Teams | Collaboration | Customer Service | Project Management

What good looks like in healthcare, finance, and BPOs.

Stuck on how to evaluate a workforce analytics platform? These 8 questions show which ones deliver real value—and which your ops team will actually use.

For COOs, CFOs, and Heads of Delivery, the start of the week is often a race to find the truth hidden in a dozen different reports. By connecting Teamwork.com to your LLM (Claude, ChatGPT) via our new Model Context Protocol (MCP) server, you can query your business health in plain English. This isn't just about speed: it's about gaining a level of operational visibility that was previously impossible without a dedicated finance team.

Question. Have you ever sent a message to your team and then immediately thought, “Wait… did I send that in the right place?” You’re not alone. Communication at work is kind of a mess. Not because people are bad at it, but because there’s a lot of it. In fact, Grammarly found that every single worker surveyed, that’s 100% of employees, deals with miscommunication at least once a week. One in four deals with it multiple times a day.

Over the past few decades in the technology industry, some of the biggest constraints to building products have been about having enough engineers, time, or compute. For the first time, that era is ending. Tech teams are experiencing a revolution unlike anything they’ve seen before. The barriers to entry for building have all but disappeared. The constraint no longer comes from producing enough output, but from deciding what to build, and the restraint required to build something good.

Freshworks Chief People Officer Johanna Jackman on bringing HR onto Freshservice to streamline operations, improve employee experience, and unlock higher-impact work.

AI agents are only as good as what they know. Right now, most don’t know enough. Not because the AI is broken, but because the data is. Information is scattered across tools, siloed by department, stripped of the human context that makes it useful. Agents guess. They hallucinate. Teams splinter around different versions of the truth. Context isn’t a file or a ticket. It’s the space in between: why a decision was made, who owns it now, what broke last time.

AI is changing how engineering teams work faster than most organizations can adapt. Coding assistants are now part of the daily workflow, agents are starting to own tasks end-to-end, and the way we deliver software is being redefined in real time. With that shift, engineering leaders are facing a new set of questions. Are these tools actually improving outcomes? Where are they falling short? Which teams are seeing value, and which aren’t?

We’ve all been there – toggling between six tabs, copying content from one tool into another, and wondering if anyone actually read the brief. The promise of AI was supposed to fix this. Instead, most teams got a chatbot bolted onto the side of their screen. We think AI should work the way a great teammate does: show up where the work happens, understand what’s going on, and actually move things forward. Not from a separate window. Not after a five-paragraph prompt.

Teams of all stripes have run billions of cross‑functional, multi‑tool workflows on Atlassian. After decades spent helping them plan, build, ship, and do, those same workflows are now lighting up with millions of agentic automations, up 7x in the last six months alone. All signals point to the rise of the AI‑native organization, where humans operate at critical junctures, deciding what matters and why, and agents do more of the execution.