To pick trending music, I watch TikTok's "For You" page and use the Sounds page to see which songs are gaining momentum. I also look at curated playlists on Spotify and follow trend reports on social media marketing sites. I choose songs that match the mood and energy of the content and test how the beat syncs with the choreography so the final clip feels natural and engaging.

I take a structured approach when debugging complex AI applications. I start by reproducing the issue and examining logs or error messages to identify where things go wrong. I verify that the data being fed into the model is correct, then isolate components (preprocessing, model inference, post-processing) to narrow down the source. I use tools like debugging statements and visualization of intermediate outputs to understand behavior, and iteratively test fixes until the issue is resolved.

I would promote Pippit AI by creating short, engaging tutorial videos demonstrating how easy it is to use the platform to plan and produce content. I would also produce UGC-style pieces showing before-and-after examples of content creation with and without Pippit AI to highlight the time savings and quality improvements. This content would be shared across TikTok, Instagram Reels, and YouTube Shorts to reach audiences where they consume video. Additionally, I would create carousel posts and infographics that explain key features and benefits, paired with clear calls-to-action directing viewers to try Pippit.