easyfreepdf

My app opens with a fourteen second welcome film. I wanted a calm ambient score under it and did not want to license a stock track for one screen, so the music is a 50 line numpy script. Warm pad chords built from layered sine waves. Small chime accents placed on the same timestamps as the scene captions. A low hum that slowly breathes underneath. It renders the exact same wav every run and it added about 300KB to the mp4.

Then the browser rules arrive. Autoplay is only allowed muted, so the film starts silent and the score sits behind a Sound on button. The realistic case is that most people watch the whole intro and never find out the audio exists.

I still think it was worth it. The unmuted version feels finished in a way the silent one does not. But I have no number for how many people ever tap unmute. Has anyone measured unmute rates on a product intro video, and were they high enough to justify the audio work?

Most people use Product Hunt primarily for launching their product, which is completely understandable and a basic thing. That's what the platform is best known for.

BUT I think Product Hunt offers far more opportunities than just launch day. If you approach it strategically, it can become an ongoing marketing channel rather than a one-day event.

Noticed something a few weeks into a bigger project. Early on, a prompt like "add a delete button" just worked, one sentence, done. Now the same size request needs four sentences of context just to not break something else, which auth flow to respect, which of the two similar-looking components to touch, which past decision not to accidentally undo.

That's not classic technical debt. The code itself might be totally fine. The debt is that every prompt now has to carry more context just to stay correct, and that context requirement grows quietly, prompt by prompt, without ever showing up as a line in the codebase you'd notice.

The trap is it feels like the project getting more complex, which is normal and expected. But it's actually something narrower: the AI's working memory of your decisions is shrinking relative to how many decisions exist, so you're the one who has to keep re-supplying context it should already "know." At some point you're basically writing documentation into every prompt just to get back to where a one-line request used to work.

The only thing that's slowed this down for me: treating repeated context as a signal, not a nuisance. If I'm explaining the same constraint for the third time in different prompts, that's not me being thorough, that's a sign the constraint needs to live somewhere permanent (a note, a comment, a doc the agent can be pointed to) instead of being retyped from memory every time.