# I asked DeepSeek to design a band-pass filter. What I learned wasn't about the filter.

> Source: <https://dev.to/rslruiz/i-asked-deepseek-to-design-a-band-pass-filter-what-i-learned-wasnt-about-the-filter-2gn6>
> Published: 2026-09-15 14:35:31+00:00

My prompt: "Design a band-pass filter with lower cutoff at 1 kHz and upper cutoff at 10 kHz. Use a 741 and set the gain to 50."

It gave a clean two-stage design. It also flagged the 741's 1 MHz gain-bandwidth product, which leaves almost no margin at a gain of 50, and recommended better op-amps and an alternative topology.

So DeepSeek gave me a textbook solution—and named the 741's limits itself. What it couldn't know is what I never told it: my supply rails and my maximum input amplitude.

That raised the real question. What solution was I expecting? In a classroom, the textbook answer is appropriate. In the lab, building a prototype, will it meet spec? Probably—maybe.

Better still: why not ask DeepSeek to test it? Sweep the frequency from 0.1 kHz to 100 kHz, vary the input from 0.1 V to 5.0 V, and plot the output.

But can DeepSeek run that test? It can write the Python script. It cannot execute it.

So the boundary is clear. **AI writes the test. I run the test.** There are tools emerging that close this gap—MCP servers that let a model drive ngspice or LTspice directly—but for now, the experimenter is still me.

Which means the next step is mine: run the sweep, and see whether the prototype matches the simulation.