Make the reasoning behind an industrial decision visible.
This private prototype explores an industrial decision-support problem rather than equipment control. It helps an operator connect signals, possible causes, operating goals, constraints, procedures and consequences in a model another person can inspect. The agents organize the reasoning while the operating decision remains with an accountable human.
The problem was larger than a single prompt.
An abnormal condition could have several plausible causes and incomplete evidence.
Operating goals and constraints mattered alongside the raw signals.
A recommendation needed to preserve uncertainty and procedure references.
The next shift needed a record of why an action was considered or rejected.
A useful system had to fit the work and its limits.
- Turn a stated operating goal into a stable, inspectable decision structure.
- Keep evidence, assumptions and confidence visible at the level of each node.
- Compare possible actions and consequences without presenting software as the decision-maker.
- Export a reviewable record that preserves human ownership of the final action.
Each agent has a separate job.
A goal-to-map agent builds a stable decision structure, a scenario agent evaluates operating states and a record agent preserves the rationale. Every node remains inspectable and editable.
Goal-to-map agent
Creates a transparent causal map of signals, causes, goals, constraints, procedures and possible actions.
Evidence agent
Attaches available telemetry and references to the relevant parts of the map while preserving missing or conflicting evidence.
Scenario agent
Tests explicit operating scenarios and compares possible consequences against the stated constraints.
Decision-record agent
Captures the rationale, uncertainty, rejected options and accountable owner without controlling equipment.
One traceable path from input to review.
- 01State the abnormal condition and operating goal
- 02Connect evidence, causes and constraints
- 03Compare possible actions and consequences
- 04Record the recommendation and final decision
Technology chosen around the operating environment.
React 19 and TypeScript in a browser-based decision workspace.
React Flow for inspectable causal nodes, connections and editable decision structure.
Motion and Lucide for focused transitions, state changes and familiar controls.
Local browser storage with JSON export for a portable prototype record.
No equipment connection, command path or autonomous operating action.
Evidence for the next decision, not a promised result.
Time required to bring signals, constraints and procedure references into one review.
Important operating limits identified before a recommendation is finalized.
Plausible actions and consequences reviewed by the operator.
Recommendations that preserve their evidence, uncertainty and accountable owner.
This is a private decision-support prototype, not a validated control system. It has no functional connection to industrial equipment and no operating outcome is claimed.
Start with the work, the constraint and the decision owner.
We can map the process, decide which agents would help and define a first release that is small enough to evaluate.
Discuss the problem