D5

D5s, an AI coworking space for people and agents

Hacker News

D5s, an AI coworking space for people and agents

Hi HN, I’m Michael. Theodore and I are the co-founders of d5s, the multiplayer AI for cross-human-agent collaboration, and we’re building it together. We’re building d5s with d5s. From day one, we’ve created dedicated workspaces for engineering, go-to-market, finance, and other parts of the company. Each workspace has a few coworkers helping with the day-to-day, with access only to what they need. They work with us through Slack and Gmail. As a startup, we’ve found this incredibly useful. Our coworkers take care of repeatable work across marketing, invoice processing, and other operational areas. We believe this is how every company will work in the near future: people set direction and make decisions in shared workspaces, while agentic coworkers move the work forward. We’re opening early access now. The first teams to sign up will get a free early-access plan with credits included, so they can start using d5s immediately. We’ll be here to answer technical questions and share what has and hasn’t worked for us.

Visit product View on Hacker NewsAug 31, 2026

Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, agentic · Missing: mac, macos, cursor

82%82% 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: created · Missing: supports, reddit linkedin, podcasting

75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

51%51% 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

29%29% 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

20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

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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