Teams | Collaboration | Customer Service | Project Management

Every AI assistant or automation connected to a messaging platform needs a way to act on your behalf: sending a message, managing a channel, pulling context from a conversation. Rocket.Chat 8.8 gives agents a standard way to do that with a native MCP server, so any MCP-compatible agent can work inside your workspace without your team building and maintaining a custom integration for it. This release also brings tighter security and more reliable calling.

Hybrid teams run into a documentation problem that purely remote teams rarely face: meetings happen in two places at once. Some people are in the conference room. Others are on a screen. The person taking notes is trying to capture what the room is saying while also following what's being said on the call. Something always gets missed.

Every missed business call represents an unanswered question, a frustrated customer, or a potential sale that may go elsewhere. Yet answering every call is difficult, especially for small teams. Employees may be helping customers, working on-site, attending meetings, or simply unavailable outside normal business hours. Technology can solve part of this problem, but businesses are often presented with two different categories of solutions: business phone systems and AI receptionists.

In 2012, your on-premise intranet lived behind a VPN, went dark during patch nights, and groaned under peak loads after all-hands emails. Jump to today: the perimeter is identity, search is instant, and updates land without a maintenance window. This guide is your bridge between those two realities.

OpenAI's new Apple Messages plugin gives ChatGPT access to the Messages application on a Mac. Once enabled, users can ask ChatGPT to find conversations, summarize them, draft replies, and send messages. That has understandably raised questions about what it means for iMessage privacy. The starting point is understanding what the plugin does and, just as importantly, what it doesn't do.

Email is one of the few workplace tools that creates more work simply by being available. Every message asks for a small decision: open it now or later, reply or ignore, archive or keep, delegate or handle personally. None of these decisions seems particularly demanding on its own, but together they can consume a surprising amount of time and attention. The problem is not always the number of messages.

AI makes it quick and easy to turn rough notes into a clean, easy-to-read document. Job well done, right? Think again. Atlassian’s Teamwork Lab suspected that this professional veneer—what we call “AI polish”—makes it harder to spot foundational flaws and give feedback, so we tested it. We wanted to know: Does AI polish make it harder to identify problems in early drafts? How can we solve for this blind spot?

ServiceNow AI is no longer just about Virtual Agent. Today, its AI stack includes Virtual Agent, Now Assist, AI Agents, AI Agent Studio, and Otto—covering everything from conversational self-service to autonomous task execution. For IT and HR leaders, the real question is not whether ServiceNow can use AI.