CQ

CQ2 – the work communication tool for writing-first teams

Hacker News

CQ2 – the work communication tool for writing-first teams

Hi! I'm Anand, founder of CQ2. CQ2 is the work communication tool built for writing-first teams. Discussions using existing written communication tools often turn into a tangle of sub-discussions around quotes, making it hard to follow. There's no clear view of all the comments in a specific sub-discussion and how the sub-discussion is related to its parent, forcing constant scrolling and hopping between comments to gather context for a meaningful response. On top of all that, it's tough to tell if any key points were overlooked. Meetings are hit-or-miss. When it comes to complex and lengthy discussions, they often go nowhere. Instead of thoughtful responses, you often get knee-jerk reactions. Many meetings benefit from taking a break to analyse deeper or reflect further, but there is never enough time. Writing-first culture is the future. That's why I'm building CQ2. CQ2's unique sliding panes design with quote-level threads helps you hyper-focus on one thing at a time. No more tangling of sub-discussions around quotes — create focused threads in organized panes around any specific quote, as well as any specific comment. No more losing context — have a clear view of all the comments and parent threads of a thread, at all times. No more copy-pasting quotes — just select the text and create a new thread at a click of a button. Easily identify parts of the discussion which were overlooked. Organise your communication chaos with posts & chat. And, CQ2 is open source! CQ2 is currently in early access. If our passion for thoughtful and coherent communication resonates with you, we would love to learn about your team, your frustrations with existing communication tools, and better understand how CQ2 can help. Check it out: https://cq2.co .

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Actual performance

2points
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Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, context, using · Missing: mac, agents, macos
72%72% 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.
Hacker NewsStrong engagement from HN community · Strong signals: exist, open source, existing · Missing: https docs, excited, just released
61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
51%51% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
48%48% 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
40%40% 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
17%17% 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.

Incorrect prediction on native model

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