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Taskguru.so – Superhuman email, for tasks (for founders and PMs)

Hacker News

Taskguru.so – Superhuman email, for tasks (for founders and PMs)

I built TaskGuru to solve a specific problem I faced as a founder, then as a banker working on many clients: switching between 10+ project tabs and losing track of what actually needs attention, when and why. So I am trying to build Superhuman emails, but for Tasks/ToDos. What TG does: - Immediate Board: Shows today's urgent tasks across all projects in one place - Cross-project visibility: See all your Trello-style boards on one page, able to see all your tasks at the same time - Built-in team chat: Chat happens inside tasks so you never lose track of where you were speaking about tasks (as what happens in Slack) Tech stack: - React + TypeScript + Vite frontend - Supabase backend (PostgreSQL + real-time) - (Building) MCP (Model Context Protocol) integration for AI assistants Key insight: Most project tools only allow you to see one project at a time (missing context or what tasks are truly priority). TaskGuru shows you the forest AND the trees. I'd love feedback on the UX approach and any suggestions for the immediate board concept. What's your experience with project management tools? https://taskguru.so/

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Actual performance

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Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, mcp, slack · Missing: mac, agents, macos
97%97% 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
75%75% 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.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
33%33% 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
16%16% 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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