosted by Tyler Postle, Co-Founder of Voker (YC S24) 🎙️ 🎧Featuring Devin Stein, Co-Founder of Dosu In today's episode I learn about how Dosu is solving the engineering knowledge problem—making code understanding accessible to both engineers and non-technical teams through AI-powered documentation and issue triage. Devin shares his journey from fine-tuning GPT-3 models to realizing that coding wasn't the bottleneck for senior engineers—it was sharing knowledge and answering repetitive questions. Devin reveals their multi-agent architecture: an orchestrator delegates to specialized sub-agents (research, code changes, documentation) that keep context clean during 30-45 minute documentation workflows. For monitoring, they use DBoss (a Postgres-backed durable execution framework) with Grafana dashboards for high-level metrics and LangSmith for deep-dive traces, plus unique signal from public GitHub threads where they compare Dosu's answers to eventual resolutions.

19

2 Comments

🚀 Product Management Meets AI: Prompting is a Tool, Product Thinking is the Job. Three years ago, "prompt engineering" became the hot job in Silicon Valley — sky-high salaries and hype everywhere. It reminded me of early Google Search, when getting good results meant knowing tricks: site:gov.au filters, exact phrases in quotes, or chaining operators to dig deep into the internet. These days? You just type, "What's the latest government report on renewable energy in Australia?" — and it works. We're in a similar phase with AI. I've been deep in tools like Claude, GitHub Copilot, and Windsurf lately. One thing is clear: you need to learn "vibe coding." Coined by Andrej Karpathy, it's about collaborating with AI — shaping prompts rather than writing every (or any?) line yourself. And yes — we will need more explicit PRDs and structured documentation to get what you want. This isn't waterfall revival — it's giving AI enough signal to generate useful outputs. When you can generate code fast, ensure the ship points in the right direction. Tools like ChatPRD and Chisel Labs are making this easier and create wonderful detailed PRDs. But I don't think this phase won't last forever. 🤖 Rules I'm adopting as a product person: 1. Work with the machine — but remember your unique value → Tools now change faster than ever. Your ability to frame, empathise, and decide differentiates. 2. Structure for today's AI — evolve as tech does 3. Prompting is a tool. Product thinking is the job. 4. Vibe coding is great for prototyping — it's a superpower, not the job 5. AI exposes weak PMs. The craft is harder to fake now. 6. Don't spec what you can test → When prototyping is cheap, over-planning is expensive. 7. Think in systems, not features → LLMs can't reason across flows and edge cases like we can (yet). 8. Stay curious, not defensive → Speed is a multiplier — but only if you're pointed in the right direction. 🎯 The bottom line: AI won't replace product managers. But PMs who fail to evolve might be replaced by those who do. How are you adapting to this shift? 👇 #ProductManagement #AI #ProductCraft #VibeCoding #Leadership

75

13 Comments

We're finally launching BentoLabs AI (YC P26). Kaushik ASP and I spent last two years at Emergent (Scaling $0 to $100M ARR in 8 months, SWE-Bench #1) living inside agent development. And we kept seeing the same thing: best engineers buried in traces, patching prompts, hoping something sticks. Whatever the agent figures out on run 47 is gone by run 48. A loop that neither closes, nor compounds. BentoLabs AI is the monitoring and learning infrastructure that fixes both. - Monitoring finds every failure across your production traces, classifies it and tracks it before a support ticket ever pops up. - Learning captures what your agent figures out on every run and makes sure it carries into the next one. Recurring failures get fixed once and stay fixed. Run 101 starts from everything runs 1 through 100 learned, not from zero. To see our engine in action, we took on ARC-AGI-3, the hardest agent benchmark we could find. Same model. Same harness. 2.6x score improvement. 34% drop in cost per successful outcome! (Refer to comments for the full go through!) If your agents are in production and your team is caught in the same cycle, that's exactly who we built this for. Let's have a chat. You can dm either of us, also sharing cal below for lower latency :D

668

67 Comments

EVERYONE is responsible for sales at your startup! This picture is actually of my CTO/Co-Founder, Gregory Steckel, a Georgia Tech grad student studying Data Analytics. While he may hold the title of CTO at our startup, everyone is responsible for sales, even him. This idea of sales culture is ingrained in all of us, so much so that my co-founder literally called a potential-customer SEVEN TIMES before actually closing the deal and getting a meeting on the calendar. Now, for most people, that would sound ridiculous. I honestly was begging him to stop calling the guy after the call number 3 (that went to a voicemail). He continued anyway, and on the 7th call the potential customer finally picked up! The call went so well that the customer sold our software for us! We didn't even have to sell our offering. The product-market fit was so amazing; it was literally out of this world, and it just showcases what happens when you really empower everyone on your team to do sales and have belief in themselves. If you're building a startup and you have two co-founders and VCs are asking you who's in charge of what: Yes, you guys may have responsibilities and titles, but just know that at a startup, every single person is responsible for sales. Versaunt

