With today s tools, translation (UI, copy, even video) is no longer the hard part.
What slows us down instead are things like tax, legal compliance, hiring, support, payments sometimes even geopolitics. The moment users show up from a new country, a product problem turns into an operating one.
The day before yesterday, I was looking at the profiles of founders and team members of Lovable, as well as other companies, e.g. Hubspot, and they all look pretty good.
Lately, I ve been getting offers to help grow LinkedIn profiles from several founders, and I m starting to feel like at least LinkedIn is hype.
If your launch does not go as planned, do not judge it too quickly. Avoid the instinct to immediately add more features or pivot the product.
Instead, pause and evaluate what already exists. Check whether the core features are clearly communicated, fully polished, and genuinely solve the intended problem. Often, the issue is not the idea, but the execution, positioning, or user experience.
Refine what you have. Improve clarity, usability, onboarding, and messaging. Then relaunch with focus and confidence.
Many products fail not because they were wrong, but because they were unfinished, unclear, or rushed.
I have to admit I m a tragedy when it comes to being first at trying new technology or so which means I ve fallen for more scams and shady situations than I d like to count.
(At least I can warn my friends and family before they make the same mistakes, so that's the only advantage.)
I decided to share some best practices I regret not doing sooner:
Ten years ago, if a Facebook post didn t receive enough reactions, I would delete it immediately.
Yep, 18-year-old Nika was terrified that people would notice her failure. Reality check: when a post flops, almost nobody sees it anyway. The only person who actually suffers from the low engagement is the original poster.
This is a recurring topic here and I recently had many related discussions. So, I wanted to share with you three different stories, three different perspectives and approaches for inspiration.
TL,DR: IMHO There's no perfect day to launch. Just launch it.
We're into the last week of November, which is a little nuts to me. It feels like last week we rang in the 2025 new year celebrations. There's been a ton of new products launch this year, unsurprisingly a lot of them with "AI" in their name. What product or products stood out to you the most?
For me it has to be @Wispr Flow, it's completely changed the game on how I interact with my devices, I rarely find myself typing anymore. Even this post was dictated through Wispr Flow.
We're into the last week of November, which is a little nuts to me. It feels like last week we rang in the 2025 new year celebrations. There's been a ton of new products launch this year, unsurprisingly a lot of them with "AI" in their name. What product or products stood out to you the most?
For me it has to be @Wispr Flow, it's completely changed the game on how I interact with my devices, I rarely find myself typing anymore. Even this post was dictated through Wispr Flow.
Everywhere I look, I see founders and operators investing heavily in their personal brand:
LinkedIn posts every day
X threads
Podcasts, YouTube, newsletters and substacks too
Meanwhile, their CV or portfolio gets updated maybe once a year.
I m wondering if we re heading into a world where your online signal (what you say, who engages with you, what you ship publicly) will matter more than any formal CV or resume.
I see many countries promoting social media to raise the age for using it (e.g., Australia, the UK, etc.).
The sad thing is that some parents are already giving their toddlers a tablet to "entertain" them. This hurts the child's brain development. Not to mention when they get on social media and are exposed to various trends.
Here s something uncomfortable I ve learned building AI agent systems:
AI rarely fails at the step we re watching.
It fails somewhere quieter a retry that hides a timeout, a queue that grows by every hour, a memory leak that only matters at scale, a slow drift that looks like variation until it s too late.
Most teams measure accuracy. Some measure latency.
Here s something uncomfortable I ve learned building AI agent systems:
AI rarely fails at the step we re watching.
It fails somewhere quieter a retry that hides a timeout, a queue that grows by every hour, a memory leak that only matters at scale, a slow drift that looks like variation until it s too late.
Most teams measure accuracy. Some measure latency.
I m Fernando Scharnick a builder and founder of Loopra. Right now, I m building Loopra a workspace that turns meetings, notes, and files into clear next steps automatically.
The idea came from watching teams constantly lose context across tools like Slack and Notion. Everyone s productive individually, but collective memory gets lost.
I m still in the early stages and not launching yet, just wanted to introduce myself and connect with other makers working in AI and productivity.
