Oracle 26ai: Enterprise Security Meets Agentic AI
Eric Guyer
2 min read
March 2026
Oracle has dropped a new and exciting set of #EnterpriseDatabase #26ai features. In the past, I would have pulled my hair out, struggling unsuccessfully to create a working demo. Now? I just instructed my Chief of Staff Anthropic #ClaudeCode #AI agent to spawn a team of agents to plan and deliver a full body of tests, then write a pros and cons summary of Oracle's PL/SQL implementation of #AgenticAI.
But I digress. What's the difference in what Oracle has created?
First, understand that agentic AI is best imagined as a wrapper to an #LLM. The wrapper controls access, authority, autonomousness, purpose, inputs/outputs, security, prompting, context, memory, etc. Given an effective LLM, the wrapper is the valuable part.
#Oracle's security model is the difference.
The database controls who can see what data and what they can do with it. Connecting agents with LLMs hosted internally (i.e., foregoing public API calls), protects the customer's IP, e.g., decades of customer and sales data.
The PL/SQL agent itself is probably crap given it's a version 1.0, and its unlikely non-technical people will get anywhere near the "simple no-code canvas" touted in the blog post. Oracle has never released a user-friendly product, but it doesn't need to now.
I'll post my agent's report in the comments when it finishes any minute now 😉