How I’m Building an AI Team Around My Actual Life

My AI warranty bot’s first live test caught a missing serial number blocking a claim.

That’s why I’m building this. Here’s how I’m using @bot and @grok to put an AI team around my day job, business, and research, with names, specific jobs, and accountability.

I work in sales and warranty while building my own business on the side. Add investing research, client work, email, and keeping up with X, and there’s a lot of shit competing for attention.

So I’ve been giving my bots specific jobs and connecting them to the systems I actually use.

They have names. They have responsibilities. They have limits. And they need to bring back evidence when they say something is done.

Here’s how I’m setting it up.

Briggs is my chief of staff for my own business. He’s the main guy I talk to when I need to coordinate work across that side of my life.

Under Briggs, Scout researches potential prospects. Hayes handles outreach drafts and email within the rules I’ve set. Atlas tracks active website and marketing clients, missing information, approvals, and next steps.

Scout finding a business doesn’t automatically mean Hayes should blast them with a generic email. And a prospect doesn’t become an active client just because a bot added their name to a list.

I want the setup to understand those distinctions.

Who needs something from me?

What are we waiting on?

What was actually finished?

What’s the next step?

That’s what I want brought back to me.

Codex still handles production work like websites, graphics, documents, and invoices. Grok Bot handles the coordination around it. I’m using both where they fit, and there are still manual handoffs between them. I’m not pretending every tool is magically connected.

At my day job, the setup gets more specific.

Vance is my main sales contact. He helps with customer context, inventory comparisons, follow ups, and preparing for conversations. Derwin handles the email side.

The follow up workflow checks the dealership system for due reminders, then checks the actual conversation and sent mail before sending anything under the authorization I’ve given it.

If the follow up already happened, don’t send it twice.

If it was only drafted, don’t call it sent.

When it’s completed, log the actual date in the customer record.

Small details, but those are the details that make this useful in a real business.

I just added Wade as a warranty specialist.

His job is to help track missing information, claim status, and what needs attention. In the first live test, he found a pending claim blocked by a missing serial number. We checked the actual record and confirmed it.

That’s the kind of output I care about. Something specific I can act on.

Here’s how I want that team to work together: I ask Vance what’s holding up a warranty case. Vance brings in Wade to check the record. If the answer depends on a manufacturer email, Wade gets the relevant evidence from Derwin. Vance brings me the answer and the next action.

That’s the workflow we’re building and testing. I shouldn’t have to open three chats and explain the same customer three times.

I’m also making sure these bots understand what ISN’T my job.

A service email landing in my inbox doesn’t automatically make me the service scheduler. Unrelated parts and service messages should reach the right team. Parts I personally ordered stay in my tracking workflow.

An order confirmation doesn’t mean a part arrived. A warranty acknowledgment doesn’t mean the claim was paid. The bots need to keep those states separate.

Clear ownership matters.

The next piece I’m testing is one morning summary with my most useful priorities and preparation for confirmed appointments. I’ve also set up an end-of-day workflow where Vance helps turn my actual updates into a clean report for review.

I don’t want ten bots asking me ten versions of the same question.

I want to talk to the main guy and have the specialists work through him.

Same idea with research.

Gage is my trading research contact. Rowan supports him with deeper research, including what people on X are saying and whether the underlying sources support it. I want the reasoning, the counterargument, and the gaps. A confident answer without reliable data does nothing for me.

Debby has a separate role around X research and content ideas. The final voice and what I choose to put out are still mine.

The biggest improvement in the setup so far is how clearly the work is divided. I know who owns each task, where the information comes from, and what still needs my decision.

There’s still setup involved. Logins break. Instructions need tightening. A bot saying “done” doesn’t always mean the work is done. You have to check.

I’m not going to invent some “saved 40 hours a week” number when parts of this were just built.

But I can see the direction.

Less searching through old conversations. Less rebuilding context. Better follow-through. More of my attention available for customers, decisions, and building the business.

That’s what I’m building toward with AI.

And I’m having a hell of a lot of fun figuring it out.