Rob Kischuk

So yeah – Capital One is acquiring Brex. Big number. Loud headlines. But the interesting part isn’t the card. Capital One didn’t buy a startup-friendly corporate card. They bought infrastructure. Brex quietly moved from “cards for startups” to something much closer to a horizontal spend + payments layer that actually plugs into real finance teams, real ERPs, real controls. That’s the asset. A product banks can distribute without rebuilding it from scratch. Inside the perimeter. On their rails. With their balance sheet. Now compare that to Ramp. Same market. Similar surface area. Very different outcomes (so far). Ramp is still priced as a growth company chasing category ownership. Brex is priced as a product that a bank can absorb. Neither is “wrong” – but only one of those is immediately acquirable. And yes, the irony is strong: Ramp’s founders previously sold a company to Capital One. You really couldn’t script it better. After closing Discover, Capital One now has: – a card network – distribution – underwriting – and a modern spend platform At some point you stop partnering and start owning. $12.3B → $5.15B looks rough if you freeze the chart in 2022. But this is still a real outcome for the founders, the team, and early believers. Brex looked written off more than once. Instead, it pulled off a quiet comeback and a very bankable exit. Guess you can’t Brex the laws of finance forever, eventually you have to Capital One-solid footing. ¯\(ツ)/¯

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Reading Metronome’s Monetization Operating Model, I kept coming back to one idea: pricing has become product. Software now delivers outcomes, not access. Yet most companies still charge as if they’re selling seats or licenses. That disconnect creates friction: for customers, unpredictability; for companies, stalled growth. The paper’s argument is simple but sharp—monetization isn’t a late-stage decision. It’s strategic infrastructure. Pricing needs the same ownership and iteration as any feature. Treat it like a surface that customers touch, not a spreadsheet buried in finance. If value is continuous and dynamic, pricing must be as well. That means product, GTM, finance, and engineering working from one system of truth. How many of us still treat pricing as an afterthought—when it should be a growth engine? https://lnkd.in/gnH7WzYf #Monetization #ProductStrategy #AI

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Crunchbase CEO Jager McConnell has the most non-obvious AI vision – he thinks VCs should plan for 2yr exits on everything 👀😳 today’s World of DaaS pod: super deep insights into every deal in venture https://lnkd.in/ebJ9rWrs

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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. 

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Startup Founders: this is the secret 🤫 to raising money for your startup: Investors are desperate to find great companies to invest in. Angel investors put money into founders and business ideas that solve a big problem for customers that could be potentially huge and explosively growing market. VCs want to deploy capital to help companies grow. Companies the have proven their business at a basic product-market fit level. If you cannot get investor interest in your company, there is usually one of three reasons: 1) You are too early for the investors that you’re pitching to. 2) You don’t have a solution that addresses a big customer problem in what could be an large and explosive market, where you have an unique value proposition, and a sustainable competitive advantage. At least from the investors perspective. So this could be true, or a perception based on your inability to convince them with evidence. 3) The investors don’t beleive in you and your team. This can be hard to swallow. But not all investors are the right fit for every team. And you may need improvements in your team. There can be a number of reasons behind this one including: (a) they don’t think you have the business, technical, and/or market domain expertise to win; (b) they don’t know, like, and trust you; (c) they don’t think you have the ‘right stuff’ to stick it out when things get rough. You can mitigate or eliminate ALL of these issues. It comes down to the secret: Build better companies. A lot of ‘entrepreneurs’ don’t want to hear this: The problem isn’t the investors. It is you. Great businesses with great teams and stellar leadership always get funded. It may take creativity and tenacity and a lot of investor ‘NO’ answers, but they ALWAYS get funded. Agree or disagree?

