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The recent project involved developing a Data Acquisition Card (DAQ) into a virtual oscilloscope, designed for plug-and-play use with 12 configurable channels and an initial 100k sampling rate. The technical stack included embedded C for the hardware, Python-Flask for the backend, and a frontend generated by ChatGPT. ChatGPT excelled in creating a smooth, non-lagging frontend but struggled with embedded C and backend processes, particularly in handling hardware limitations and asynchronous issues. The project successfully demonstrated that data rates up to 200kB/s can be processed smoothly in a browser, validating the DAQ system's feasibility. However, issues remain, such as USB communication losses, backend process management, and frontend code readability.