In a recent LinkedIn post, Ruben Hassid discusses why he has cut back on his daily AI apps while adding an AI assistant to his team’s Slack. This article covers Hassid’s account of that change and the workflow he describes; it is a report on his post, not an article written by him.
“It’s hard to believe that an AI freak like me uses less AI than ever before.”
Hassid says he now opens four apps each day: Claude and Claude Code, Slack, Wispr Flow for meeting notes and dictation, and Viktor, an AI assistant he added to Slack. He presents the choice as a shift toward fewer tools and more shared work in the team’s existing communication space.
Moving AI work into the team conversation
According to Hassid, his main frustration with Claude was that the exchange stayed between one person and the AI. “I can’t bring/loop my team into the conversation,” he writes. He says Viktor addresses that limitation by letting colleagues join a Slack thread and collaborate with the assistant there.
“Now my team & I talk to each other in Slack, and Viktor collaborates with the entire team, using both Anisha’s Claude and mine (+ connected to all our apps).”
Hassid illustrates the approach with a task involving his newsletter, “Claude for legal.” He says a colleague asked Viktor in Slack to turn prompts from the article into a page built with Claude Code. After Viktor returned a link, Hassid suggested a different direction. In his account, the assistant continued working with both people in the thread, retrieved content from his Substack, and produced a lead magnet.
A workflow shaped by iteration
Hassid describes the exchange as the kind of “proactive collaboration” he wanted from Claude Tag, while saying that tool had too many bugs for his needs. His example emphasizes a practical pattern: assign work in a shared channel, review the result, and correct the assistant in the same thread.
“Correct it in the thread when something’s off.”
That instruction is central to the setup Hassid recommends. He says teams can add Viktor to Slack or Microsoft Teams, connect the tools it needs—including the Claude API in his case—and tag it with tasks written as messages to a team member. The post does not establish how the approach performs across other organizations, but it offers a concrete account of how Hassid is using an AI assistant to make work visible to colleagues.
From individual tool to shared participant
In Hassid’s view, the appeal is not simply access to another AI app. It is placing the assistant inside a collaboration routine where teammates can contribute context and respond to its work. His post frames that change as a way to reduce isolated exchanges and make AI-assisted tasks part of the team’s ongoing conversation.
📝 About This Content
This article is based on insights shared by Ruben Hassid on LinkedIn.
📅 Originally posted on November 3, 2026 | View original post on LinkedIn →