Rohan Punamia

Want to see what Kernel’s CRM and account data actually look like? In last week’s session with Ramy A. from Pigment and Matthew Volm from RevOps Co-op, we walked through how enterprise RevOps teams are rethinking planning and account data management in the age of AI. The clip below shows how we use Kernel to map complex corporate hierarchies inside our own CRM and build the account data foundation that makes it possible. A big theme from the discussion was the shift from static to dynamic account data. Most teams still rely on rigid, once-a-year segmentation and firmographics that go stale quickly. The market changes continuously, and your planning needs account data that keeps pace. AI can help with this, but only if it starts with accurate entities, identities and buying centers rather than generic data from traditional providers. We also spent time on the power of custom hierarchies and real buying centers. Legal entities rarely match how a business actually decides or buys. Using AI to model the true structure of an organization gives RevOps a far more accurate base for planning, territory design and forecasting. This shift is already happening inside the enterprise RevOps teams we work with at Gong, Navan, Zip and Remote. It was especially valuable to hear how Ramy and the Pigment team use Kernel to build the account data foundation they need for accurate planning. If you missed the full conversation, the link is in the comments. Don't miss our next event with Jordan Crawford next Tuesday 📅

39

2 Comments

Too many vertical SaaS founders are burning down their markets before they even realize it. You hit $2M-$3M in revenue and think the next move is to scale like a horizontal company. Cold email programs. Spray and pray demand gen. All the tactics that worked for companies you read about on LinkedIn. It works for a quarter or two, then it stops. And by the time you realize it, you've burned through 2/3 of the companies in your vertical. I've worked with dozens of vertical SaaS and AI companies over the last couple years. The same mistakes keep showing up. Vertical markets have their own physics. Three laws in particular: Law 1: Brand velocity compounds fast Early at Levelset, we got into a public legal dispute with a competitor who ran the industry association for one of our core buyer personas. They banned us from their events. Made their position on Levelset very clear. We lost deals we didn't even know existed. Buyers disqualified us before we had a chance to earn their business. We spent 8 years working to overcome negative brand velocity with that segment. Your brand in a vertical is never neutral. It's either building momentum or losing it. And it compounds faster than you think. Law 2: Everyone on your team has to be an expert The founder knows the problem cold. But when you start hiring sales reps, marketers, and CS people, they don't have that foundation. At Levelset, we spent weeks onboarding new hires on how construction payments worked. The lien laws. The payment challenges. The GC and sub dynamics. Without that knowledge, they couldn't have real conversations or build trust. Your customers expect you to understand their world better than they do. Law 3: Vertical markets are local markets We struggled for years to build a repeatable mid-market sales motion at Levelset. Right ICP. Strong product. But we couldn't close consistently. Then we realized our best customers came through local referrals. A contractor in Dallas didn't care who we worked with in New York. They cared about the competitor across town using our software to gain an advantage. Everyone knows everyone in their city. They see each other at association meetings, industry events, job sites. They talk to each other often. You want your company to be part of those conversations. Show up to the conferences. Get active in the communities. Even better if you can own the community. Most industry associations haven't evolved in decades. Shift the center of gravity over to your brand. _______ The tactics change every year. The laws of nature don't. Build a great product. Know your customer. Educate the market. Show up in their world. When the vertical adopts your brand as the one they identify with, you'll have more demand than you can imagine.

60

12 Comments

GPT 5.4 dropped today. We’ve had early access for a bit - here’s what we’ve seen. We ran it through our benchmarks across hundreds of real-world workflows. The finding that matters: prior models quit after 3-5 attempts. 5.4 doesn’t give up. Our reports say it’s the new state of the art model for persistence and multi-app workflows. With other models when the model finds an obstacle, hits a dead end, and gives up. The human has to pick it up from there. 5.4 changes that calculus. For the first time, we're testing a model that behaves less like a tool and more like someone who actually wants to finish the job. The tradeoff is real: it's fast and occasionally overeager. Build a plan before you let it run. But directionally? This is where the industry has to go. Now available in Zapier. Try it and let me know what you’re seeing.

40

3 Comments

The Neo robot hype reminds me of what is wrong with AI in GTM right now. Cool demos. Product based on hype. Lots of potential. But the reality is MUCH harder and not as cool as everyone is expecting. If you don't know the robot is being sold as something that will do all your chores for you autonomously. But in reality it can only open a door autonomously. Everything else it will do will be controlled by some dude sitting in an office somewhere. Side point: Not creepy at all to know a random person you don't know basically has control over a robot in your house. The same thing is happening in AI. There are loads of cool demos of products, automations, vibe coding... But when you ACTUALLY try and do the work yourself with your own hands the reality is it's bloody hard to get even simple things working well. That said, it's not impossible. We have some cool things running at CS2 and I use AI to help me with a ton of day to day work. But the hype and expectations are off the charts. So lots of people are feeling bit of buyers remorse and expectations not being met. Which sucks because the tools we have today are really good. Just think back just a few years ago, the progress is massive. The hype train people just need to temper expectations a bit so reality can catch up with expectations. I am always reminded of the quote: 'Most people overestimate what they can do in one year and underestimate what they can do in ten years.' Very true here.