42

3 Comments

I had a wonderful time joining Alec Crawford on the AI Risk Reward podcast. We spoke about how AI should enhance rather than replace human creativity, what it means to build ethical, human-centered AI systems, and the future of work. We even discussed how AI acts as a mirror to our collective unconscious. 🎧 Listen to the full episode here: https://lnkd.in/g6Y9b9Yp ▶️ Watch on YouTube: https://lnkd.in/grtJ3FC6 #AI #GenerativeAI #Creativity #AIethics #AIinBusiness #Podcast

7

If you're too busy to mentor — you’re not a product leader, you’re a bottleneck. & Stop trying to be the smartest person in the room. Start being the clearest. #leadership #pm #productmanagement #productmanager #productleader

41

2 Comments

Curious how AI is affecting Product Managers? 💡 For an enlightening read, check out this Dice career advice article, with insights from GA's Director of Product, Beatrice Partain, WGU's Principal Product Manager for Innovation, Ryan Gialames (who we are also grateful to count among our Future Skills Board members), and Typeface's Chief Product Officer Vishal Sood. A few highlights: ✨ 78% of product managers say they use AI agents ✨ 98% say it improves their product lifecycle ✨ 38% vibe code to build and test prototypes (and if you want to join them, check out our free Vibe Coding 101 class -- the next one is Monday, Nov 17) If you're a product manager, or work with a product team, I'm curious how you might be using (or thinking about using) AI. 💡💡💡 https://lnkd.in/gS5CiNK2

19

2 Comments

The Latticework of Understanding (What 10,000 years of Pattern-Building Says About Your Messy Desktop) Every new thing you learn is not a brand-new thing. It is a wrinkle on top of something you already understand. https://lnkd.in/es9r2C9f

1

I wrote about why product managers should step into the shoes of their customers and dispassionately figure out if they would buy their own product if they were a customer https://lnkd.in/gZDzuVFY

25

3 Comments

One of the most rewarding aspects of mentoring at Harvard Business School is the opportunity to engage with builders who don’t just learn the craft—they evolve it.   One example is Dewan Sharfaraz Ahmed, who is rethinking product management through an AI-native lens. After HBS cancelled the PM course, he took the initiative to found a Product Management education series that teaches experienced and aspiring product managers how to use the latest AI platforms like Claude Code, Codex, Cursor, Replit, and Lovable to compress cycles, expand capability, and fundamentally change how products get built. His series "Everyone Is A Product Manager" are worth watching: https://lnkd.in/eRVJ7cZB   Thanks Dewan Sharfaraz Ahmed for stepping up to continue advancing the craft!    #AI #ProductManagement #AINative #FutureOfWork #Leadership

20

1 Comment

👀 Have you been watching the TV series 𝗧𝗵𝗲 𝗣𝗶𝘁𝘁? ✋ I have been binging (unfortunately, one of my worst vice). How about that AI notetaker that Dr. Al-Hashimi was trying to get the ER to 𝗔𝗗𝗢𝗣𝗧? Read more about it here: https://lnkd.in/dh272ygX This little bit is surprisingly so relevant to my work. Not because of the AI feature, but because I truly see how building great technology is only half the battle—adoption is everything. In healthcare, even the most innovative solutions face a tough reality once they leave the lab. It’s not just about performance metrics or clinical validation. It’s about fitting into real-world environments where time is limited, workflows are complex, and trust has to be earned. A few challenges that stand out:  • 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 & 𝘂𝘀𝗮𝗯𝗶𝗹𝗶𝘁𝘆 – If it’s not intuitive, it won’t be used consistently  • 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 – Even small disruptions can slow down already stretched teams  • 𝗖𝗹𝗶𝗻𝗶𝗰𝗮𝗹 𝘁𝗿𝘂𝘀𝘁 – Adoption depends on confidence, not just capability What’s interesting is that success often comes down to the “non-technical” pieces—listening closely to users, iterating based on feedback, and designing with their day-to-day reality in mind. At Oncoscope, we understand these pain points. That's why: 👆we built our interface to be a 𝗷𝘂𝘀𝘁 𝗮 𝗳𝗲𝘄 𝘀𝗶𝗺𝗽𝗹𝗲 𝗰𝗹𝗶𝗰𝗸𝘀 from a living SLR evidence library to a customized PICOS SLR report 🌐 no training or downloading required, 𝗳𝘂𝗹𝗳𝗶𝗹𝗹 𝘆𝗼𝘂𝗿 𝗲𝘃𝗶𝗱𝗲𝗻𝗰𝗲 𝗻𝗲𝗲𝗱𝘀 𝗮𝗹𝗹 𝗮𝗰𝗰𝗲𝘀𝘀𝗲𝗱 𝗼𝗻𝗹𝗶𝗻𝗲 𝗳𝗿𝗼𝗺 𝗼𝗻𝗲 𝗽𝗹𝗮𝗰𝗲 🔗 𝘁𝗿𝗮𝗻𝘀𝗽𝗮𝗿𝗲𝗻𝗰𝘆 of a clear SLR protocol and each individual publication traced back to the 𝗼𝗿𝗶𝗴𝗶𝗻𝗮𝗹 𝘀𝗼𝘂𝗿𝗰𝗲, and trust me, the numbers DO add up! Innovation in healthcare isn’t just about what we build. It’s about whether it actually gets used—and makes a difference when it matters most. Curious to hear from others in the space—what have you seen make or break adoption?

