Capture the Path Once, Then Run It Deterministically

The first time an automation is built against an enterprise application, it is exploring. It does not know which menu to open, which tab to click, where the target field is. It reasons from scratch, discovering the path step by step. Takes a while, makes a few wrong turns.

The tenth time it runs the same workflow, it should know the path. Open this menu. Click this tab. Navigate to this field. No exploration needed. Significantly faster, no wrong turns.

What Is a Computer-Use Agent

A computer-use agent is software that operates an application's real interface the way a person would: reading the screen, moving the cursor, clicking buttons, typing into fields. Instead of calling an API, it drives the actual UI. That is what makes it useful against legacy desktop systems that were never built to be integrated with, the enterprise EHRs, dealership platforms, and back-office tools that have no clean API to hook into.

The catch is how most computer-use agents decide what to click. They reason from pixels on every run, re-interpreting the screen each time as if they had never seen it before. Minicor's own automations run at roughly 96 to 99 percent click accuracy, and even at that level, reasoning from scratch every run means every run carries the cost and the risk of exploration. The accuracy of any single click is not the problem. Repeating the exploration forever is.

The Problem With Starting Fresh Every Run

Most computer-use approaches do not work this way. Every run starts fresh, reasoning from pixels each time. There is no durable path, so the run that succeeded yesterday is re-explored from scratch today, at full cost and full risk.

It is like training someone to do a task every day but erasing their memory every night. They will never improve. They will never stop making the same exploratory mistakes.

How Deterministic Code Captures the Path

The concept is simple: if a path through the application has been proven once, the system should run it deterministically forever, not rediscover it.

When an automation is built, debugged, and tested against the live app, the successful trajectory is captured as deterministic code. Every subsequent run follows that compiled path directly. A recovery agent stays out of the way until the interface actually shifts, then repairs the step and updates the path.

The difference on repeated workflows is significant, especially under clinical latency constraints. Reasoning from pixels every run, the hundredth run takes about as long as the first. With a captured path, execution is deterministic from the first production run: no exploration time, no wrong turns, the same result on every call.

The overhead is minimal, with the system designed for high-speed execution.

When This Matters Most

For one-off tasks, it does not matter. For RPA workflows that repeat hundreds of times a day, deterministic code changes the economics of the entire system. Predictable paths and a recovery agent that only wakes on breakage are what let it scale.

Writing the automation is the easy part. Keeping it running as the underlying application shifts is the real work, and that is what a captured deterministic path plus a self-healing recovery agent is built to solve.