Shared AI chat experience

Hacker News

Hey HN, I'm Akshay, and I love to experiment with real-time apps. SparkPad is an experimental GenAI chat app. The twist is real-time collaboration: think multiplayer, a shared chatbook. Messages and streaming AI responses are live for everyone in the space. The prompt editor is also shared and synced. I use it to create different spaces with custom prompts suited to a task, workflow, or project, keeping my chats scoped. It can also be shared with a team for a common prompt setup. Tech details: Built with Yjs. Client-side AI API calls are routed through a designated host's API key. The only AI model for now is Gemini (because it's fast)

Visit product View on Hacker NewsMar 26, 2025

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

92%92% 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: gemini · Missing: supports, reddit linkedin, podcasting

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: host, calls · Missing: plus, platform, intuitive

51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

38%38% predicted probability of success on TrustMRR, 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

37%37% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

21%21% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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