Teams | Collaboration | Customer Service | Project Management

Agents need more than access to your tools. They need connected context that shows how work fits together, and where the boundaries are. An account team is preparing a customer renewal, and the customer is asking for a discount beyond standard policy. The contract and the discount policy sit in different systems. A recent support escalation has changed the tone of the conversation, a similar case came up in Slack last quarter, and someone approved a different arrangement for this account.

How to securely scale AI agents from individual to org-wide use without introducing unnecessary complexity.

AI makes it possible to produce work quickly, but it can also result in a lot of workslop—that is, work that looks polished, but does little to move the project forward. Sorting through workslop is time-consuming and undercuts the ROI on AI. It may look like productivity, but it just moves the actual work farther downstream. The Teamwork Lab realized that workslop isn’t an AI problem, or even a people problem.

The Atlassian Marketplace has surpassed $7B in lifetime sales, and while that alone is a milestone worth celebrating, the pace behind it may be even more exciting. The most recent $1 billion was transacted in just nine months, the fastest billion in Marketplace history. Nearly half of all lifetime Marketplace sales happened in the last three years. Those numbers reflect something bigger than just a storefront.

AI is making teams faster, but not organizations. The gap is a missing layer: governed work context that turns a change in strategy into a change in what happens next. AI is making teams faster but that doesn’t necessarily mean it is making organizations faster. That distinction matters. In a recent 451 Research survey, 88% of organizations using AI in workplace tools report productivity gains.

Maya runs IT for Beaconstone Financial, a fintech company with 2,000 employees. Her engineering teams work in Jira and GitHub. Sales lives in Salesforce. Most decisions happen in Slack threads, Google Docs, and SharePoint folders that nobody can find six months later. Leadership wants Rovo to answer questions across all of it. Her head of sales has asked for account briefs that pull in the latest Salesforce opportunity data and last week’s customer call.

Atlassian’s 2026 State of Developer Experience report reveals a disconnect between AI adoption, developer productivity and organisational performance. An engineering leader recently asked me how AI could help their team work more effectively, to keep up with a rapidly growing workload. It turned out the problem was upstream teams creating significantly more output with the help of AI.

In 2025, companies spent a collective $581 billion on AI. The results were underwhelming: according to a study by MIT, 95% of Enterprise AI pilots showed zero impact on organization’s bottom lines. In short, the vast majority of AI pilots are unsuccessful. The reflex is to blame the models. The evidence points somewhere easier to control: context. Every answer AI produces is assembled from a context packet—the material used to respond to the presented prompt.

This is a practical guide for anyone using AI to move an idea towards something real. It gives you five ways to keep the people, context, decisions, and quality connected as the work moves.

The Browser Company of New York, the startup behind the Dia browser and its earlier iteration, Arc, moves at a pace that seems impossible from the outside. It’s easy to assume its team of 65 is fast because it’s small and AI-native, but that’s only a part of it. The bigger factor is their unique way of collaborating that they deliberately designed to keep work from getting stuck.