Amit Kumar

Don't Build a Better Wheat Farm" - Why Defensibility Stakes Are Higher in Deep Tech Just published a new piece on my "Ignore the Confusion" blog, building on thoughtful insights from Eric Ver Ploeg at Tunitas Ventures about startup defensibility. Eric's core thesis: Too many startups pitch like wheat farmers - "huge TAM, slow incumbents, growing market, domain expertise" - but fail to think through long-term defensibility until it's too late. From a deep tech perspective, the stakes are even higher: ** Unlike software, deep tech founders must commit to defensibility strategies from day one - their funding depends on it ** Patent vs. trade secret decisions are often difficult to reverse and shape your entire competitive strategy ** Even "picks and shovels" providers (the tools that make industries more efficient) become commodities without proper moats The key insight that resonates: Defensibility can't be retrofitted. Whether you're building software or deep tech, your moat must be architected into the business model from the start. Thanks to Eric Ver Ploeg for sharing these insights on startup strategy and letting me build on his framework from a deep tech lens. Read the full post: https://lnkd.in/dEj_iF-Q #DeepTech #StartupStrategy #Defensibility #VentureCapital #Innovation

21

2 Comments

Two trends in fundraising that I’m seeing on a daily basis: 1/ The "we'll monetize later" era for infrastructure startups is dead "We'll figure out revenue once we have users" / "we're focused on adoption first"/ "monetization comes later" This worked in 2021. It doesn't work now. Today’s market won’t reward research organizations or companies that believe in perfection over getting it in users' hands. If you don't have a clear path to revenue… you won't get funded. period. VCs aren't writing checks hoping you'll figure it out later. 2/ "Vibe ARR" is everywhere Remember Jasper? hyper growth, but the model companies ate them alive. We're seeing this again. Companies growing really quickly on point-in-time technology that isn't defensible These companies look amazing on paper. Growth charts going up and to the right. But if you think models are getting better and becoming platform companies, many solutions become obsolete. 

162

19 Comments

PSA to seed and early-stage founders: stop worrying about competition. I’ve spoken to hundreds of late-stage founders, and they all say the same thing. The biggest mistake they see at the early stage is founders obsessing over who else is in their space. When you are pre-PMF, comparing yourself to other buzzy AI startups is a distraction. They already have a defined GTM motion, some level of product-market fit, and a playbook to execute. Their “big new feature” might just be about expanding revenue or building parity. You’re still trying to land your first 10 paying customers. Here’s the truth: 1. Worry about competitors only when you actively lose a deal to them. THESE ARE THE COMPETITORS TO WORRY ABOUT. 2. When a customer chooses someone else, they will usually tell you why. Nine times out of ten it’s not the reason you think. It’s rarely a missing feature. More often it’s pricing, brand trust, or timing. 3. Competitors often move in completely different directions. OpenAI went after consumers, while Anthropic leaned into enterprise and APIs. Playbooks diverge fast. 4. The only real roadmap at the early stage is customer pain. Every conversation, every demo, every user insight. Talk to as many customers as possible. If you spend your time trying to copy what competitors are doing, you will always be a step behind. If you spend your time talking to users, you’ll know exactly what to build next. The path to PMF isn’t found on Twitter threads about “AI competitors.” It’s found in the feedback from the 5 people actually using your product every single day.

55

10 Comments

Hot take: lot's of #LP's are growing underwhelmed with traditional venture investing. 💰 Fees are high given the level of engagement with the company operators. ❓ Access is opaque - LP's are unclear on the portco operations and outcomes. Outcomes are scattered - power law investing can certainly work, but many feel that venture capital investing is just a numbers game. There's another way. I'm biased, but I think it's better: #VentureStudios as an asset class. They blend: 🤜 🤛 Control and ownership 💡 Thematic focus 👬 Partnership with operators Studios offer a fund-like structure — but with more alignment, higher value conversion and less noise. If you're interested in understanding more about the studio model, we have resources to share. Please reach out and let's connect!

12

An emerging VC manager's fundraising lessons... the first two funds are a grind. Now, we’re on our third fund, it feels like we’re almost over the hump, but fundraising never gets easy for most of us. I want to congratulate the emerging VC firms presenting at this year’s RAISE Global conference. As former RAISE presenters, and (soon-to-graduate) emerging managers, we thought we’d share this LP Translator, a lighthearted guide to decoding what LPs really mean during the fundraising process. Fellow GPs, which ones did I miss? 👇 The LP Translator 📣 "Let’s stay in touch.” Translation: We’re not interested. “We want to see your track record develop.” Translation: Either we don't believe in your strategy, or we’re focused on managers with more buzz. “We’re not allocating to new managers right now.” Translation: We’re not allocating to you right now. "Show us your deals so we can get to know you.” Translation: We’d like free co-invests if you get something hot. “We need to see more DPI before we commit.” Translation: We don’t really understand VC, but we’re pretending to. “We’re fully allocated for this year; check in early next year.” Translation: Next year we’ll still be fully allocated (just not to you). “Call us before final close.”  Translation: I’m too polite to say no at this time, so I’m kicking the can down the road. “Your fund is too small.”  Translation: Okay, that one might actually be true (for some LPs). “We went through your data room and want to meet face-to-face.” Translation: We’re genuinely interested, keep going! “Can you send us your LPA for signature?” Translation: Let’s go! 🚀 -------------------------- Fundraising is a long game, longer than we ever expected. We're now seeing how LP relationships are built across several funds, not several months. If they’re investing time to learn about you and your strategy, that’s your best signal of real interest. #emergingmanager #venturecapital #LP #RAISEGLOBAL

