Building an AI agent is only the beginning. The harder work is knowing whether it performs reliably, whether its architecture will hold up at scale, and who keeps it running once it's live. Microsoft's Copilot Acceleration Team (CAT) brings together practical resources aimed at these challenges.
CAT is part of Microsoft's Copilot engineering organization. Its mission is to accelerate the adoption and success of Microsoft 365 Copilot and Copilot Studio, drawing on real-world customer experience. CAT is a resource hub, not a new Microsoft product.
Microsoft Copilot Acceleration Team (CAT) — Enterprise AI and Agent Adoption Resources.
Start with evaluation
The Copilot Agent Kit helps teams develop and test custom agents, validate AI-generated responses, optimize prompts, and track key performance indicators.
Its GitHub repository also documents capabilities such as Agent Inventory, Compliance Hub, Agent Review Tool, and performance analysis, extending its usefulness into agent governance and operational oversight.
For organizations preparing to deploy agents, evaluation should be considered early, alongside requirements, architecture, and security.
Design for operation, not just launch
CAT's guidance addresses the questions that come after a successful demonstration.
The Architect Agent Solutions guidance covers fit for purpose, operability, trust, search and tool use, and multi-agent architecture patterns.
The broader Agent Resources collection brings together resources for building, deploying, managing, and adopting agents across Microsoft's AI platforms.
For enterprise teams, these resources provide useful starting points for defining architecture standards, operational responsibilities, and governance practices before scaling deployments.
Learn by building
For hands-on learning, Microsoft's Copilot Studio Samples provide examples and reusable components that developers can explore and adapt.
The Skills for Copilot Studio GitHub repository provides tools for authoring, testing, and troubleshooting Copilot Studio agents through YAML files using compatible AI coding tools.
This repository is an experimental project rather than a formally supported Microsoft product, so generated configurations should be reviewed and validated before deployment.
CAT also offers learning opportunities, including Agent In A Day, monthly Agent Build-A-Thons, AI webinars, and a three-day Architecture Bootcamp for architects.
These programs help teams move from understanding agent concepts to building and evaluating practical solutions.
Keep up with the thinking
The Custom Engine blog shares insights, architecture patterns, and implementation practices from the CAT team on building custom engine agents and extending Microsoft Copilot.
It's a useful resource for following how Microsoft's practical guidance continues to evolve.
An enterprise leadership perspective
CAT's emphasis on evaluation, architecture, and operability connects with a broader question I've explored in The Enterprise of 2035: as AI agents become part of everyday enterprise operations, who remains accountable for their decisions, permissions, performance, and outcomes?
Technical capabilities alone cannot answer that question. Organizations need clear ownership, governance, operational accountability, and measurable outcomes throughout the agent lifecycle.
Resources such as CAT can help translate these principles into practical implementation approaches.
Where to start
If your organization is beginning its agent journey, explore the architecture and adoption resources alongside the evaluation tools. Use the samples and learning programs to develop practical experience.
For organizations already deploying agents, the testing, governance, performance-monitoring, and operational guidance may be particularly valuable.
Building agents is only the beginning. Evaluation, secure architecture, operational governance, and measurable business outcomes are what make enterprise AI adoption sustainable.
CAT provides a useful collection of resources to support that journey.
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