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Just saw this post on X about a team that vibe-coded their entire CRM to avoid HubSpot or Salesforce. A year later, they’re ripping it out and migrating anyway. And honestly… this is happening more and more. I’m all for teams building things internally when there’s a real strategic edge. But software isn’t a “set it and forget it” project. It requires maintenance forever. It grows, it breaks, it takes work to keep it usable. If there isn’t a strategic reason to own that code long-term, it usually becomes a burden rather than an asset. And if teams are going to rely on “vibe code,” there has to be a plan for how it’ll be maintained when the stakes get higher. Otherwise the shortcuts catch up quickly. The app layer is fine. But the foundation matters. This is why we invest so much into maintainability, clear architecture, and long-term ownership for the founders we work with. You can move fast without creating something your future self will hate. Happy to see this conversation happening more openly. It’s overdue.

Churn and retention aren’t mirror metrics. They tell different stories, and they decide your growth trajectory. A few hard-won takeaways we see with SaaS teams: ► Treat churn like a leak you can locate. Cohorts and path analysis reveal where users drop and why. ► Onboarding is the first retention feature. Get users to the “aha” fast, then reinforce it. ► Measure what compounds: GRR/NRR over time, not just this month’s logo count. If you want a clear breakdown of formulas, benchmarks, and practical tactics, this guide is worth a read. https://lnkd.in/ek3At5S6

Teams are shipping faster than ever, but the real differentiator in 2025 isn’t speed; it’s how early and how often you test. The days of “we’ll QA it at the end” are gone. Products are more complex, users are demanding flawless experiences, and regressions show up in places you’d never expect. What stood out most in this write-up is simple but true: QA isn’t a phase anymore, it’s a culture. You need alignment between product, engineering, and QA from day one, or cracks start showing up in production. If you’re planning your roadmap, scaling your platform, or trying to minimize the number of “surprise” bugs before launch, this is worth reading. It breaks down what QA teams should focus on this year: continuous testing, smarter automation, accessibility, performance, and everything in between. 👉 Here’s the full article: https://lnkd.in/esxPa-Js

AI is reshaping how software is built, from copilots that write snippets in seconds to autonomous agents capable of testing and deploying code 24/7. But here’s the catch: the faster AI generates code, the faster your systems need to validate, test, and deploy it. Without a strong CI/CD foundation, AI doesn’t accelerate development; it overwhelms it. This article from The New Stack makes a great point: most companies chasing AI gains are still missing the basics. A third of DevOps teams use AI today, but very few have optimized pipelines that can actually handle the increased throughput. AI brings more code, more changes, and more potential for breakage. What separates the teams who scale from those who stall isn’t the AI model; it’s the foundation beneath it. In other words, before you build with AI, make sure your CI/CD can keep up with it. Read more here: https://lnkd.in/edrP8Xbc

Non-technical founders often underestimate how many hands it takes to get a feature from “done” in code to “ready” for launch. This illustration breaks it down: Each sprint moves through multiple checkpoints: Developer → QA → Dev/QA → QA/Product Owner → Product Owner, each with its own responsibilities, validation steps, and approval gates. Why does this matter for founders? Because skipping or blending these roles is where things fall apart. • Without a dedicated developer, bugs linger. • Without a QA specialist, edge cases slip through. • Without a Product Owner, priorities drift and timelines stretch. A dedicated product team isn’t just about having “more people.” It’s about clear accountability and a process where every role protects quality and velocity in its own way. That’s how great software goes from “it works” to “it works beautifully.”

AI tools have changed the game for non-technical founders. You can spin up a prototype in days, something that used to take months. But here’s the catch: a Proof of Concept isn’t an MVP. AI and no-code tools are amazing for validating an idea, testing flows, or showing investors what could be. They’re not meant to handle real users, real data, or real risk. We’ve seen how easily that line gets blurred and how costly it can be when it does. The difference between a sketch and a foundation is everything. In the latest edition of my newsletter, I unpack why AI is fantastic for PoCs but dangerous for MVPs, and how founders can use both stages strategically without falling into the “AI can build my app” trap. Read it here https://lnkd.in/eNT8jQkv