Li

Linen.team – A lightweight, thread-first Slack alternative

Hacker News

Linen.team – A lightweight, thread-first Slack alternative

Hi HN! I'm Kam, the founder and one of the authors of Linen. Today, we are launching Linen.team ( https://linen.team/ ), a lightweight threaded messaging app for your team. Modern workplace messaging apps (like Slack) are based on IRC, which is great for small groups, but as it scales, breaks down quickly: you either get overwhelmed by notifications or you have to turn them all off. Most chat apps have threads tacked on but aren't built from the ground up with this design in mind. We wanted to create a thread-first experience where you can organize and prioritize conversations so that you are not reliant on notifications to make sure you don’t miss anything. In apps like Slack, you have to check activities, channels, threads, and replies just to make sure you aren't missing anything important. We designed every message in Linen to belong to a thread, so it makes it easy to centralize everything in a single location. We let you select which channels you subscribe to from your inbox. This way, your inbox only has the important channels. This makes it easy to keep track of conversations without having to rely on notifications to make sure you don’t miss anything. We also wanted a better way to separate urgent vs. non-urgent communication. In Linen, we have introduced the concept of a !mention that is designed for urgent/time-sensitive messages. A !mention will send a push notification, whereas an @mention will show up in the person’s inbox. This allows us to encourage more async conversations and reduce the need for the number of push notifications. We also designed the mention system closely with the inbox so that even if you aren’t subscribed to channels, mentions will still appear in your inbox. This is great for joining partner teams where you don’t need to view every conversation but do need to respond when you are mentioned. We believe that most messaging apps are secretly to-do lists in disguise; you have to read, respond, or do some task when you receive a thread. We wanted to give you the ability to manage threads individually. We let you mark each thread as done, which hides them from your inbox and is useful to keep track of tasks. You also can set reminders and mute threads with one click/key. With these features, we make it easy to get to a zero inbox state. This combined with the inbox makes it easy for you to keep track of conversations and make sure you don’t miss anything. Linen is designed for power users. We love keyboard shortcuts and want an experience that is keyboard-first. For many, the messaging app is the app that is used the most. We believe that you should be able to use Linen for an entire day without touching the mouse. We’ve added modern features like CMD+K for navigation. We’ve designed Linen to be fast and lightweight. Our gzipped bundle size is 400KB, so it's fast on first load, and we’ve introduced multiple layers of caching to make sure things are fast on subsequent loads. We’ve been working hard on this app for the past 6 months, so there are still gaps in the platform. But we’re also very excited about the direction we can take. Our focus is on what a modern message platform built in 2024 should look like and what lessons we can take from the previous decades of IRC and messaging apps. If our message resonates with you, we would love for you to give us a try at https://www.linen.team/signup?callbackUrl=%2Flinen , where you can join our public community and come say hi!

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124points
64comments
Made the leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: slack, apps, user · Missing: mac, agents, macos
94%94% 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: para · Missing: supports, reddit linkedin, podcasting
93%93% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist
65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: apps, month, users · Missing: mobile apps, ios, personal
51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews
48%48% 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
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, introduce · 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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