Gokhan Celiker

🚀 Can efficiency be the ultimate unfair advantage in fintech? In Episode 516 of The CTO Show With Mehmet Gonullu, I sit down with Tomas Navickas, Co-Founder & CTO of myTU, a digital bank that famously ran its entire operation on less than €1K/month in cloud costs. We dive into: ✅ How efficiency became a moat for myTU ✅ Using AI for fraud prevention and compliance ✅ Why APIs are reshaping B2B payments ✅ The next wave of digital banking innovation Tomas’s story is a masterclass in building lean, scalable systems while competing in a highly regulated industry. A must-listen for founders, tech leaders, and fintech enthusiasts. 🎧 Episode 516 — Efficiency as an Unfair Advantage: Tomas Navickas on Scaling Digital Banking Available on all podcast platforms + YouTube (links in comments).

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At Vibe Capital, we believe the venture landscape is bifurcating. The reason is simple: reality is full of drunk cats. "Drunk Cats" are the emergent, second-order effects that arise from simple rules. They can tank a product, entire system, or an entire country. The ability to see -and master - these drunk cats reveals the true split in startups today. It is no longer between software and hardware, but between "impressionistic" founders who map the world as it is, and "mechanistic" founders who can reverse-engineer reality from first principles. My latest Dave's Quick Hits newsletter provides the playbook for identifying and funding these mechanistic architects. It is about a fundamental shift from describing effects to mastering cause. I break down the three core stages of the Mechanistic Playbook: 1. See the System: Identifying the hidden rules and emergent flaws in any complex system, from software to biology. 2. Debug the System: Using technology to patch the legacy "bugs" of a previous industrial paradigm. 3. Architect a New System: Building with true primitives, like DNA, to program matter itself. The next trillion-dollar companies won't be built by operators chasing surface-level trends. They'll be built by system-thinkers who can see, debug, and architect reality’s source code. You can read the full analysis and the investment theses here: https://lnkd.in/dkhkBUwh #VentureCapital #DeepTech #FrontierTech #Investing #Strategy #Biotechnology #Nanotechnology #vibecap #vibecapital #drunkcats

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4 stages of consumer PMF. Which one are you at? Stage 1: Product-user-fit Users are retained. Monetization validated. Users are demanding more features or content. Stage 2: Product-market-fit Growth channels matching your monetization model. You can now grow profitably. Stage 3: Negative CAC Enough people are using you and talking about you that your CAC goes to near 0. The market pull exceeds what your company can sell! Stage 4: Cultural shift Your product is changing people’s lifestyle and beliefs. People think about your product on their ride to work. They talk about it at dinner. They connect over it. Every consumer founder’s wet dream! Companies often repeat 1,2 in order to expand their user base or to survive in a changing market. I often see startups skip 1. Those businesses are now dead. I've also met businesses who can't crack 2. Also dead. After 3, money comes easy, companies grow into monstrosities full of waste and mediocrity. That's also when they'll be disrupted! The game shall never die 🙌 

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🚀 Scaling isn’t just a product challenge—it’s a people one. So many startups hit traction, raise a round, hire fast… …then crash just as fast due to silent burnout, misaligned culture, or bloated org charts. 🎙️ In my latest episode of The CTO Show With Mehmet Gonullu, I sat down with Nahed Khairallah, founder of Organized Chaos, who has helped 150+ startups scale from 7 to 9 figures by fixing what most founders ignore: their people strategy. We talked about: ✅ Why hiring fast (without context) leads to layoffs ✅ When global headcount expansion makes sense—and when it doesn’t ✅ Culture as a business responsibility, not an HR task ✅ Burnout, founder bottlenecks, and how to avoid “operational debt” ✅ The right way to bring AI into your HR stack This one is a must-listen for founders scaling post-product-market fit—and for anyone who believes HR should be a growth lever, not a cost center. 🎧 Episode 485 — Scaling Starts with People: Nahed Khairallah on Building Teams That Don’t Break 👇 Available on all platforms + YouTube

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It is not only about top-line revenue, but about the quality of revenue. At least in my opinion. Acquisition metrics are meaningless if your product doesn’t keep users coming back. When talking to founders and looking at the key metrics they present in their pitch decks, I don’t just look for top-line revenue growth. In my view, "Product metrics” is where the real story lies. 🔎 Why? Because it tells you if your customers love the product and whether there’s actually room to scale. Here are 4 key metrics I always recommend founders keep a close eye on: 🔁 Personalisation & Stickiness Are users coming back, and are they getting more value over time? Products that learn from users’ usage and personalise (adapt) based on behaviours or use cases tend to drive deeper adoption and loyalty. 📉 Churn User churn and logo churn are early indicators of whether you’ve nailed product-market fit. High churn suggests you’re plugging a leaky bucket, no matter how good your sales engine is. 💸 NRR (Net Retention Rate) NRR growth is a key sign of product love. Are customers using the product more and more over time? If customers love the product and the value they get is irreplaceable, they are willing to pay more for it over time. What other metrics do you track and keep a close eye on? Always curious to see how different teams approach this. Would love to hear from you Michael Tefula, Leah Tharin, Carmen Alfonso Rico 🍫, Camilla Dolan, SC Moatti, Alexandre Lazarow, Andrea Gurnari, Pietro Bezza, Dilek DAYINLARLI, Emmanuel Cassimatis #ProductStrategy #EngagementMetrics #PLG #VentureCapital

