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Large Language ModelsAI Coding AssistantsZenn AI/MLPublished: Oct 18, 2026, 10:00 JST

Gemini 2.0 Flash-Lite aces manual text, fails red-box overlays

Gemini 2.0 Flash-Lite aces manual text, fails red-box overlays

3 Key Points

  1. What happened

    Using ClickCapture screenshots of Robocopy Scheduler, Gemini 2.0 Flash-Lite produced a structured parameter table, step-by-step guide and checklist in under 2 minutes.

  2. Why it matters

    The developer concludes AI should handle text extraction and table formatting, while pixel-level red-box overlays and final layout tweaks stay manual.

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Context & Analysis

The test is a concrete example of where multimodal AI helps and where it does not yet. The developer, who builds tools like ClickCapture and Robocopy Scheduler for Windows, wanted to avoid the manual grind of screenshotting, drawing arrows, writing step text and rebuilding parameter tables. But when the same model was asked to place red highlight boxes around UI elements, the boxes landed slightly off target or covered text, forcing a fallback to manual layout. The practical lesson is to split manual work into AI-doable and human-doable tasks, rather than expecting one-click full automation. That boundary may shift as models improve, but for now the developer recommends letting AI do the extracting and the human do the pixel-level polish.

FAQ
How long did the AI take to generate the manual?
The fully structured document foundation appeared in just under 2 minutes after the screenshots were submitted.
What exactly did the AI get right?
It correctly read settings like /MIR and /COPYALL /SECFIX into a table, turned image sequences into step-by-step instructions, and generated a checklist.
Why did the red-box overlays fail?
The developer says multimodal AI can read what is on screen but struggles to calculate pixel-level absolute coordinates for drawing shapes.

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