Teams | Collaboration | Customer Service | Project Management

At Canvas 26 in San Francisco. Ravi Mehta — product strategy advisor, longtime product leader, and teacher of Reforge’s AI strategy and AI prototyping courses — laid out a bold vision for product teams: unlearn the MVP, trade the assembly line for a jazz band, and expect the playbook to reset every six months.

Bring document knowledge you already have access to from Google Drive, SharePoint, and OneDrive into Rovo Search, Chat, and Agents so teams can move from questions to useful context faster. The project plan is in Google Drive. The financial model is in SharePoint. The work is tracked in Jira, and the decisions are documented in Confluence. Your team has the information it needs.

For many organizations, employee newsletters remain one of the most reliable ways to keep employees informed. But too many newsletters have become catch-all containers for every update, announcement, and reminder. When everything is important, nothing feels important.

A developer with the right AI tools can now build in days what used to take a quarter. So a lot of CIOs are asking a fair question: Why buy an enterprise platform when my team can spin something up in a sprint? The answer depends on what you think you’re replacing.

Most teams treat capacity planning as an operations chore, something the resourcing spreadsheet handles on a Monday. That framing is why so much client work loses money without anyone seeing where. Capacity planning is the lever that decides whether the work you win is actually profitable to deliver, and this guide walks through the benefits one by one so you can build the case for it and act on it.

You know how things work. The question is whether your team does—or whether that knowledge walks out the door the moment you do. Our research into 303 professional services firms found that only 21% have documented best practices. The other 79% are running on institutional knowledge. Which means onboarding takes longer, quality depends on who’s staffed on a project, and every departure walks out with know-how nobody wrote down. Most ops leads already know this.

Centralized project feedback is the foundation of effective collaboration for remote teams. Without a single place to collect, review, and track feedback, important decisions get buried across chats, emails, and meetings, leading to confusion and unnecessary rework.

Your business looks healthy. Your numbers say otherwise. Every project is staffed. Every team is working. Timesheets are filled out, standups are happening, and clients are (mostly) happy. And yet, at the end of the quarter, the numbers don’t add up the way they should: If this sounds familiar, the issue isn’t effort. It’s visibility. You can’t fix what you can’t see, and most businesses can’t see where their productivity is actually going.

AI is changing expectations for service. Employees want help that feels seamless. Customers want answers without long waits or repeated explanations. Operations teams want to get ahead of incidents and prevent disruptions rather than just respond. Those expectations rest on a critical dependency: context. AI is only useful when it can see the full picture – from people and knowledge to services, assets, and code – and all connections in between.

Connect any coding agent to your system of record to automate engineering loops AI coding agents have made individual developers faster. But faster individuals working in their local environments do not automatically create faster engineering organizations. The bottlenecks that slow software delivery are usually systemic: work stalls in human queues, triage waits for idle cycles, and routine handoffs depend on manual intervention.