On Monday morning the weekly reports for my clients are already in my Telegram before I open the laptop. I didn't write them that morning. I set up the assistant that did, and I check every number before a client sees it.
People ask what an AI assistant does for a paid ads specialist beyond writing headlines. Below is my own list, task by task, with the parts I keep for myself.
Client notes
I work in Claude Code, which keeps a folder of notes for each client. When we decide something, the assistant writes it down: which conversion action is primary, which words the client bans from ad copy, which campaign must never receive a certain type of search term, what the client has promised customers on the site. The next session starts from those notes, so I don't re-explain the account, and the assistant doesn't propose an idea we rejected two months ago. For an account I touch twice a week, this saves more time than any writing feature.
Reports, and the search terms that come with them
Each client gets a report in the same layout every week: spend, purchases or leads, cost per result, revenue where the store shares it, and the changes I made. The assistant pulls the numbers straight from the ad platform through its reporting connection, lays them into the template, and sends the file to my Telegram. Two rules came from experience. I take the numbers from the account level. A manual export inherits whatever filter was on in the interface and can drop paused campaigns without saying so. And the Monday report gets a second pass on Wednesday, because purchase conversions in Google Ads keep arriving for days after the click. When the gap is large, the client gets the corrected version.
Alongside the report, a script inside Google Ads runs once a week, reads the search terms report, sorts each query by a set of rules we wrote together, adds the clearly irrelevant ones as negative keywords, and sends me the borderline cases to decide by hand. I still read that list. The script only removes what cannot be confused with a customer.
Drafts and the blog queue
The assistant writes the first version of ad copy, landing page text and blog drafts from my notes and my opinion, then runs it through a checklist of habits that make text sound machine-written. Then I cut, rewrite, and sometimes throw the draft out. I still do the writing, from a draft that already contains my notes.
Finished articles wait in a queue with a date and time. A small program on my laptop checks the queue every hour, publishes whatever is due, confirms the page opens on the live site, and sends me a one-line message: published, and how many are left. If the laptop was off at publish time, the article goes out when I turn it on.
The part I keep
Budgets, targets, pausing a campaign, changing a primary conversion: I make those changes myself, after reading what the assistant suggests. Clients get messages written by me, with numbers I opened myself. The opinions are mine; the assistant has read the documentation, and it has not run an account. Paid image generation waits for my yes as well.
Verification stays with me. The assistant states things with confidence whether they are true or not, so I check every claim about a platform against the platform's own documentation, and every number against its source. A draft once described a service the client does not offer. The paragraph read fine, and I caught it only because I check every claim against the client's site.
If you want to try this on your own account
Pick one task you repeat every week and dislike. For most people that is the report. Write the format down once, which numbers, in which order, what counts as a conversion, and that document becomes the assistant's instruction. Give it access to the data: a connection to the ad account, or at minimum a scheduled export into a spreadsheet. Make it deliver where you already look, Telegram or email. Then read every output for two weeks before you trust it, and keep spot-checking after that.
And keep a notes file per client from day one: decisions, bans, what the client cares about. It costs nothing and it is where I would start.
The next step is a server. Everything above runs on my laptop, so when the laptop sleeps, nothing runs, and a report due at noon waits until I open the lid. The scheduled tasks are moving to a remote machine so that they run on time whether my computer is on or not.
If you want help setting this up for your own accounts, with your rules and your reports, that is a conversation I have in mentorship.
My tip: everything in this area changes so fast that an approach that worked in spring is outdated by autumn. Don't settle on one setup, and keep trying new things. For example, move your regular tasks to a remote server, so they run on schedule without your involvement and don't depend on whether your computer is on.
