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Agora – An Organized, Social, Decentralized Experience for the Web

Hacker News

Agora – An Organized, Social, Decentralized Experience for the Web

While I do find LLMs useful for some tasks, I have been concerned about how centralized the web will be in a world after this hype cycle. Google learned that the best way to print money is to be the one place that everyone goes to before they go somewhere else on the web. Now these companies want to ingest everything on the web so people don't have to leave their sites; being the few points where all content goes to and comes from (this makes for a terrible spider web). Web development has become more accessible and easier for everyone, but it feels like the number of sites people are going to are only decreasing (social media sites, Google, ChatGPT, a few major publications). Especially after distrust with almost every social platform there is out there today who are all converging towards the same type of platform (short-form videos), I think it is important to create a new text-based space on the web that will allow people to find others' creations that they'd find interesting and have discourse on them. I created Agora as a side passion project with this sentiment in mind. Especially since I have been struggling to find places I could go to learn from what others are discovering on the web (past and present) without getting distracted with addicting videos and random content. I'd appreciate any feedback you may have. HN is a place I go to to find cool things regarding tech/dev but I built Agora to be a space for all types of interesting content. So if you have family/friends who don't have a place like HN on the web, it'd be great to send it to them as well.

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Actual performance

7points
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, new, chatgpt · Missing: mac, agents, macos
84%84% 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 · Strong signals: created · Missing: supports, reddit linkedin, podcasting
81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: platform · Missing: plus, intuitive, reviews
59%59% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
56%56% 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, google, way · Missing: mobile apps, ios, personal
50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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