Actually these retention numbers tell that mass consumer base doesn’t have use cases for Muse.

flipkart big billion days sale is on right now and it's bringing back a ton of memories from the first one in 2014. we had done flash sales before. xiaomi, motorola, a few other events. but this was a different BEAST. we did 20x the revenue of a usual day. and we were live for ONLY 10 odd hours. I was in the ads team and something funny happened. there were established brands paying to put banners on flipkart. banner click through rates were usually 1-2%, a tiny slice of our traffic. and they went down. they couldn't survive the load. think about that. 1-2% of flipkart's traffic was enough to bring down large established company websites. the other thing i remember is how close i was to it. as an engineer with 1 year of experience, i got to watch decisions like our CTO prioritising the customer order path over committed ad revenue, while everything was on fire. it was never kept behind a closed door. that's just how flipkart worked, and i didn't know how rare that was until later.

And with that OpenAI’s offerings are completely irrelevant

My agent stack: - @instinct - on-the-go purchases, form fill, local recs - @Muse - mini-apps that require reliable connectors (ex. "track my sleep and movement, send me a survey daily") - @tomo - motivation + goal tracking, also want to try their Interest Groups - @bot - X feed monitoring + alerts - Dots (@OpenAI) - deep, long-running projects...I'm currently making it start a business 👀 - @townai - everything work-related in email, Slack, docs - @Tabdotbot - outbound phone calls / appts