Five workflows to hand an AI agent first

The first agent most teams want is the impressive one. The first agent that survives is the boring one: a task done many times a week, with rules someone can write down, where a mistake is cheap and a person can take over. Start there and the agent earns its keep while you learn what the next one should do.

1. Answering and qualifying new enquiries

Reply within a minute on WhatsApp, email or the website, ask your qualifying questions and book a call with the right person. It needs your FAQs and prices, your calendar, and a rule for when to hand over.

2. Order and booking status

"Where is my order?" is the most repeated message in most inboxes. The agent confirms who is asking, looks it up and replies. It needs read-only access to orders or bookings and a check that it is the real customer. Loopwave, a shared WhatsApp inbox we built, pairs AI auto-reply with a team inbox for the conversations that need a person.

3. Documents in, data out

Invoices, receipts, forms and IDs arrive as PDFs and photos and get retyped. An agent reads them, fills the fields and flags anything it is unsure of for a person. It needs examples of each document and the system the data goes into.

4. Content your team retypes

Product descriptions, listings and first drafts written from data you already have, in your voice, reviewed before they go live. KrutAI, an AI product-description tool we built, cut a 30-minute copywriting task to 30 seconds.

5. Follow-ups nobody has time for

Payment reminders, unfinished sign-ups, renewal nudges and post-purchase check-ins, sent inside the hours and rules you set, with every reply logged. It needs the list, the rules, and a stop the moment someone says no.

The test for your own list

• It happens at least daily.
• Someone could write the rules on one page.
• A wrong answer is cheap to fix.
• There is a person to hand over to.
• You can measure it: time to reply, hours saved, errors caught.

Passes all five: a good first agent. Fails the third: add an approval step. Fails the second: it is not ready for an agent yet. It is ready for a conversation about how the work is actually done.