14

2 Comments

New podcast drop with Alex Oppenheimer is live 🎙️ We went deep on what really drives PLG - and why most teams get it wrong. Here’s what we covered: > What PLG actually means: your product should do the job of Sales/CS - guide, qualify, and tell the story inside the experience. > Why focus wins: one lever, done exceptionally well, compounds everything else - activation, retention, and CAC. > AI ≠ magic: Prompt bars and “wow” moments drive curiosity, but long-term adoption still comes from solving a real problem with guided context. > Why bring in specialists: Even great teams only tackle onboarding a few times. Repetition across dozens of SaaS products shortens the learning curve - and avoids the usual pitfalls. And a whole lot more in our 30-min chat… When I started Valubyl, the goal was simple: solve one painful, repeatable problem - self-serve onboarding and activation. At first, we were advisors - helping SaaS teams spot what wasn’t working and what to fix. Now, three years later, we’ve evolved into an execution-first agency - not just telling teams what to do, but actually doing it for them. Our core offer: In 2-4 weeks, we ship a redesigned onboarding experience your team can launch and see the results - no fluff, just outcomes. If you’re trying to turn more signups into revenue, see what great activation actually looks like, and get a better understanding of what it takes to win with PLG - this episode’s for you. Comment ALEX and I’ll DM you the link... ... just joking :) check the first comment.

41

11 Comments

This alone is a $1B+ idea. Price discovery for compute is a huge issue. If you want to price compute, you have to email/call every neocloud. Everyone gives a different price. Some deal direct, others push you to brokers. + all the creative financing deals complicates price discovery. Compute markets solve this.

111

23 Comments

Yesterday Clay hit $100M ARR and I shared a post on the GTM bets that got us here. Today, I'm sitting down with our Head of Finance to dive deep on the business - metrics, our view on the AI market, and the path to $1B. Karan often gets this question from candidates: "Look, I have to dedicate my livelihood to Clay. All the upside of my equity is baked into one asset. How should I frame the real risk/reward?" It's a great question! So I wanted to use this video to go beyond the tactics and share how we think about the business holistically. The fundamentals, market dynamics and where we're really going. Some of what we cover: - The AI market and why GTM is actually the least crowded - Cohort data that shocked even us (enterprises never churn!) - How we've built an entire economy around Clay - The three things that create our customer flywheel - Why we're not burning cash while growing at an insane rate - The vectors to $1B: new geos, personas, use cases, channels, and verticals At the end, we get candid about the real risks and why World of Warcraft helps explain them. Watch here 👇

460

44 Comments

If I look across every demo I sit on, every product briefing I get, every cadence I read, every discovery call I sit on, I think there's one boulder standing in the way of GTM teams succeeding that many org may not even realize is an issue: Across roles, I see a lack of understanding on why their product matters to their buyers or end users, which means we're disconnected in what would drive someone to buy or adopt their product. The user interface is amazing. We can source this data for you at a low cost! The integrations are unparalleled. You can boot this right up in Claude! Our analytics have never been more robust. You can create lists and run searches! Great. So...what...? We've talked about this for ages: feature + benefit to the max, but what are we doing to really connect product, PMM, and sales to deliver a message that will actually get buyers to want a meeting, take a demo, and find a path to purchase? #samsales

94

47 Comments

Fun dinner last night with an exciting group of founders and builders in San Francisco. The conversation went many places...we got into how pricing models are being upended in the AI era, whether the application layer is disappearing or being fundamentally reinvented, what actually predicts AI adoption inside organizations (spoiler: it's not age or technical background), and how go-to-market is shifting as the cost of building software collapses. A few threads : * The app layer isn't dying, it's shapeshifting. Foundation models are pushing into the application layer, but that doesn't eliminate apps. It reinvents them as the context-aware scaffolding around intelligence. The next generation of durable software businesses will be built with . * Curiosity is the real leading indicator. The strongest predictor of AI effectiveness inside an organization isn't domain expertise or seniority : it's the intrinsic drive to go try things. Most performance management systems don't even measure for this. That's a blind spot. * Pricing is an important unlock, and most companies are stuck. We're shifting from seat-based to outcome-based, but most teams haven't defined what "outcome" means for their product yet. True outcome based pricing that actually aligns with how customers experience value is hard to build but a massive competitive advantage. What I love about these conversations is that the questions don't have clean, binary answers, and everyone in the room knows it. That honesty is what makes the thinking sharper. Thanks to Matthew Jacobson, Kelly Zheng, and the ICONIQ team for bringing together such a thoughtful group.

284

17 Comments