Topic
Insights and notes grouped by this theme.
Why enterprise agents need working memory, semantic memory, procedural memory, and episodic memory
A semantic layer helps AI understand business meaning. But useful enterprise agents need more than meaning. They need memory, procedures, governance, tool access, and a record of what has worked before.
The governance meeting is dying. The governance system is becoming mandatory.
Data governance is not dead. Governance theater is. In the agent era, inconsistent definitions become operational risk because AI scales ambiguity into confident decisions.
AI does not replace data modernization. It makes the missing foundation impossible to ignore.
Modern data stacks were supposed to simplify analytics and accelerate decisions. Instead, many teams inherited complexity by default. AI agents do not fix that foundation. They amplify it.
Agentic AI is powerful because it can act. That is also why it needs real controls.
AI agents are moving from demos into production workflows. Once they call APIs, write records, and trigger business processes, they become part of the control plane.
What ServiceNow's AI agent incidents reveal about enterprise workflow integrity.
Prompt injection becomes materially more dangerous when AI agents can act. Once language is connected to workflows, text becomes a control input.
