Teams | Collaboration | Customer Service | Project Management

How to Use AI in Customer Messaging Workflows

See how AI can use customer context to personalize messages, route users through different paths, and generate structured outputs for downstream workflow steps. In this demo, we show how to add an AI step to a customer messaging workflow, use profile and event data as context, define the expected output, test the response, and use the result to personalize what happens next. What you’ll see.

Inside Reddit's IT playbook: Building for scale and AI-readiness

The learnings are based on our recent webinar, “Inside Reddit’s IT playbook for AI and scale”. Check out this session and other conversations with customers on-demand. When Reddit grew from fewer than 400 people before 2020 to roughly 4,000 globally distributed employees today, it wasn’t just their headcount that changed. The mandate for IT changed with it.

Canvas 26: Teamwork AI-mplified

Join us for Canvas 26 — Miro's global event on collaborative AI for teams and leaders. AI makes everyone a builder. But building the right thing? That takes teams working together. At Canvas 26, learn from the organizations already bringing teams and AI together to solve complex problems — and leave with scalable workflows, actionable strategies, and the insights that actually change how work gets done.

3 ways AI alert grouping is transforming on-call engineering at Atlassian

At Atlassian, on-call engineers live at the intersection of urgency and uncertainty. Floods of noisy alerts sap focus, energy, and productivity — especially when responders must decide what matters, what can wait, and what’s just noise. A single underlying issue can trigger dozens of near‑identical alerts in hours.

How customers are using Confluence Agents to turn knowledge into action

Since we first launched custom agents in May of 2024, we’ve seen teams use Rovo to build agents in Confluence that help them accomplish everything from turning customer feedback into PRDs to maintaining consistency across large sets of data and processes. And agents are getting even more popular, with over 5M invocations of agents every month. They take the foundation of knowledge that lives in Confluence, and act on it, saving customers over 200K hours in February alone.

How Asana scales one idea into a full content engine with AI

Stephanie Bui, content marketing strategy lead at Asana, used to think about her role in straightforward terms: managing content calendars, overseeing assets, and running a team. That framing worked when each idea lived in one or two places, like a gated asset or a blog post. The work started with one strong idea and ended when it shipped. AI changed all of that. A single idea ending at one asset was no longer enough. "AI raised expectations," says Steph.