Fernando Taranto Cassettari

Hot take for FinTech founders 👇 Your AI isn’t the problem. Your static UX is. AI products don’t break...they drift when UX stops listening to live behavior, risk signals, and decisions in motion. Great FinTech products behave like ecosystems, not feature launches. They observe → learn → adapt → repeat. If your UX isn’t evolving in production, you’re building complexity, not intelligence. 💡Design systems that think, not screens that freeze. #Fintech #AI #UX

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Switching subscription providers shouldn't mean losing your retention history. Cohorts. LTV. Churn patterns. The data you've spent years building. Wellbel had already lived through it once when they migrated to Shopify. So when the time came to move their subscription stack within the Shopify ecosystem, starting from zero wasn't an option. HAM stitched their full subscriber history across the migration. Every cohort, every trend, every signal carried forward. "HAM gave us confidence that our historical data stayed clean and reliable throughout the migration." - Sonja Grasser, MBA Switching providers should be an operational decision. Not a data risk. 🔗 Case study link in the comments

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𝗖𝗮𝗻 𝘆𝗼𝘂𝗿 𝗵𝗼𝘀𝘁𝗶𝗻𝗴 𝘀𝘂𝗽𝗽𝗼𝗿𝘁 𝗿𝗲𝗮𝗹 𝘁𝗿𝗮𝗳𝗳𝗶𝗰? Because launch traffic isn’t the test. 𝗧𝗿𝗮𝗰𝘁𝗶𝗼𝗻 𝗶𝘀. We see this pattern with many founder-led teams. Weeks spent preparing for launch. → Design polished. → Product ready. → Messaging dialed in. ⭐ 𝗧𝗵𝗲𝗻 𝘁𝗿𝗮𝗳𝗳𝗶𝗰 𝗳𝗶𝗻𝗮𝗹𝗹𝘆 𝘀𝗵𝗼𝘄𝘀 𝘂𝗽. And that’s when cracks appear. ✕ Pages slow down. ✕ Requests stack up. ✕ The site feels unstable right when attention peaks. 𝗡𝗼𝘁 𝗯𝗲𝗰𝗮𝘂𝘀𝗲 𝘁𝗵𝗲 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 𝗳𝗮𝗶𝗹𝗲𝗱. Because the infrastructure wasn’t built for momentum. 👉 𝗪𝗵𝗮𝘁 𝗽𝗼𝗼𝗿 𝗵𝗼𝘀𝘁𝗶𝗻𝗴 𝗾𝘂𝗶𝗲𝘁𝗹𝘆 𝗰𝗼𝘀𝘁𝘀: → Response time ↳ Pages hesitate before loading → Reliability ↳ Small spikes cause errors → User trust ↳ Slow sites feel risky → SEO performance ↳ Instability gets noticed → Conversion momentum ↳ Interest fades while waiting ⭐ 𝗧𝗵𝗶𝘀 𝗶𝘀 𝘄𝗵𝗲𝗿𝗲 𝗼𝘂𝘁𝗰𝗼𝗺𝗲𝘀 𝘀𝗽𝗹𝗶𝘁. ✓ 𝗪𝗼𝗿𝗸𝘀 → Hosting built for real load → Speed that holds under pressure ✕ 𝗙𝗮𝗶𝗹𝘀 → Launch-ready setups only → Cheap infrastructure hiding limits Founders plan for day one. 𝗧𝗿𝗮𝗰𝘁𝗶𝗼𝗻 𝗮𝗿𝗿𝗶𝘃𝗲𝘀 𝗼𝗻 𝗱𝗮𝘆 𝘁𝗵𝗶𝗿𝘁𝘆. 👉 𝗧𝗵𝗲 𝘀𝗵𝗶𝗳𝘁 𝘁𝗵𝗮𝘁 𝗰𝗵𝗮𝗻𝗴𝗲𝘀 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴: → Treat hosting as growth infrastructure → Plan for spikes, not averages → Choose stability over savings → Build for traffic you want When this is done right: Traffic stays smooth. Trust holds. Growth doesn’t trip itself. 💾 𝗦𝗮𝘃𝗲 this for later 🔁 𝗥𝗲𝗽𝗼𝘀𝘁 if growth is on your roadmap #Orbillo #DesignPartner #WebDevelopment #Hosting #Performance #StartupGrowth #Founders 𝘗.𝘚. 𝘊𝘰𝘶𝘭𝘥 𝘺𝘰𝘶𝘳 𝘴𝘪𝘵𝘦 𝘩𝘢𝘯𝘥𝘭𝘦 𝘥𝘰𝘶𝘣𝘭𝘦 𝘵𝘳𝘢𝘧𝘧𝘪𝘤 𝘵𝘰𝘮𝘰𝘳𝘳𝘰𝘸?

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I am been following Henrique Cruz since years for his way to do product & growth, on the Rows.com bold move to do NOT have a landing page (before even chagpt launched) and honestly it was amazing having him on stage. What we learned? Most AI startups are doomed. They build something cool. OpenAI copies it. Game over. Henrique told us the uncomfortable truth: if you're not 10x better than ChatGPT, you're building on borrowed time. So what makes you 10x? It's not the model. It's your product discipline. The 5 principles from the talk: 1. Pick problems with instant validation Can users tell in 5 seconds if it worked? Yes → good use case. No → rethink it. 2. Assume AI gets free and perfect They're building for a world where models cost nothing. Your moat can't be the model — it's your product. 3. Price by frequency + token consumption High frequency, many tokens? Can't afford free trials. Low frequency, few tokens? Give it away. Review this monthly. The landscape shifts constantly. 4. Version control your prompts Their prompts go through PRs, testing environments, automated evals. They caught a prompt change that dropped answer rates from 85% to 73% — rolled back on a Saturday. "Prompt engineering IS software engineering." — Henrique 5. Daily metrics, weekly intuition Daily: answer rate, prompt volume, cost per prompt, failed questions Weekly: read actual user prompts, test new models, review architecture His favorite ritual? Reading user conversations every week. You learn what they actually want vs. what they say they want. Some users hit their AI 70 times in one day and never reply to emails. That's better feedback than any survey. The impact of these routines? → 95% answer rate (up from 86%) → 5x their baseline prompt volume → Under $0.08 per prompt → 1 million users in 6 months 80% of improvements came from big architectural changes. 20% from daily kaizen tweaks. But here's the key: daily reviews inform the big decisions. You can't make smart bets without ground-level intelligence. "The AI product that wins isn't the one with the best model. It's the one that gets 1% better every day." I'm stealing this framework for our community. Watch Henrique's full talk: https://lnkd.in/eWq-RHND Complete breakdown here: https://lnkd.in/eEKTQ45e Connect with Henrique Cruz

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