◆ HTML

Validate an email address in JavaScript

This is real work, not a feature someone invented — it comes from real job ads and real questions people asked. Below are four ready AI prompts: get it done, make it easy for the next person to say yes to, work out the right move when you are stuck, and stop it coming back.

4prompts

The same task, four prompts

today's deadline · the next reviewer · the stuck moment · the pattern
AExecute — do the immediate taskAdd a check to the email input field on the signup form so it only accepts valid email…+
Add a check to the email input field on the signup form so it only accepts valid email addresses, before the user can submit.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
BImprove — make it easier to acceptBefore the user submits their email on the contact form, validate it. Don't just check for an…+
Before the user submits their email on the contact form, validate it. Don't just check for an '@' symbol; make sure it looks like a real email address, and give them a helpful hint if it's clearly malformed.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentOur CRM is getting flooded with invalid email addresses from the contact form, despite my…+
Our CRM is getting flooded with invalid email addresses from the contact form, despite my current validation.
Our CRM is getting flooded with invalid email addresses from the contact form, despite my current validation. I'm afraid my regex isn't catching edge cases, or users are finding workarounds. What's the most robust and widely accepted method to validate an email address in JavaScript that minimizes false positives and negatives, without being overly restrictive?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI keep losing time cleaning up bad email data in the database because my client-side validation…+
I'm constantly dealing with bad email data because my client-side validation isn't good enough.
I keep losing time cleaning up bad email data in the database because my client-side validation isn't catching enough errors. It feels like a never-ending game of whack-a-mole with new invalid formats. What habit should I change in how I approach email validation to significantly improve data quality at the source?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?

Questions people actually ask

honest answers, no sign-up

Every task here was seen in the real world. Someone doing the job named it, a real job ad asked for it, or a lot of people asked about it online.

If nothing real showed a task, it is not on the page. That is the whole rule.

They are the same job approached four ways, because what you need depends on where you are.

Get it done today. Make it easy for the next person to say yes to. Work out the right move when you are stuck. Learn the pattern so the job stops coming back.

For most of these jobs it can carry the heavy thinking - draft it, sort it, check it, rehearse it with you.

It cannot sit in your chair, take the blame when a number is wrong, or notice what nobody wrote down. Let it do the first 80%. Keep the last 20% that is truly yours.

No. Copy any prompt and paste it into the AI you already use. No account, no score, no wall in the way.

Any of them. The prompts describe the work rather than naming a product, so they are not tied to one assistant.

That is also why they keep working when you switch.

Change it freely. Every prompt is a starting line, not a rule.

Put in your real numbers, your real names and your real deadline. The more you make it yours, the better the answer comes back.

The tasks come from real job ads, published job data and the questions people ask in public forums.

The steps come from HTML's own documentation, with practitioner sources for the traps the manual does not mention.

Push once. Ask it to sharpen the weakest part and to say what it assumed.

Most wrong answers come from a missing detail rather than a bad prompt - tell it the thing it could not know.