11

1 Comment

Looking to land your first Product role? Here are five things you can do this week to get a leg up on the competition. 1️⃣ Pick one of the vibe coding prototype tools and teach yourself how to use it. Doesn’t need to be amazing, and you can just pick your favorite website or app and try to replicate it as closely as possible. I go with Bolt for my own projects and for the cost of an oat milk latte, you’ll have enough credits to get a decent prototype.  2️⃣ Reach out to five second degree connections and ask to have an open-ended chat with them. Brag about yourself and tell them what THEY can learn from you. Not everyone will say yes …. But you’ll find someone that has a little free time and is curious to learn. Reverse mentoring is a thing - don’t assume you don’t have something you can teach. 3️⃣ Reach out to colleagues in other departments and ask them if you can shadow a meeting or help out on one of their projects. I probably learned more about Product by watching OTHER teams work than watching my own team work. Figure out where you can fit in and how you can improve the way different teams work with each other. 4️⃣ Get away from your computer but bring your phone or a small notepad. The shower principle is true. When you turn off your brain, you get your best ideas. So go for a walk, take a yoga class, bring a book to a coffee shop. But jot down your great ideas when they come to you. 5️⃣ Pick a book or a podcast to dive into. Highly recommend Upstream (https://lnkd.in/ekufQJq6) to read and then either Lenny's Newsletter, The Media Copilot, The Product Manager, or Decoder to listen to. Any tips I'm forgetting? Drop em below

12

4 Comments

Last week I had the privilege of speaking with 200 + future  Haasies about the incredible entrepreneurship ecosystem at Berkeley. (Ignore the less‑than‑flattering photo of me 😊.) Huge thanks to Rhonda Shrader for inviting me to share the lessons I’ve collected this past year building FeatureBox AI A few questions from the session stuck with me, so I’m sharing the highlights here for anyone on a similar path: 1️⃣ “What are a few things an MBA or non‑technical founder actually contribute in the earliest stage?” (While there are many, here's my top favs)   • Storytelling: You must make people(customers, teammates,investors) care—about the problem, the market, and why you are uniquely equipped to solve it.   • Domain expertise: In the early years you’re effectively the first (and only) product manager. Become the resident expert—or show you’ll get there fast—and you’ll be irreplaceable. 2️⃣ “What are realistic career options if the startup doesn’t go as planned?”(A few that jump out to me)   • GTM / Sales: If you owned narrative, distribution, and customer conversations.   • Product Management: If you lived in the problem space, shaped the roadmap, and stayed close to tech + users.   • Chief of Staff / Strategy: If you wore every hat and kept the engine running. Focus on the skills you’re actively leveling up and benchmark against the best in those roles. 3️⃣ Parting advice I wish I’d heard earlier:   • Don’t over‑analyze—your story can be a work in progress. It need not make sense to everyone out there.   • Execute, test, learn; even a failed experiment beats a perfect strategy doc collecting dust.   • “No” is just a data point—keep iterating. Grateful for the chance to pay it forward and can’t wait to see what this next wave of entrepreneurs builds. 🚀 #BerkeleyHaas #Entrepreneurship #Startups #MBA #FeatureBoxAI

48

1 Comment