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Lookback – capture the stories behind your photos

Hacker News

Lookback – capture the stories behind your photos

Like many others, I rely on photos to document my memories. Over time, I’ve come to realize that they’re not very good at it. Memories need stories, and photos can’t tell stories. Lookback is my take on what I think a better solution looks like. It’s basically a photo sharing app that lets you attach video messages (stories) to photos and share them privately. When your invites watch your memory, they'll hear your story play while scrolling through your photos, just like they would if you were looking at the photos together in-person. They can reply by adding their own photos and video messages, creating a shared memory of stories and photos that you can tap into and relive anytime you want. Now instead of looking at old photos and wishing I remembered more, I can look at old photos and hear my friends and family relive every detail. Looking forward to feedback from the HN community.

Visit product View on Hacker NewsMay 17, 2022

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

45%45% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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