E13: Crypto, the Fed, and Venture Competition with Eric Golden

Alex Rubalcava, Managing Partner at Amplify, joins Joe Magyer to discuss contrarian early-stage investing, how AI is reshaping software risk, and why some of the best venture opportunities attract little competition. They also cover greenfield markets, capital efficiency, lessons from public-market investing, expanding a circle of competence, and how to tell productive persistence from simply grinding on something that isn’t working. Here's a longer breakdown of the conversation: Why technology risk may be overrated. Alex explains why technically ambitious startups have historically scared off many early-stage investors—and why being willing to underwrite that risk can create an edge. Today, as AI makes software easier to build, he sees more meaningful technical risk shifting toward hardware, physical products, regulated markets, and other areas where reliability matters. How AI is changing what investors should look for. Shipping features is becoming easier, so simply asking whether a team can build is less informative than it once was. Alex argues that investors increasingly need to understand whether founders know what to build, in what order, and how quickly they can adapt as technology and competition change. What public-market investing taught Alex about venture. His background as a contrarian, value-oriented investor made him unusually sensitive to valuation and trained him to ask: Why am I seeing this opportunity? That mindset helps him avoid groupthink and focus on situations where he has a differentiated reason to develop conviction. Why Alex prefers greenfield markets. Some of his favorite companies enter markets where there is no incumbent software vendor, Gartner category, or existing technology budget. Rather than competing against dozens of venture-backed startups, he prefers opportunities where a startup can create an entirely new market—or where incumbents are structurally unable to respond. How capital efficiency protects non-consensus companies. Being early and different only works if a startup has enough time to prove the thesis. Alex explains why he works backward from the milestones future investors will need to see and why AI-enabled efficiency can give companies more runway to remove product, technical, and market risk before raising again. Why a circle of competence should never be static. Alex traces his progression from enterprise software into robotics, space infrastructure, physical AI, and eventually space lasers. The goal isn’t to suddenly jump into unfamiliar sectors, but to expand expertise through adjacent investments until new categories become underwritable. Productive persistence versus grinding in place. Alex shares the story of a founder who worked relentlessly but never found meaningful customer adoption. The distinction, he says, is often the velocity of experimentation: productive founders continually test new products and go-to-market approaches, while unproductive persistence means repeating the same motion despite continued evidence that it isn’t working. Why conviction may matter more than allocation. Alex closes with one of his strongest contrarian views: companies that attract only one term sheet can sometimes be better investments than heavily contested rounds. Many of his strongest investments faced little competition, reinforcing his belief that investors should spend less time chasing hot deals and more time building independent conviction. Investing in Startups is hosted by Joe Magyer.

Gopinath Sundaramurthy is a Partner at Ensemble VC, where the firm uses data and software to systematically identify promising founders and investment opportunities at the earliest stages. In this conversation, we talked about how AI is changing venture capital, why data may become one of the few durable advantages between firms, and what happens when investors apply the same operating discipline they expect from startups to themselves. Gopi explains how Ensemble uses data to improve sourcing and diligence without trying to replace human judgment. The goal is to automate the work of finding and understanding companies so investors can spend more time building relationships, evaluating founders, and developing conviction. We also discuss how Ensemble evaluates founding teams, why Gopi believes most startup ideas are evolutionary rather than revolutionary, and why following where exceptional talent is moving can be more useful than starting with a fixed investment thesis. Gopi also shares his views on portfolio support, follow-on investing, and why many VC firms have been surprisingly slow to adopt the technologies and processes they encourage their founders to embrace. Investing in Startups is produced by Seaplane Ventures and hosted by Joe Magyer.

Abe Othman has spent years digging into AngelList’s data to better understand how venture investing actually works, not just how investors say it works. In this episode, Abe joins host Joe Magyer to talk about portfolio construction, check sizes, valuations, and the relationship between price and returns. They discuss how much investors should put into each deal, why owning more of a company isn’t always better, and what the data can (and can’t) tell us about building a strong early-stage portfolio. They also get into contrarian thinking and the importance of changing your mind when the evidence changes. Abe shares some of the beliefs he has reconsidered over the past few years and explains why good investing often means letting go of ideas that once seemed obviously true. It’s a thoughtful, numbers-heavy conversation about making better decisions in an asset class where the outcomes are extreme, the sample sizes are small, and certainty is usually an illusion. Investing in Startups is hosted by Joe Magyer. The show is a Seaplane Ventures production.

Nick Tippmann is the Founder of TipTop Ventures where he invests in vertical AI and applied AI companies at the earliest stages. In this conversation, we talked about vertical AI, systems of work, and why distribution may matter more than ever in a world where software is getting easier to build. Nick explains why vertical AI is not simply the next version of SaaS. In his view, the unit of value is shifting from time saved to work delivered. That changes the buyer, the budget, the pricing model, and the size of the opportunity. Where traditional vertical software captured a slice of software spend, vertical AI can go after much larger labor and services budgets by doing the work itself. We also discuss what makes vertical AI companies defensible. Nick shares why the best companies are not just thin wrappers on top of foundation models, but systems of work that combine workflow, context, proprietary data, and domain-specific judgment. He explains why OpenAI and Anthropic moving up the stack may actually prove that intelligence alone is not enough. A big theme in the episode is go-to-market. Nick argues that many fundamentals have not changed: trust, domain expertise, tight ICPs, fast time to value, and distribution still matter. But in an AI-native world, pricing is being rewritten, revops and go-to-market engineering are becoming table stakes, and founders need to think earlier about brand, community, and how they stand out in crowded markets. We also talk about Nick’s journey from operator to investor, what he learned as CMO of Greenlight Guru, what he saw early in GC AI, and what VCs and founders often misunderstand about each other. It is a conversation about the future of software, the realities of early-stage investing, and how to separate durable vertical AI businesses from the noise. Investing in Startups is produced by Seaplane Ventures and hosted by Joe Magyer.

This episode originally aired in September 2024 — and it's aged remarkably well. We're bringing it back with fresh context on why Niki's predictions have proven out.