52

1 Comment

founders that have only ever worked within a large company tend to be empty vessels. the most valuable skill at a big company is identifying who has (or could soon have) power and then aligning with and advocating for their ideas as if they were your own. take a spin through the recent YC class and you see a pattern of big company mids all founding the same AI for xyz... its not really their idea, it just sounds good. the board meetings will be especially painful. founders acting like they work for the investors, seeking approval, lost in the woods. there are exceptions. but they tend to be founded before zirp. when founding a company was hard and low prestige and there wasn't capital at every turn. an empty vessel doesn't jump into the abyss without first raising a $5m round from the 9 figure 'seed firms'. 

20

4 Comments

The YC W26 batch is settling into rhythm, and week by week, the direction of this cohort is becoming clearer. As always, Y Combinator selection process acts as a powerful market filter: thousands of applications distilled into a small group of founders whose focus often hints at what’s coming next. This week’s launches suggest a batch leaning into complexity, regulation, and the real-world systems that actually keep the economy running. What stood out: 🧬 Healthcare & life sciences are gaining momentum Companies like Ruma Care, Rhizome AI, and Strand AI reflect renewed founder interest in regulated healthcare, biotech, and life-science workflows. From prior authorization and regulatory intelligence to biological datasets and financial crime prevention, these teams are tackling high-stakes problems where accuracy and trust matter deeply. 🏭 Manufacturing, logistics, and the physical world are being supercharged by AI Startups including Kyten Technologies, Servo7, Inviscid AI, and Pollinate are applying AI to atoms — battery manufacturing, adaptive warehouse robotics, building and data-center optimization, and ERP-layered supply chains. This is practical AI, focused on efficiency and resilience. 🏢 Enterprise operations continue their AI-native rebuild General Legal, FullSeam, Oximy, Orthogonal, Librar Labs, and Booko are rethinking legal services, finance ops, AI governance, API infrastructure, inventory management, and dynamic pricing. Less dashboard-watching. More execution. Taken together, this feels like a turning point. Early-January experimentation is giving way to conviction — companies built for regulated environments, physical infrastructure, and enterprise-scale execution. This week’s Fund Manager Picks: 🔹 Rhizome AI — Always know what the FDA thinks Citation-backed, hallucination-free regulatory intelligence for life sciences. Already generating six-figure revenue and becoming indispensable for regulatory affairs teams. 🔹 Inviscid AI — Real-time building simulations Physics-informed AI and digital twins that optimize energy use, HVAC efficiency, and air quality — pushing building management beyond rule-based systems. 🔹 General Legal — The AI-native law firm Flat-fee, high-quality contract drafting and negotiation for growth-stage companies. Contracts in hours, not days. 🔹 Servo7 — Autonomous warehouse robots Flexible, learning-based robotics that adapt as warehouse needs change — increasing value over time rather than becoming obsolete. 🔹 Booko — Dynamic pricing for service businesses Bringing marketplace-style pricing to appointment-based services, unlocking ~20% revenue uplift by monetizing perishable time slots. More to come — but this week’s launches made one thing clear: YC W26 founders are building for the hard, regulated, and deeply operational parts of the economy. And that’s where things get interesting. https://lnkd.in/edAyRgRk

22

SF VC Takeaway #2: Pricing expectations, performance bars, and what’s actually getting funded. One theme that came up repeatedly in SF was how far pricing expectations and performance bars have shifted, even compared to just a few years ago. A few things investors kept anchoring to: 1️⃣ Median Series A valuations are higher than their 2021 peaks, but fewer of them are getting done. 2️⃣ Capital is being concentrated into fewer and fewer companies (and lots of capital!) 3️⃣ “Good” progress is no longer enough and the bar for standout performance has moved in an AI-native world So what does “top performance” mean right now? One investor told me that top quartile seed companies in their portfolio are going from $0 to $2M in ARR in <12 months. Outside of pure traction numbers, a few other themes that came up to describe "top performance": 📈 Explosive early revenue ramps (or a very credible path to them) 📊 Strong velocity and momentum for 2 quarters in a row, even if the baseline is small. 🚀 Clear signals of category leadership, not just product-market fit. Sometimes shown by either domain expertise, speed of product optimization, or by lack of competition in the category. This creates a counterintuitive dynamic where it can be easier to fund a company with strong pedigrees in a hot space and no traction yet than a company that went from 0 to $1M ARR at what used to be considered a rapid pace. Pricing today is driven by trajectories, not moments in time. We used to say investors invest in lines not points; I think that's more true than ever now because crossing certain milestones doesn't carry as much influence as it once did. Finally, investors still say that valuation matters, but many of them are acting differently. Pace and belief in category-defining companies really sets the price; while slower growth gets scrutinized rather than discounted. One silver lining in the camp of durable growth: Series A rounds are happening so fast that many companies don’t yet have meaningful history of retention data. Large bets are being made on velocity before the durability is proven. Several investors told me the same thing: we may soon swing back to a market where retention, not growth, becomes the defining metric. Let's hope so. I'll share my third SF VC takeaway tomorrow!

59

7 Comments