Agent Setup From Slack in Enterprise Environments
Security controls must come before agents launch, not after data exposure happens.
Staff Writer
Mira Okoro covers agentic ai foundations and agent security for LetterMCP.
13 stories
Security controls must come before agents launch, not after data exposure happens.
Security and compliance hang on identity, credentials, and policy—not just features.
Platform engineers must rebuild identity, access.
Governance and audit trails separate production agents from prototypes.
Native compatibility solves tool integration, but authentication and transport gaps remain.
Building an MCP client forces security choices long before deployment matters.
Enterprise teams are adopting open source AI agents faster than they can evaluate them safely.
MCP collapses thousands of custom integrations into one reusable protocol.
Four MCP client types solve different problems; pick your constraint before comparing vendors.
Agentic AI needs memory and planning where generative AI only needs to respond.
Why thousands of exposed MCP servers put your data at risk.
Agents executing tasks in systems employees don't fully understand create new security risks.
Governance gaps in agentic AI deployment create real breach risk before most enterprises are ready.