Robert Echevarria
Founder & Chief Architect, Buildwise Media · Atlanta
Building in the age of AI.
The proposed session
Running AI in a Real Business
What's actually working, what's hype, and where the window closes.
A live, audience-driven Q&A. Your members submit the questions, Cathryn Marshall hosts, and Robert answers — no slides, no script, no net.
For the committee — what you're looking at
This isn't a vendor pitch or a slide deck. It's a working operator who has run AI inside real businesses for two years, proposing to answer your members' hardest AI questions live. Cathryn Marshall — who has known Robert for years — recommended him for this series. Below: who he is, exactly how the session works, and what every member walks away with.
Who he is
Twenty years turning marketing into revenue.
In 2020 — when enterprise marketing and IT budgets were frozen overnight — Robert led the demand strategy at Perficient — a global digital consultancy — that generated $800 million in new business across more than a dozen industries, in the worst budget year in a generation. The method wasn't a bigger budget. It was finding the problem underneath the freeze — the thing a company couldn't afford not to fix.
It started at Dell in his twenties, helping customers solve the technical headaches of their brand-new laptops — back when a built-in DVD player was all the rage. Hands on the technology and face to face with what people actually needed: the same instinct he runs on now.
He studied politics, religion, and ethics at Harvard — the three things you're not supposed to bring up at dinner. That's not a footnote. The same frameworks for reasoning about competing values under genuine uncertainty are exactly what you need at the edge of a technology where the rules haven't been written. Every AI system makes choices about what gets prioritized, amplified, and suppressed. The leaders who don't think about that are building liability they can't see yet.
Four moves, one through-line: understand how revenue actually gets made — then engineer it.
Not theory — live
He doesn't talk about AI. He runs it.
Most conversations at this level are still at "should we use this?" Robert has been past that for two years. His marketing system reads and writes to a proprietary knowledge base in real time, makes attribution decisions on its own, and updates itself — live, with paying clients, today. He isn't building toward it. Clients pay for the output.
No one touches it for this to happen. That's the difference between running AI and talking about it.
We're in the top fraction of practitioners running AI in real production environments — not the researchers building the models, but the operators running them under commercial pressure every day.
— Robert, on the call with Dale. Grounded in two years of live client results, not a deck.
The format
A speech is about the speaker. This is about the room.
A keynote gives members the talk the speaker wanted to give. A curated live Q&A gives them answers to what they're actually wondering about — and it can't be phoned in. It's the harder, more generous, more memorable choice. With Cathryn Marshall curating and hosting, the format is deliberate, not informal.
- 01Members submit questions in advance — the real ones they'd never ask a vendor.
- 02Cathryn Marshall curates the sharpest and hosts the conversation.
- 03Robert answers live — direct, concrete, nothing off the table.
- 04The room sets the agenda, and everyone leaves with answers, not a pitch.
A gift to the room
Don't just hear about AI — watch it work.
If the committee wants a showpiece: Robert will run a real-time AI teardown of one recognizable Atlanta business — volunteered in advance — using only public data. In his words: "I'll spend twenty minutes doing publicly what we charge $15,000 for privately." Nothing makes the value land like watching it happen to someone in the room.
And every attendee leaves with a one-page AI-Readiness Map for their own business — eight dimensions, scored, no email required. A give before any ask.
A preview of the conversation
Four questions, answered.
Members will submit their own. Here is the kind of answer they'll get — unfiltered. The four below span the full range, from honest skepticism to the question about ethics most AI speakers never get to.
Every few years there's a technology wave — internet, mobile, cloud. We were told each one changed everything. How is this different?
Some of the hype is exactly that — most vendors are repackaging old software with a chat box. What's actually different: the internet gave you a channel, mobile gave you a device. AI gives you the ability to do skilled knowledge work at volume, without adding headcount. That's a different category of leverage. I'm not selling a trend — I'm running it live inside real businesses. The gap between companies that have working AI and those that don't compounds every quarter. The question isn't whether it's real. It's which side of that gap you're on.
I run a real business, not a tech company. Where does someone actually start — the tactical answer, not the philosophical one?
Start with the thing that costs you the most when it breaks down. For most service businesses that's speed-to-lead — how fast you answer an inbound inquiry before a competitor does. It's measurable, high-stakes, and AI solves it cleanly. You don't overhaul your operation; you build one working system that shows a real number in 45 days. Then you decide whether to go further. Small scope, real stakes, real proof.
Every agency overpromises and underdelivers. How would I actually know if it's working?
That distrust is earned, so my answer is structural. Everything is instrumented. You don't get a quarterly report telling you what happened — you get a live dashboard showing where every lead came from, the path it took, and what it cost. You own that dashboard. You own the ad accounts. You own the customer list. If I stop performing, you take the system and go. The measurement is part of the product on day one — not an afterthought at renewal.
You studied ethics at Harvard. Most people selling AI don't. What should we genuinely be careful about — not the sci-fi version?
The real risks aren't robots — they're mundane and serious. First, dependency without understanding: companies that buy AI they can't read become brittle when it breaks. That's why I build systems clients own and can see inside. Second, measurement theater — output that looks impressive but is never tied to a business result. Third, speed without judgment: AI removes friction, so bad decisions move faster too. The obligation isn't to slow down. It's to be deliberate about what you're accelerating — and to keep asking whether the thing you're optimizing for is the right thing.
Why now, and why here
The window is still open in Atlanta.
Robert builds here, and his clients are here. In most Atlanta service categories, no one has locked the AI advantage yet — and the first operator to compound real data, attribution, and optimization in a category builds a lead competitors can't simply buy later. Same dynamic as a website that's been earning authority for three years: you can't purchase that head start the day you finally decide to start. The window is open today. It closes the moment a competitor moves. The members in this room are exactly the operators who should be first.
What he builds
The system behind the answers.
Buildwise Media builds verifiable, autonomous marketing systems for service businesses — a pre-built revenue engine across eight layers, plus custom AI built for each client's own workflows. The client owns the code, the data, the ad accounts, and the customer list on day one.
To assemble the equivalent from specialists — a fractional Chief AI Officer, an AI implementation boutique, an AI-first revenue-operations platform, a website team, a paid-media manager, a content studio, a social agency, and a data-and-attribution retainer — runs roughly $25,000–$50,000 a month plus $45,000–$150,000 upfront, across six to eight vendors who don't share data. The closest single comparable does one of those eight, for about $15,000 a month.
Same scope. One system instead of six to eight that don't share data — at a fraction of the assembled cost.
The promise: 5x attributable return within 24 months — or the team keeps building, at no added cost.
In his words
Most operators don't have a strategy problem. They have a tooling problem.
AI didn't remove work. It removed friction.
The early movers aren't just ahead. They're building something competitors can't buy.
The ask
Give him the stage.
For the Catalyst Collective's Summer of AI: a live, member-driven Q&A, hosted by Cathryn Marshall, with an operator who will answer the hard questions and leave the room with something useful in hand. If it isn't the most practical hour on the summer calendar, that's on us.