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Here’s the thing. Where CEO nightmares come from. Your contractor says the Node.js app will “work perfectly”. Then you switch the ads on. Everything crawls. Sales drop. Support explodes. What happened? Capacity is math. Not hope. Node.js runs JavaScript on a single main thread by default. One loop. One lane. It can do lots of I/O in parallel, but the lane is still single for code that runs on CPU. When more work arrives than that lane can serve per second, a line forms and response times spike. Think of a checkout counter. If 10,000 people show up and your counter serves 100 at once, 9,900 wait in line. The longer the line, the slower it feels. That’s a simple law of queues. More arrivals with the same speed mean longer waits. And here’s the trap. When it slows, browsers and apps retry. Those retries add even more traffic. That creates a feedback loop that tips systems over. The fix is controlled retries with backoff and jitter. It’s a standard reliability practice for a reason. Why turning ads off rarely saves you in time? Agencies and platforms deliver traffic on schedules. Programmatic slots are bought. Shutoff can take hours. You keep paying while your site shows spinners. The only winning move is to be ready before the spike. That means pre-scaling and warming capacity so new servers are ready to serve right away, not still booting while users bounce. (AWS Documentation) What “ready” looks like in plain English. 1. Know your lane size: How many requests can you serve per second at your target response time. This is just arrivals, service time, and queue length. We calculate it with a simple formula from queuing theory and prove it with load tests. 2. Use all the lanes: Run multiple workers across CPU cores and multiple pods across machines. But don’t let them fight over one hot resource. We remove shared chokepoints so extra pods actually add speed. Official docs explain the single-threaded event loop model. We design around it. 3. Isolate blast radius: Split by region or tenant so one surge does not take everyone down. Separate databases or partitions where it matters. If one area spikes, the rest stay fast. 4. Pre-scale for campaigns: Warm instances and containers before traffic lands. Use scheduled or predictive scaling and warm pools to cut spin-up time. (AWS Documentation) 5. Add backpressure: Set fair limits at the edge. Cap queue depth. Fail fast on non-critical paths so checkout and sign-in stay alive. Retries must use exponential backoff with jitter and hard ceilings. No retry storms. (Amazon Web Services, Inc.) 6. One-click ad kill switch: If error rate crosses a threshold, pause campaigns in one click. No committees. Save the budget. Restart clean. If you plan to push 10,000 people through a counter built for 100, it will feel slow or die. That’s not a mystery. That’s physics with invoices. We fix the counter. We add lanes. We make sure the lights are on before you open the door. We’ll handle it.

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New startups today mostly don’t need VC money. Build costs collapsed...Distribution is accessible...AI turned small teams into highly leveraged operators. Reaching revenue no longer requires raising first. This creates a structural shift in venture itself. Mid-size VC funds ($100M–$1.5B funds) are the most exposed. Too large to write small experimental checks early. Too small to consistently lead or win competitive later rounds. They sit in the middle while the market moves around them. Meanwhile, two ends of the spectrum are strengthening. Large funds ($5B–$20B+ AUM) are the real winners. They provide scale, signaling, and the ability to deploy $50M–$300M checks once companies prove momentum. Micro VCs ($5M–$100M funds) will thrive for the opposite reason. Fast decisions. $50K–$1M first checks. Access before consensus forms. That said, venture math at the micro level gets tricky. In many cases, ownership, management fees, and outcome distributions make the economics challenging for GPs unless they consistently access outlier winners. The hardest place to be right now is the mid-tier. Too big for experimentation. Too small to dominate late-stage.

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Why do developers leave after 6-12 months with most agencies? Because most staff augmentation agencies ROOT for your developer to quit. Sounds extreme, but follow the money. You pay $10-12k a month. The engineer receives $4k. The agency keeps the $8k spread. As the engineer gains tenure, they become more valuable to you and more expensive for the agency to retain. The easiest path is churn: replace them, reset the salary, and preserve margin. That’s why attrition is built into the model. Your success doesn’t compound; their profits do. We built Remotely on the opposite principle. Developers keep 100% of their negotiated rate. We charge a flat fee. When the engineer grows, both sides win. Retention has stayed above 90% for 3+ years. Transparency doesn’t sound like a growth strategy, but it’s the one thing that compounds better than churn.

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99.4% telemetry distillation. That's the latest benchmark for OtterMon AI's MVP build. But you might be surprised to hear data optimization isn't our primary focus... Our platform is designed to help customers *prevent* security incidents and business outages instead of them constantly reacting to problems. We accomplish that by sitting on top of their existing DevOps tools and analyzing their holistic digital footprint. What are they monitoring? What vendors are they using? What critical context is hiding in documentation, code, and runbooks? Today, trying to process all that data just doesn't scale. But by solving the data volume problem first, we also solved the data silo problem. And now our customers can see auto-detected issues, risks, and optimization opportunities instead of drowning in disparate dashboards and endless alerts. That's the power of Unified DevOps Intelligence 🚀

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Not every product failure is a tech problem. Some are taste problems. Quinn Favret and Hassaan Raza make a powerful case in this episode. Fast shipping is great. But if you don’t love what you’re building or who you’re building it for, it shows. This conversation is a reminder to create with conviction, not just code. Want more insights like this? Subscribe to The AI Report here: https://lnkd.in/gGi2d5fK

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