Pick a depth. Each prompt opens in your AI pre-loaded with the lesson. Click a row to preview the prompt.
Every automation works in the demo; the paid work is making it survive real data. Real users leave fields blank, paste emoji into name boxes, type emails with plus signs, and submit twice — and any of these can turn your clean flow into a half-written row or a failed run. The professional response is not anxiety, it is a routine: open the run history, find the failed run, read the exact data that went in and what each step did with it, fix the cause, replay. This debugging-by-log loop is the single most valuable habit in this module because it is what separates people who build automations from people who can be trusted to keep them running — which, not coincidentally, is what retainer clients pay monthly for.
Feed your flow three deliberately awkward submissions and read the results like a mechanic. Submission one: name 'José Núñez', email 'jose+test@gmail.com', message left as just a hyphen. Submission two: full name field containing only 'Cher' (one word). Submission three: a message containing an emoji and a line break in the middle. Then open the log — in Zapier it is called Zap History, listing every run with a status; click a run to see each step's data in and data out. In Make, open the scenario's execution history and click the little bubbles above each module to inspect the exact packet each one received and produced. Reading a failed or ugly run this way usually takes under a minute: you are looking for the first step whose output is not what you assumed.
Here is a realistic diagnosis from that test batch. 'Cher' breaks your name split: there is no second segment, so Last Name maps to nothing — depending on the tool, that is an empty cell or a halted run complaining about a missing value. The fix is a decision, not just a setting: either make the form's name field require two words (fixing it at the source), or accept one-word names and let Last Name be blank, or add a fallback so the blank becomes '-'. Any of the three is defensible; a professional picks one deliberately and writes it down. José's accents and the emoji, meanwhile, usually pass through fine into Sheets and Slack — verifying that non-English characters survive intact is itself a test worth running, because plenty of client data is not ASCII. Fix your one real failure, replay or resubmit, and confirm the run history now shows a clean pass for the same awkward input.