I made Dailygram so you stop social-media doomscrolling

Hacker News

Hi HN, Dailygram (open beta) lets you pick any public Instagram or X profile; once a day or week it fetches new posts, runs them through GPT-4o, and delivers a digest you can scan in under a minute—both as an HTML email and via an auto-updating RSS feed. Early adopters include marketers, journalists, and solo founders who track competitors or industry voices without opening social apps. So far: 111 sign-ups, 1 565 digests sent, 56 % open rate, 8 % click-through. Tech notes: Laravel backend, Apify for scraping, GPT-4o for summarisation, Maizzle + AWS SES for mail, signed-URL webhooks for metrics, CDN-proxied images (no originals stored). I’d love your feedback and I’ll be happy to answer anything technical or product-related.

Visit product View on Hacker NewsJul 21, 2025

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, new, email · Missing: mac, agents, macos

88%88% 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 HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

50%50% 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: apps · Missing: mobile apps, ios, personal

49%49% 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

27%27% 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

23%23% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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