An AI agent can finish its task and still leave a business with a bigger problem. It might send a good customer message without approval or claim a record was updated when it was not. The issue is not always model capability. Teams often design AI workflows around available tools before deciding which actions those…

An AI system can have access to every tool it needs and still fail at the task. The problem is often not the technology. It is how teams assign responsibilities. The Skills vs MCP debate is part of a bigger architectural question involving Skills, MCP, and AI agents. Skills package reusable procedures, MCP connects applications…

Connecting an AI agent to Figma feels like progress. It is also the easiest part. The real test starts when the agent has to work inside a design system without inventing components, hardcoding values, or ignoring rules the team already follows. If you are figuring out how to use Figma MCP, the useful question is…

Teams rarely lose workflows because they are impossible to document. They lose them because the details stay scattered across prompts, checklists, files, and employees’ heads. Agent Skills give teams a way to package that know-how so AI can reuse it. That shift matters as companies move from occasional AI assistance to repeatable agent workflows. The…