7 essays
When agents write records about the real world, the safest fix is to make the bad record impossible to write, not to repair it later. A hotel story and one small diagram.
Agents need a disposable workspace and a durable record. Here's where Databricks Lakebase fits, in plain terms, and what it still leaves to you.
When a whole company books travel through agents, the database gets a new kind of user: many, fast, and often wrong. What that asks of the data layer, and why branching alone isn't enough.
An agent books your flight, then crashes before writing it down. When it restarts, does it book again? What an agent remembers, and why some of it has to survive a crash.
An enterprise agent isn't simply a model with tools. It's a system that pursues delegated goals, takes consequential actions, works within defined authority and keeps a clear line of accountability.
Capable agents can still fail on stale or ambiguous data. What an AI-ready analytical platform needs, and why I favour a lakehouse foundation.
Agents need dependable data, and they create records of their own. Why I think data delivery becomes the constraint once the model can do the job.