Agentic AI  ·  Building in Public

Nobody needs a morning briefing

Why the first AI agent you build is almost never the one worth keeping, and the question that sorts one from the other.

By Carol Roderick, PhD  ·  September 29, 2026 Agentic AI Building in Public

Most people build their first AI agent as a morning briefing. This is about why that one rarely earns its keep, and the question that tells a business owner whether the next one will.

The first agent I built sent me a morning briefing. Halifax weather, my calendar, three priorities pulled out of Asana, some AI news, anything in my inbox touching work already in motion. It showed up on time every day and did exactly what I'd asked it to do.

I wrote about it in June, mostly because it spent two days making the news up and I didn't catch it.

What I didn't write about is that I stopped reading it. Not slowed down, stopped. It would land every morning and I'd leave it sitting there. Eventually I deleted it. I'd also run a business for years without anyone briefing me about anything.

I felt bad about it for months. Guilty. I'd built the thing myself, it worked, it was sitting there every morning doing its job, and I wasn't holding up my side of the deal. It was screaming look at me and I ignored it. That's how it felt.

I've listened to Successful Idiots since the first episode. It's my fave AI podcast, I recommend it to friends and other business owners, and I often listen to episodes more than once so I can get as much out of it as I can.

Joe Downs is one of the hosts. He runs self-storage companies and on the show he's the one who goes and tries things. Peter Swain is the AI side of it.

In June, Joe told everyone listening that they needed an agent. It wasn't that difficult, it would change their life, and he'd gone and built one. I built mine the same month (we're both in Peter Swain's AI mastermind).

Ten weeks later he's back on, and the message he'd had to type into his own agent was stop running everything except the morning briefing. A few days after that he told it to stop doing that too.

So it wasn't just me, which was reassuring.

How and why did we start with morning briefings? Simply. The main Hermes tutorial sells itself as build a free AI morning briefing bot that emails you daily news, and its getting started walkthrough is a daily briefing on WhatsApp. Everything sitting around it is some flavour of chief of staff. One runs somebody's inbox. One is somebody's day one.

Nobody actually tells you to build a briefing first. It's just the easy one to picture. You can explain it in a sentence and people get it straight away.

Whether it's worth building is a whole other question. The tutorial isn't going to ask it.

The guilt was misplaced. I'd built the wrong thing.

The agent that I'm still using is boring. Yup. Boring. It pulls in data from Meta, CRMs and Google Analytics every day and puts them beside each other. It doesn't tell me what the data means or what to do about it. Yup. I said it was boring.

And yes, I know. That's a dashboard.

Mostly it is. Same sources, same numbers, and a decent dashboard would lay them out better and cost less. It's true.

How it's different: it literally comes to me rather than me having to go and get it. That sounds like the difference and it isn't, because scheduled reports have been doing that for years. I can reply and ask why something moved, which a chart can't. Real, but small.

I could make it smarter. Tell it what to flag, what to ignore, what a bad week looks like. I won't.

So mine stays boring. It fetches. I decide.

The question was never whether it's a dashboard. It's whether it replaced work or just showed me things.

The briefing showed me things. If I want to know the weather, I just look out the window. My calendar was already open. The news I'd have run into anyway.

The boring one saves me an hour of opening tabs and copying numbers into a sheet. Every day.

None of that is really about AI.

So that's the only question I ask before building anything now. What does this take off me?

If the honest answer is that it shows me things, it's a dashboard, and I should go and build a dashboard. They're cheaper, they're better at it, and nobody ever feels guilty about not looking at one.

Frequently asked questions

What exactly does an AI agent do?

An AI agent carries out a defined job from start to finish rather than answering one question at a time. It takes an instruction, works through the steps, uses whatever tools it has been connected to, and returns a result. Carol Roderick's position is that an AI agent is only worth building when that job is work somebody was otherwise doing by hand.

What should my first AI agent be?

Not a morning briefing, which is what most people build first because it is the easiest thing to picture. Carol Roderick recommends starting from the work instead of the demo: name a task that takes real time every week, and build the agent that removes it. If the candidate only displays information rather than replacing effort, a dashboard will do the job better and cost less.

What are the key differences between AI agents and ChatGPT?

ChatGPT answers a prompt and waits for the next one. An AI agent runs a multi-step job on its own, acts through connected tools, and keeps going without a person re-prompting at each stage. The practical difference for a business owner is supervision: a chat tool needs checking per answer, while an AI agent needs a written specification up front.

Is an AI agent just a dashboard with extra steps?

Often, yes. An AI agent that pulls data from several sources and presents it is doing much of what a dashboard does. Carol Roderick's test is not whether it looks like a dashboard but whether it removed work a person was previously doing by hand. An agent that only displays information is a dashboard, and a dashboard will usually do that job better and cost less.

Should an AI agent interpret the data it reports?

Not always, and Carol Roderick deliberately builds hers so it doesn't. An agent asked to summarise or flag takes over the decision about what deserves attention, which is the part of the job an owner should be doing. Collecting the data is the easy part. Deciding what it means is the part worth keeping.

Sources

Successful Idiots, episode 39, “The Difference Between an AI Agent and a Digital Employee,” 23 August 2026. Listen here.

Hermes Agent tutorial documentation.

Voice of Customer research, Carol Roderick, September 2026.


Carol Roderick, PhD is an AI adoption consultant and implementation partner working with expertise-led businesses across North America. She builds AI systems that carry an owner's standards instead of flattening them, and writes about what she learns while doing it. carolroderick.ca