We gave users 14 days of full access expecting them to explore deeply. Instead, most signed up, used it for 10 minutes on day 1, and never logged back in until the Trial Ending automated email triggered .
When we shortened the window to 7 days (or gated key actions behind reverse trials activation actually went up because urgency forced immediate exploration.
Is the standard 14-day trial dying, or are we just structuring trial onboarding wrong?
when we finally launched our first project, i spent weeks obsessing over backend architecture and minor ui bugs, thinking everyone would notice those technical details instantly.
instead, the very first user feedback we got was about a completely random button placement that took us two seconds to code.
These days, almost every product that launches comes with some form of AI. It's become the default AI for this, AI for that. And honestly, most of them don t really need it. The result? Everything starts to feel the same. The only real selling point becomes we use AI.
That s exactly why I started building @HumanEye because not every problem should be solved by AI. Some things, like resume reviews and career guidance, still deserve the human touch. Real feedback, from real people.
Would love to hear your thoughts:
Are we overusing AI just for the sake of hype?
Have you come across products that felt forced because of their AI features?
What are some areas where human input still matters most?
There s a small difference in how you ask an AI to save something, and it changes what gets saved. Save this for next time. The AI writes a message to the next AI, and it comes out as instructions: Next session: confirm the hotel before booking trains. Do not change the Paris dates. Remind the user about the deposit. Save what we settled. The AI writes down facts: Paris is three nights. Trains between cities; a rental car was dropped because of city parking. The hotel deposit is due May 1. The second note stays true after the conversation ends. A month later, it still says where things stand and why. The first is a set of instructions from a moment that has already passed. A new conversation reads them and follows them, even after the plans have changed. I saw this in my own records. Notes written as instructions carried an earlier stage into new conversations. Notes written as facts read like a record: what was decided, and why. Now when I save, I ask for what settled. Have you noticed how your AI writes the notes it saves? I m curious what others have seen.
You can have the cleanest codebase in the world, but if a developer has to scroll past three paragraphs of fluff just to find the quickstart command, the repo is getting closed. The last few repos I starred all had one thing in common: I could copy-paste the install command and see it running locally in under sixty seconds. Beyond that it's all about trust in the maintainer.
Have you ever un-starred a project because the repo went completely silent after a big launch?
