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Stop Slack from controlling your brain

Hacker News

Stop Slack from controlling your brain

HN, we talk a lot about how Slack has ruined our productivity (eg. https://news.ycombinator.com/item?id=18320968 , https://news.ycombinator.com/item?id=16301508 , etc.), but nobody has taken steps to fix this. I am building Oliv to take a stand. I am a software engineer turned manager. I am guilty of enthusiastically introducing Slack in my previous organization, only to realize how it killed the pockets of focus time that my engineers need to be productive. Once you introduce Slack in an organization, all communication becomes synchronous, even if only 10% of it needs to be, and Slack’s notifications start controlling everybody’s attention. Oliv is a slackbot that manages your Slack status & Do Not Disturb based on your calendar. Oliv also auto responds and takes messages for you / escalates as needed when you are unavailable for a longer period of time. Here’s how my team and I use Oliv today to create focus and manage expectations around communication: 1. We make it a habit to schedule couple of 2h “focus time” blocks for every day on every engineer’s calendar. During that time, Oliv sets Do Not Disturb, updates the status to “is heads down” and takes messages to show later when the focus time ends. 2. For me, when I am in meetings, Oliv updates my status to “in meetings till 4p”, etc. so that my team knows I won’t be able to respond immediately. 3. During vacations, Oliv sets our status to “On vacation till Dec 31”, etc. and takes messages on our behalf. We get to enjoy our vacations, and instead of having a deluge of notifications to comb through when we come back, we get a list of clear asks from our teammates. Oliv has worked wonders for our productivity, and I hope it can do the same for you and your team. You can enable it for yourself at https://oliv.app . It’s free and you don’t need admin privileges to enable it.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: slack, new · Missing: mac, agents, macos
72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
66%66% 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 · Missing: mobile apps, ios, personal
40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
19%19% 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: introduce · Missing: web3, chat, crypto
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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