I am reading "The Hard Thing About Hard Things" book and, this line: "There are no shortcuts to knowledge, especially knowledge gained from personal experience." It's literally been my 2025. I thought I could learn to build by watching tutorials and reading docs. Nope. The

Wrapping this up with 3 takeaways 👇 🚀 Fast launch = starting line, not the win 🔑 No “aha” moment = misleading growth 📉 User behavior > user feedback Speed gets attention. Clarity and retention build momentum. #buildinpublic #saas #startups #product #founders

Learning 5: What happens after launch matters more than how fast you launch Products that slow down after launch to fix onboarding and clarity often see retention improve first. Even a 5–10% retention lift compounds more than shipping features faster. Fast launch starts the

Learning 4: Behavior tells the truth faster than feedback Users often say nice things. Their actions tell a different story. Session data usually shows people bouncing on the same screens. That’s a sign of friction or confusion, not a lack of interest. Exits are more honest

Learning 3: Features don’t fix unclear positioning Adding more features rarely improves retention. Data shows that only about 10–20% of features get most of the actual usage. If the core message isn’t clear, more options just create more confusion.

Learning 2: Activation beats sign-ups every time Sign-ups can look great while the product quietly struggles. In most SaaS products, only around 20–30% of users reach the first meaningful action. If people don’t get to the “aha” moment, growth numbers are misleading.

Learning 1: Speed to launch ≠ speed to value Many products ship in weeks, but users leave in under a minute. Across SaaS, about 55–65% of users drop if they don’t see value in the first 30–60 seconds. Launching fast only helps if people instantly get why it matters.

We launched fast. Users moved away faster. This thread breaks down what actually goes wrong after a “fast launch”, based on real user behavior and numbers 👇

What BORING tech thing did more for your product than weeks of coding? 😅 For me: Timeouts, Caching, Defaults, Rate limits

Weeks of roadmap debates. Hours of design reviews. Countless Slack messages. User opens the app: “Where do I click?” Case closed. 😭

Reading The Hard Thing About Hard Things and this line stayed in my head: “Sometimes, however, the things you’re not doing are the things you should actually be focused on.” It made me think about how progress isn’t always about adding more work. Sometimes it’s about choosing

Today I lost 2 hours “debugging” before realizing nothing was broken. My schema was. Code was fine. UX was fine. Data shape wasn’t. Reminder: your data model is your real product architecture. You don’t refactor it, it refactors you 😁

Quick builder note 👇 If growth feels stuck, look here: 🔁 Distribution loops ⚡ Activation metrics 🎯 Jobs-to-be-Done 📊 Retention cohorts 🧠 Product positioning Shipping more features usually isn’t the answer.

My main conclusion from this: Different wording, same signal: Every model converged on one idea → stop guessing. Whether they called it users, revenue, TTV, retention, or validation, the core theme was the same: get REAL signals from REAL users, FAST. 90 days of that beats

8 - Qwen Qwen focuses on retention. If users don’t stay, nothing else really matters.

7 - Meta AI Meta AI lands on customer validation. Make sure the problem is real before optimizing anything else.

6 - DeepSeek DeepSeek emphasizes tight feedback loops. Talk, measure, iterate fast or risk building the wrong thing.

5 - Perplexity This one defines the metric as “customers who repeatedly get real value.” Basically a practical north star for product decisions.

4 - Grok Very blunt take: getting paying customers. Revenue as validation, runway, and survival.

3 - Gemini Gemini zooms in on Time-to-Value. Shorten the path to the “aha” moment and retention follows.

2 - Claude Claude frames it as customer acquisition. Very business-first: no customers, no revenue, no company.