LukeW | Rethinking Applications for AI

With every new technology platform, the concept of an application shifts. Consider the difference between compiled apps during the PC era, online applications during the Web, and app stores during mobile. Now with AI it’s happening again.

Before getting into the impact AI is having on applications, it’s worth noting we still have downloadable desktop applications, Web applications, mobile app stores and everything in between. Technology platform shifts don’t wipe out the past and they also don’t happen overnight. So AI-driven changes, while happening fast, are going to be happening for a long time.

The basic components of an application have also stayed consistent for a long time. An application at its highest level is just running code and a database. The database stores the information an application manipulates and the running code allows you to manipulate it through input and output controls (user interface, auth, etc.).

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, that information is passed on to all subsequent agent use.

With these two changes, the concept of an application is already shifting. But what if the idea of needing “running code” is also changing? By fronting an AgentDB database and template system with a remote Model Context Protocol (MCP) server: all you need is a URL plus an AI model to have an app.

All you need is a URL plus an AI model to have an app.

In this video, I demonstrate uploading a CSV file of a credit card statement to AgentDB. The system creates a database and template, encapsulates both with a remote MCP server URL that you can add to any AI application that supports remote MCP like Claude, Cursor, Augment Code, etc. The end result is an instant chat app.

Through natural language instructions, you can read and write data immediately and consistently and ask for any variant of user interface you want. Most credit card websites are painfully limiting but now I can create the specific visualizations, categories, queries, and features I want. No waiting around for the credit card site to implement new code.

You also don’t need a CSV file to make an app. Just tell an AI model connected to AgentDB what you want. It can use AgentDB to create a database, populate it, and then ensure anything you add to it includes the right information. Tracking the date, location, and cost of concert tickets? AgentDB will enforce all that info is there and if you add a new bit of data to track, it can update all your records (see video below).

You can try making your own chat app from a database or CSV file at the demo page on AgentDB to get a feel for it. There’s definitely some rough edges especially when trying to add a remote MCP server to some AI applications (in fact, this whole step should go away) but it’s still pretty compelling.

As I mentioned at the start, we don’t fully know how the AI platform shift will transform applications yet. Clearly, though, there’s big changes coming.