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There’s one quantitative metric I particularly love when it comes to measuring the health of a startup’s PMF, and I look at it during every leadership meeting. Sean Ellis gives us a qualitative signal to measure PMF — how disappointed would users be if we shut down? The retention-to-activation ratio gives us the quantitative equivalent. Here's how it works: we take the number of users who keep coming back to the product and divide it by the number of users who activated. This ratio tells us whether the product is actually required in their workflow or just sitting there on auto-renew. Why this matters more than revenue: 1. Revenue can mask problems. For example, people can forget they're paying for products, especially with auto-renewals. We might be making money, but if users aren't coming back, we're vulnerable. When economic conditions tighten, those unused subscriptions are the first to get cut. 2. Retention shows us real usage. If activated users keep coming back, the product is solving something they need. So, what’s a good retention to activation ratio? There's no universal benchmark. The ratio that signals health varies based on market size and pricing. Dropbox has 700 million registered users and 15 million paying — roughly a 2% retention-to-activation ratio. That works because the market is massive and pricing is low. Palantir sells to maybe 100 companies globally at $10M+ per contract. A 2% retention ratio there would be catastrophic. With a small market and high pricing, retention needs to be significantly higher. I see an inverse relationship: as pricing increases, the base of activatable customers shrinks, so we need higher retention to stay viable. As pricing decreases and market size expands, we can work with lower retention rates. This isn't about hitting a magic number. It's about understanding whether the retention we're seeing makes sense given the market we're playing in. The retention-to-activation ratio, calibrated to our specific market, might be the most honest answer to "have we hit PMF?” Product builders, what are your thoughts on the retention to activation ratio?

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Interesting new process I've been trying for product development: 1. Define product vision on my own based on company vision, customer feedback, data 2. Workshop with the team and ChatGPT 3. Vibe code vision 4. Play with the vibe-coded prototype of your future product (it's janky, but it helps you really see what you think you want) 5. Identify problems and opportunities you will encounter in pursuing said vision 6. Refine vision given those learnings, or at the very least, identify tactical problems you will encounter as you pursue the vision and work through solutions before you start actually building This is crazy. Should help us tremendously with product precision, which, if velocity = precision x speed, will make a massive difference.

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Y Combinator Spring 2026 Request for Startups Here’s a clear breakdown of the startup categories getting YC’s attention right now 👇 1️⃣ AI-Native Workflows & Business Models ✔️AI-Native Agencies → Software-like agencies delivering outcomes (legal docs, ads, designs) with AI at high margins. ✔️AI-Native Hedge Funds → Funds run by AI agents analyzing filings, earnings, and executing trades. ✔️“Cursor for PMs” → AI tools that turn customer data into feature ideas, specs, and priorities. 2️⃣ Modernizing Industry & the Physical World ✔️Modern Metal Mills → Software + energy tech to cut lead times and improve margins in steel/aluminum. ✔️AI Guidance for Physical Work → Multimodal AI + smart glasses to coach workers in real time. ✔️Large Spatial Models → AI that understands 3D, geometry, and physics for real-world design. 3️⃣ Government & Civic Infrastructure ✔️AI for Government Ops → Automate forms, applications, and back-office workflows. ✔️Fraud-Hunting Infrastructure → AI tools to surface evidence and accelerate whistleblower cases. 4️⃣ Developer Tools & Financial Primitives ✔️Easier LLM Training → Simple APIs and tooling for data + model training. ✔️ Stablecoin Financial Services → Compliant products bridging DeFi and TradFi. 👉 Explore YC’s full Requests for Startups and see if your idea fits: https://lnkd.in/gYvnhJCr ♻️ Repost for founders who want real Fundraising Intelligence. 📩 Subscribe → https://www.foundevo.com/ 👉 Follow CompareBizTech for hands-on AI tools, workflows, and founder-tested software.

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Most founders claim they optimize for growth. I optimize for suffering. At Kortex, we've implemented "Pain-Driven Development" where each feature is assigned a "misery metric" - a precise calculation of how much anguish it causes our developers. The more our engineers cry during standups, the higher our revenue climbs. Users don't care about happy teams. They care if the app works online, syncs offline, functions collaboratively, responds instantly, helps them get a job, makes them 6 feet tall, the list goes on. In other words, if your team isn't balding in their early twenties, you're cooked. P.S. In case you're wondering, the "misery metric" is actually just a jar of hair. Each strand of hair lost in the office = 1 unit of misery.

