Concurrency, But Make It Fashion: Why Trustworthy AI Needs an Agentic Lakehouse
Every enterprise AI conversation eventually reaches the same awkward sentence: “Yes, the agent can write code, but absolutely do not let it touch production.” This is not because executives have suddenly become philosophers of machine autonomy. It is because production data is where optimism goes to be audited. A clever agent that drafts SQL, patches a pipeline, or debugs a transformation is useful right up to the moment it drops a table, joins incompatible versions of data, installs a charmingly malicious package, or writes hallucinated output into a dataset used by finance, compliance, or customer operations. At that point, it is no longer “agentic productivity”. It is an incident report with better syntax. ...