Hey! I'm Yas, solo founder of Semita an AI travel planner that generates a full day-by-day itinerary in under 60 seconds.

A few things I learned building and launching solo:

• Distribution is harder than building the product took months, getting people to see it is a whole different challenge

• User feedback surprises you I assumed collaboration would be the most popular feature but Hidden Gems mode got way more attention than I expected. Goes to show that what you think users want and what they actually care about can be completely different

• Plan your launch day better than I did it is chaotic trying to make sure everything works while also getting posts out everywhere. I got so caught up checking the product that I missed the time and lost the first few hours of momentum. Lesson learned schedule your posts in advance

• Getting people to respond is hard I personally emailed early signups hoping for feedback and heard nothing back. Apparently that is normal but it is still a humbling reminder that getting people to engage takes way more effort than you expect

Would love to connect with other founders what was your biggest lesson from your own launch?

Genuinely curious: what s your first-mile approach before you book those early interviews?

Do you start with Reddit deep-dives? Reverse-engineer reviews? Talk to personas in your head?

Honestly, it feels like if your product doesn t feature an LLM integration, investors and launch hunters look right through you. But let s be real not every micro-SaaS or developer tool needs a chatbot.

For those who launched or are building a "traditional" software product recently: How are you handling the marketing? Are you feeling pressure to pivot or force-feed AI features into your roadmap just to stay relevant, or are you doubling down on pure, rock-solid utility? Let's discuss.
By the way, I also wanted to ask for your thoughts on websites like this one. It has a lot of interesting offers and various bonuses. Although this isn t related to the topic, I ve found it very useful. I recommend checking it out and sharing your thoughts.

Building community used to be a Web3 thing. Crypto projects lived by their Discord. Token holders became evangelists, most of the times the community was the product, almost as much as the technology itself.

In 2026 AI companies are borrowing the same playbook and taking it offline. The trend I'm watching most closely right now is in-person events as a growth channel. Not conferences. Not sponsored booths. Genuine community gatherings built around the product.

I spent most of last year replacing my own team's manual work. The one that changed everything: a daily pipeline that generates the videos, converts them to GIF with FFmpeg, burns in the logo, watermark and caption, then publishes across 36 client channels. Nobody touches it now. It used to take three people a full morning.

The strange part is that I miss the morning. There was a rhythm to it.

What did you automate, and did you miss any of it?

A two minute check for anyone who lets a script, a CI job or an agent run commands in their repository. List the commands that ask before they do something. Then find out what each one does when nobody is there to answer.

Mine is the schema migration generator. Its job sounds like writing a file: compare the models against the database and produce a migration for the difference. To compare honestly it needs the database up to date, so if any migration has not been applied yet, it asks whether to apply them now. The default is yes.

Nobody reads that as dangerous, because there is a question, and the question is the safety. There is a second safety underneath it: the console framework checks whether it is attached to a terminal, and if it is not, it marks the run non-interactive, and a non-interactive run refuses instead of applying anything.

I read the code this morning to find out why neither of those had ever stopped it. The terminal check only runs if the input object has a stream to test. The ordinary input, the one built from the command line arguments, has none. So the check is skipped, the run is treated as interactive, the question is asked, and reading the answer hits the end of an input that was never connected to anything. The library treats end of input as no answer, and no answer as the default. Yes.

Imagine a $5M check just landed in your account today. How would you spend it?

Here's my rough split:

I've tried both and I'm still not sure which I hate less.

The all in one approach is nice because everything is in one place. Notes, tasks, docs, databases, whatever.

Then eventually the app starts doing so much that I feel like I'm managing the system instead of actually using it.

So I split everything up again, end up with six different apps, and then complain that everything is scattered.

A few years ago, the biggest challenge for building a software product was usually technical skills.

Today, with AI coding tools, someone with limited coding experience can create a functional MVP in days or even hours.

But I m starting to wonder if the bottleneck has simply moved somewhere else.

Building is becoming easier, but:

I started skipping the review section and going right to the comments. Most reviews sound identical after a while, full of generic praise that tells you nothing about how the tool actually performs.

The comments are messier, but people mention real issues like bugs, missing options, and setup friction. That input is far more helpful before testing something new.

Where do you find honest signal on a new launch? Do you read the comments, rely on recommendations, or just test the app yourself?