Teams | Collaboration | Customer Service | Project Management

troop messenger

10 Ways AI Can Improve Team Communication

Aug 11, 2026 By Apoorva Nayak In Troop Messenger
AI workplace communication is transforming how modern teams connect, collaborate, and share information. From drafting messages and summarizing meetings to translating conversations and organizing knowledge, AI workplace communication tools are helping employees communicate faster and work more efficiently. As remote and hybrid workplaces continue to grow, teams often deal with overflowing messages, lengthy meetings, scattered information, and communication across different time zones and languages.
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atlassian

3 AI bets powering Atlassian's integrated marketing impact

Aug 11, 2026 By Esra Guler In Atlassian
The past couple of years have changed how my team operates. We’ve experimented, adjusted quickly, and seen meaningful early results. That momentum got me excited about where marketing is headed in the age of AI, even as we continue learning along the way. Since then, we’ve witnessed what holds companies back from succeeding with AI.
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atlassian

Agents are in Confluence (and wherever you need them to be)

Aug 10, 2026 By Avinoam Zelenko In Atlassian
@mention an agent on any page and it creates, edits, and comments alongside your team. Through the Atlassian Rovo MCP, the same agents work from Claude, Cursor, or your IDE. Agents have been working in Confluence since we launched custom agents in May 2024, and teams now run more than 5 million agent invocations a month. In February alone, Agents saved Atlassian customers more than 200,000 hours.
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atlassian

Why better tickets help agents write better code

Aug 9, 2026 By Anand Shastri In Atlassian
A reflection on building an enterprise product using AI agents, and what the data says about how we worked. The observation For the past few months we have been rapidly building an enterprise-wide, production-grade application that helps with employee compensation planning, management and communication. I compared what we built against a traditionally-built product to draw out insights about our new ways of working.
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miro

From messy discovery notes to a scoped PRD: how Miyagami uses AI Flows to keep context alive across the PDLC

Aug 6, 2026 By Miro In Miro
Alicia Calderon is Design Strategy Lead at Miyagami, a software agency in Amsterdam, where she oversees discovery and design for client projects. In collaboration with their Sales, PM, Design and Delivery teams, she built a Miro template that turns raw discovery sessions into a scoped PRD and product diagram, keeping one source of truth across an AI-heavy product development lifecycle workflow. Here’s how it works, and a template you can clone.
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Nifty: AI Workflow Builder

Aug 6, 2026 By Nifty In Nifty
Describe the work you manage and Nifty builds the project around it: the statuses, the lists, and custom fields already set to the right type. In this video we build a real project from a single sentence, walk through the preview, and change everything before creating it. What's covered Why it is useful Setting up a project usually means renaming columns, adding lists, creating the fields you need, then remembering the one you forgot. This does that part for you, and nothing is committed until you press Create Project. Everything stays editable afterwards.
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nifty

When everyone has an agent, alignment becomes the bottleneck

Aug 5, 2026 By Shiv Kapoor In Nifty
Something changed over the last year that most teams have not fully adjusted to yet. A year ago, one person on the team was often “the one using AI.” Today, almost everyone is. Designers have assistants. Engineers use Claude, Cursor, or both. Product teams run research through ChatGPT or Gemini. Marketing teams use AI to draft campaigns, and support teams use it to summarize issues and prepare responses. Individually, people are producing more than they were a year ago.
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Simpplr

Why healthcare leads industries in AI adoption but still struggles to prove ROI

Aug 4, 2026 By Sylvia Ogweng In Simpplr
Recent Forrester data shows healthcare leads every industry in workplace AI adoption, yet it’s the sector least likely to call that adoption a success. It has moved fast on deployment but still trails on the outcomes leaders care about most: productivity, trust, and measurable ROI.
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