Alex Vogenthaler

We continue to see fintechs launch their own chains. First Circle with Arc. Now Tempo from Stripe. In today's webinar, folks asked, "Do we really need another payments chain?" The answer depends on where you are in your journey. At Dynamic, we’ve seen this play out across every type of builder (fintechs to consumer apps to onchain infra teams). The truth is: there is no single “right” chain. There are only tradeoffs. - L1s (like Stripe building its own): Maximum control, but higher setup fees. You own the infrastructure and the overhead. - L2s & rollups (like Robinhood's choice): More agile, but built on shared foundations. Optimized public chains (Solana, Stellar, Spark, etc.): Fast, cost-efficient, and ready to go. They're great for teams that want to launch quickly without reinventing the wheel. My recommendation: Start with what’s performant and proven. Chains like Solana Foundation, Stellar Development Foundation, and Lightspark get you to market fast. Once you’ve found product-market fit and scale, then revisit whether spinning up your own chain makes sense. – 🔁 Share this post if you found it helpful. ➕ Follow me (Itai Turbahn) for more posts on stablecoins and crypto.

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Moov's biggest competitor isn’t another platform. It’s doing nothing. When we talk to customers about why they haven't new payment rails - like FedNow, Visa Direct, or RTP - tech is almost never the blocker. It’s uncertainty. Nobody wants to juggle multiple sponsor banks, hold extra reserves, or run separate KYC flows just to “see who uses it.” They can’t put a confident forecast on adoption, so they don’t even try. That’s the real growth challenge: Not convincing people that we’re better at Visa Direct. But making it safe/easy for them to take the first step in offering it and seeing if customers bite. If we want these rails to grow, we have to make testing low-risk, ROI visible, and adoption as close to one-click as possible. When the alternative is “do nothing,” the friction has to be nearly zero.

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$550k left on the table. For over a year. And nobody knew. A fintech lender we onboarded had been understating their borrowing base since day one. Not fraud, just data errors compounding across multiple systems. The culprit? There were many errors but one that stood out were duplicate payments that made outstanding balances look smaller than reality. This led to them over-pledging $550k into their facility, turning it into dead capital that should have been working for the business. At 14% interest, that mistake was bleeding $77k annually in cash drag. Money sitting idle while the business was trying to get advance rates increased. This wasn't a sophisticated error, just basic reconciliation failures between systems. But with integrated systems talking past each other, the errors slipped through every review. In a market where every basis point matters, leaving $550k of capacity untapped because of duplicate payment entries is inexcusable. The fix isn't revolutionary. Transaction-level verification. Daily reconciliations between systems. Automated flags for duplicate entries. Basic blocking and tackling that most lenders do to catch most errors, but which when not done leaves them vulnerable to reporting issues. We see this pattern repeatedly: companies trust their reporting because the numbers look reasonable. But reasonable-looking numbers can hide massive inefficiencies when nobody's checking the underlying transactions. In private credit, the difference between winning and losing often comes down to deploying every dollar of available capital efficiently. At Cascade, our data validation system runs 60+ checks on all new raw data, catching boring stuff like duplicate or missing data that most teams skip. But catching one duplicate payment sequence can unlock millions in working capital. Trust your data, but verify every transaction.

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𝗛𝗼𝘄 𝘄𝗲 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗮𝘁 𝗣𝗮𝗿𝗰𝗵𝗮 We recently wrote an engineering memo for new hires outlining how we operate at Parcha through our company values. Here are some highlights. The full memo is in the comments below. ⏱ Act with Urgency: While startups are chaotic, having rituals keeps the engine running well-oiled. We operate in days, and ensure we meet all of our weekly rituals every week: planning → kickoff → standups → Thursday hack night, → Friday pizza from Il Casaro. AJ Asver likes to say that "we should never be the bottleneck". If we commit to building a feature for a customer, we commit to doing it in days. We may start with something rough, but try to get it in front of the customer as soon as possible to gather feedback. We are also on the hook for support, and always respond to customers promptly, even if it's a "we're looking into this". ✨ Make it Dope: We care about the craft in everything we do. From our swag, website, marketing, our office, how we talk to each other, etc. That also reflects in how we build. We have abstractions we've invested in heavily for LLM workflows and other areas. We use them and make them better. We also apply a common sense principle when building new abstractions: build it once → consider abstracting it if building it twice → "the third time, either build the abstraction, or you're not doing your job." 🛠 Build with Rigor: With the acceleration of AI-generated code, it's more important than ever for an engineer to get really good at reading and reviewing code. Our PRs start with a self-review, and engineers are responsible for any bad AI-generated code making it to a PR. "It's not AI slop, it's your slop." LLM workflows need to scale, on token capacity, on accuracy, and most importantly, on cost. A simple mantra when building LLM workflows is "make it work → make it dope → make it cheap—never more expensive." 💭 Believe: What was impossible 5 years ago may now be very hard, but possible. In a year or two, it will be routine. If we do not build it now, someone else will. That's why it's essential to always ask ourselves, "How can we make this work?" instead of defaulting to "This is not going to work." This unwavering and sometimes irrational belief is our fuel. When in doubt, look at that yellow Believe sign on our wall and remember, as Samuel Rivera yells every Monday morning after kickoff: "Let's go!"

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Perigoso isso. "Later-stage startups are increasingly turning to venture debt as they struggle to keep up with growth expectations from VCs, and as a way to avoid raising equity financing at lower valuations."

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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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