AI agents need more than a human safeguard
Keeping AI agents' actions and the risks they create under control remains difficult, even with a human in the loop, this opinion piece argues.
Keeping AI agents' actions and the risks they create under control remains difficult, even with a human in the loop, this opinion piece argues.
Accurate data is not enough for agentic AI, the author argues. Agents also need coherent, governed and traceable context built on a foundation shared by data and business teams.
Google now requires AI agents that access Workspace to be declared. In small businesses, agents often act under an employee's name, and the article offers three questions to help tell later whether a human or an agent did what.
Business software is opening up to AI assistants, so connecting them is no longer a technical hurdle. The open questions, the author argues, are who connects what, under which account, and where the data ends up.
This opinion piece argues that service accounts, a 1990s-era concept, are a poor fit for AI agents. It gives four reasons to give each agent its own identity and five steps to take with existing identity and access management tools.
Korben gave Claude Code four reverse-engineering exercises, including a keygen, patching a compiled binary and Wolfenstein 3D cheats, first with the REA MCP server and then without it. The test aims to show what the MCP server actually adds.