Why Data is More Valuable than Code

In “Data Rules Everything Around Me,” Matt Slotnick wrote about the difference between SaaS & AI apps. A typical SaaS app has a workflow layer, a middleware/connectivity layer, & a data layer/database. So does an AI app.

AI makes writing frontends trivial, so in the three-layer cake of workflow software the data matters much more.

The big differences between an AI & the SaaS app lie within the ganache of the middle layer. In SaaS applications, coded business rules determine each step a lead follows from creation to close.

In AI apps, a non-deterministic AI model decides the steps using context : relevant information about the lead that the AI is querying from other sources.

The better the data, the better the workflow.

The context is the most valuable component because it ultimately changes the workflow. Models are relatively similar in performance.

For example, an inbound email comes into a customer support desk, “Was I double charged this month?” An agentic workflow would query the billing system, the contract system, & the email drafting tool to draft an email to the customer with distinct language for that persona. This only works if the enterprises’ data is well structured.

Enterprises will be shy about sharing the context with their vendors because of how much value it provides. They may start to structure it & assign a department to manage it because the better its availability, the more effective the agentic systems will be.

Data architecture may become a competitive advantage & the future battleground for software companies will be the access to that context - & the fight has already begun.