Smarter Systems Beat Smarter Models
The next leap in business automation will come from turning capable models into reliable parts of an operating system.
Developed from a conversation between Pete Winn, Andy David and Jarrad Grigg
A business does not need frontier intelligence at every step. It needs models that are capable enough to write simple software, make bounded decisions and reliably transform data between systems. The greater challenge is implementation. Harnesses, workflows and processes must give each model a defined role and move its output to the next step.
Much of the work inside a business is deterministic. Rules already define how information should be handled, yet people often bridge disconnected software by copying data between screens. Agents can help discover and perform that work, but leaving hundreds of agents to improvise creates the same management problem as adding hundreds of employees. They consume resources, vary their approach and still require supervision.
The durable result is software. Once an agent has worked out a repeatable process, that process can become a script that calls one system, reshapes the output and passes it to another. The model then handles only the decisions that genuinely require intelligence. Competitive advantage will come from encoding operations this way, with models as replaceable components rather than making the entire business depend on one provider.