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The most important startup metric isn’t revenue. It's whether people use your product. We used to think it was revenue. We chased revenue hard. We scaled fast. We booked millions in just a few months. But then we started to look deeper. A pattern emerged. The customers who signed up without a demo, who clicked an ad and converted instantly, rarely signed in again. It was tempting to dismiss it. Maybe they trusted the "AI agent" to just run. Maybe they didn’t need to log in often. But when we looked at the data in retrospect, the story was clear. Logins were a leading indicator. The users who came back daily, who explored new features, who gave feedback, and who engaged, were the ones who renewed. They were the ones who referred others. They were the ones who stuck. Since then, we’ve made one shift: Make customers love the product. At all costs. It's our primary KPI. When they do, everything compounds: 1/ NDR climbs 2/ True CAC drops as they refer other customers 3/ Upsell and cross-sell become far easier 4/ Reviews get posted and case studies become easy Bad revenue slows you down. Good usage builds real businesses. If you measure one thing this quarter, measure this: How many of your customers actually love using your product? Then do whatever it takes to make that number go up.

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Founders talk a lot about product-market fit, fundraising, and growth. We rarely talk about how to stay sane while doing it. When I founded Stitcher back in 2007, from the outside it looked like a startup success story: raised from Benchmark and NEA, sold in 2014. The truth? It almost broke me. We were a month from running out of cash three times. I was sleeping 4-5 hours a night, taking stimulants to keep going, drinking to come down. Every failure felt personal. I thought the company was me. By the end of year two, I was burned out—physically and mentally. So I decided to change. Over the next six years, I experimented, failed, and slowly learned how to stay sane while building something insanely hard. Since then, as an investor, startup advisor, and now full-time founder coach, I’ve talked with thousands of founders about this same challenge. Here’s what’s helped me (and many of them) the most: Maintain perspective • Create a small CEO group that meets monthly. Talk honestly about your biggest challenges. It uplevels you strategically, tactically and mentally. You can join a group like Hampton or YPO…or create your own. • Meditate: studies show that meditating for as little as 8 minutes a day can rewire your brain to be more calm and focused. • Volunteer: Helping others gives you perspective (and dopamine/serotonin - scientists call the effect “givers glow”). • Read history: Lincoln, Tubman, Shackleton—suddenly your CAC problem feels small. • Gratitude list: Three things, three times a week. It works. Fix the foundation • Sleep: This is the foundation of everything. I literally lost a term sheet once because I was too sleep deprived to do basic math. • Exercise: Move your body every day - even if it’s just for 20 minutes. But if you’re already depleted, don’t go 100%. • Get help if you need it: If you’re numbing with alcohol, pills, or having really dark thoughts - get help! Founders have a higher prevalence of depression and anxiety. There is no shame in professional support. Trust yourself • Founders make dozens of decisions a day under uncertainty. When I started writing them down—pros, cons, feelings—it changed everything. Clarity, confidence, awareness. The truth is, being a founder means failing, recovering, and inspiring others to follow you through constant uncertainty. To do that well—and for long enough to win—you have to take care of yourself first. If you’re a founder, I hope this helps you prioritize your own mental health. You can’t scale your company if you can’t sustain yourself.

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Most startups don’t fail for lack of ideas. They fail because execution takes too long. These 6 SaaS tools can shrink that timeline from months to days—so you can test, iterate, and grow before competitors even react. A few weeks ago, I was helping a founder with some data analysis. So, I introduced him to a set of tools, each solving a specific bottleneck: **One helped him launch landing pages in minutes. **Another gave him goal tracking without the OKR headaches. **One automated his outreach, another delivered competitor insights in seconds. **We even fixed his investor decks and made product videos in a fraction of the time. A week later, he sent me a message: “You should share that list with other founders. I didn’t realise execution could move this fast.” So, here it is: the 6 SaaS tools that streamlined his business and gave him back time to focus on growth. #SaasTools #RathiVakkayil #GrowthStrategy #Innovation #AItools

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One thing that can speed up PMF and get you customers faster, especially early in your journey, is selling to other startups with small teams that fit your ICP. Yes, startups usually have less money but they move fast. Even if they say a no to using your product. At ImageKit, some of our earliest momentum came from working with smaller teams. The feedback loops were tight, decisions were fast, and we could improve the product in days instead of weeks. Compare that with enterprises. An enterprise deal can take a few months, sometimes even more than a year, just to get a “yes” (or a silent no). The product requirements also lean more toward security and governance, which are essential to them but may not help you validate the core problem you are solving. Selling to startups won’t maximize revenue early but it will maximize learning, speed, and signal. And early on, that matters more. Unless you are solving something specifically for enterprises only, then the startups are actually not your ICP.

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