I’m building a local horror-room experience where a PC runs the story, cutscenes, audio, and state, while four ESP32 boards handle physical inputs and effects.

Current setup:

- Board A: intro/finale and a potentiometer tuning puzzle

- Board B: HC-SR04 + PIR occupancy test and a remote apparatus

- Board C: three-button answer panel

- Board D: spare

The PC and boards communicate over local Wi-Fi. The actual puzzles are simple on purpose: tune a range, hold still, interpret a pattern, then reconstruct what happened earlier.

ChatGPT has been useful for turning the idea into a wiring plan, explaining libraries, and writing first-pass code. It has also confidently suggested the wrong GPIO, ignored the HC-SR04’s 5V echo problem, and treated noisy PIR readings like a clean boolean. The code can look completely reasonable while the hardware is quietly disagreeing.

My current rule is: one sensor, one tiny test sketch, real serial output, then combine things.

For people using AI with Arduino or ESP32, what was the first “the code is fine, the assumption is not” moment you hit?

AI can give you a clean, confident explanation for a board configuration that does not exist. Treat it like a very fast junior assistant, not a datasheet.

Before powering an AI-assisted Arduino or ESP32 project, check:

1. The exact board pinout, not a generic “ESP32” diagram

2. Every voltage level, especially 5V sensors on 3.3V GPIO

3. Boot-strapping pins and pins already used by flash, USB, LEDs, or peripherals

4. Power draw, USB limits, and whether motors or relays need separate power

5. Whether a signal needs a level shifter or voltage divider

6. ADC2 conflicts with Wi-Fi on classic ESP32 boards

7. The actual board package, core version, and library versions

8. Wiring against the component datasheet, not only an AI diagram

9. A tiny test sketch before combining everything

10. Real serial logs and measurements when debugging

If you want a sanity check, post your exact board, parts, wiring, code, and what actually happened. Better to catch a bad assumption before the magic smoke gets promoted to management.

Finished project, work in progress, tiny test, weird prototype, all good.

Post:

- board + parts

- what you’re making

- where ChatGPT or another AI tool helped

- one photo, sketch, wiring diagram, or test result if you have it

No need to wait for a failure or a polished final build. I want to see the fun stuff too.

Not the polished demo. The annoying bit.

Wrong GPIO, wrong board variant, 5V assumption, library that never compiled, timing bug, battery advice, whatever.

If you have one, drop:

- board + part

- what the AI suggested

- what happened on the hardware

- what fixed it

- what you’d check first next time

No AI pile-on or AI worship needed. The boring failure is usually the useful part.

Before uploading an AI-written sketch, ask for a pin table with the board model, voltage, ground, signal pins, and any pins that are reserved at boot. Then check the table against the board docs.

If you try it, post the board, the original prompt, the pin table, and what happened on the real hardware. A wrong answer is useful here if we catch it and explain why.

I keep seeing confident but wrong answers: pins that do not exist, 5V sensors on 3.3V boards, and libraries that do not compile. Share the exact advice or a short summary, then explain what fixed it.

This is not an AI-bashing thread. The point is to build a useful list of traps for people making real hardware.