"As AI coding agents have gotten more capable, they've increasingly been able to handle more of the running code aspect of an application. Not only can they generate code, they can review it, fix it, and maintain it. So it's not hard to see how AI agents can be a self-sustaining loop. As AI coding agents take on more and more of the running code aspect of an application, they increasingly need to create, update, and work with databases. Today's databases, however, were made for people to use, not agents."
"So we built a database system for AI applications called AgentDB designed for agents, not people. AgentDB allows agents to manifest new databases by just referencing a unique ID. Instead of filling out a series of forms - like people do when creating a database. It also provides agents with templates that let them start using databases immediately and consistently across use cases. These templates are dynamic so as agents learn new or better ways to use a database,"
Technology platform shifts change what an application is without immediately replacing existing desktops, web, and mobile forms. An application remains running code paired with a database that stores and manipulates information through input and output controls. AI coding agents increasingly generate, review, fix, and maintain running code, enabling feedback loops where agents sustain and evolve applications. As agents take on more coding responsibilities, they must create, update, and interact with databases. Current databases were designed for human users, not autonomous agents. AgentDB lets agents instantiate databases by referencing unique IDs and offers dynamic templates that provide immediate, consistent usage and propagate learned improvements.
Read at Lukew
Unable to calculate read time
Collection
[
|
...
]