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Eraser vs Production Reality: What AI Diagram Tools Get Wrong!

The first time I tried an “AI diagram generator,” I dropped a prompt about our system and got a neat set of boxes and arrows. Looked fine at first. Then I showed it to the team and the questions started: where does auth happen, how does traffic reach the DB, what fails first, what scales, what runs in the VPC? None of that was in the diagram because the tool didn’t understand production reality, it just arranged shapes.

That’s the pattern with most prompt-based generators like DiagramGPT and others. They give you a clean sketch, but skip the things that make real systems real: networks, infra, data paths, queues, auth, redundancy, scaling, and blast radius. Good for slides, bad for truth.

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Dashin solves the part that actually hurts. You describe your system in plain language and the AI generates a production-ready diagram: services, databases, queues, cloud components, and correct connections. You can edit layout, export, or share instantly with a link or embed, so docs and proposals don’t drift from how your system actually behaves under load or failure.

If you’ve ever used an AI diagram tool, looked at the output, and thought “this isn’t how the system works in production,” that’s exactly why we built Dashin.

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