Stewart Butterfield says Slack is working on threaded messages, hopes to update service with the feature by next quarter
Walt Mossberg / The Verge :
Context & Ripple Effects
In a 2016 interview with Walt Mossberg, Stewart Butterfield committed Slack to threaded messages — a notable reversal for a product whose flat, chronological channel stream was its signature. The promise landed nine months later, when Slack shipped threads on all platforms in January 2017, attaching replies to specific messages in a sidebar flex pane.
The gap between announcement and ship was filled by hard design tradeoffs: Fast Company's account of the notification and inline-versus-broken-out-thread decisions shows why Slack had resisted threading while rivals treated it as table stakes.
First-order effects
- Slack's own users gain a way to hold side conversations without fragmenting channels, changing how notifications and channel noise behave on every platform at once.
- Butterfield converts a long-standing user complaint into a shipped commitment, closing the most-cited feature gap against competing team-chat tools.
Second-order effects
- Thread-first challengers lose their differentiation angle: Todoist's Twist bet its entire product on organizing all conversations into threads, so Slack adopting threading narrows the wedge new entrants can attack.
- Once threads exist, they become infrastructure for everything Slack layers on top — the 2019 rollout of email replies and structured features builds on the message-as-container model threading established.
Third-order effects
- If the pattern holds, team chat consolidates around platforms that treat individual messages as addressable objects — the foundation later monetized through paid structuring features like task lists and agent surfaces rather than raw messaging.
- Threading normalizes asynchronous communication inside real-time tools, pressuring the whole category to balance immediacy against interruption — a tension that keeps resurfacing in Slack's subsequent feature bets.
The trend: Team chat is evolving from a single chronological stream into structured, per-message conversation objects, with each platform layering workflow and AI surfaces on top of that structure.