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Automation Engineering. Artificial Intelligence. Music.
The drainage pump stopped. In the VR room, the trainee finds the drawer, reads the PLC ladder and the relay, warns the electrical team before touching anything and decides whether it can be restarted, away from an energized panel and as many times as needed.
People in the field need to know where a signal is wired: which remote panel, which card, which bit. The app brings the addresses of several plants together, and the control room, far from there, answers in minutes.
Who reviews what the AI wrote? Lenses based on the public work of 28 experts read the project and cite file and line; the code checks every citation, and the final decision is human.
You speak, a model plans, the code fills it in. A 3D character that lives on the desktop and fills a web form field by field, in front of you.
Three coding agents, one request. Orquestra plans, splits the work into tasks, runs the independent ones in parallel, each in its own Git copy, tests, asks an agent from another vendor for a review and integrates one at a time. The person approves the plan and the delivery.
One string of panels stopped, and the inverter did not report it. From its telemetry alone, the study estimates how much the system should generate and finds the loss; Sunny explains the result in plain words.
I am responsible for the software and the field tests of a GNSS/RTK anti-collision system for bulk stockyard machines, as part of a team. The rule is to test before installing: a GNSS signal simulator, a virtual environment that replicates the field computers, and acceptance and failure tests, such as signal loss and reconnection.
Test first, install later. The simulator plays the part of a stockyard machine's antennas and gateway: the positioning software connects to it as in the field, and each write it sends back is checked, word by word, against the model.
Walk into a pelletizing plant with your hands only. The fines yard is ready, with the reclaimer working the pile; the plant comes station by station, in process order, towards voice-guided training.
