Most AI advice comes from strategists who have never shipped anything, or from
engineers who have never sat with a customer. The gap between those two is where
AI projects go to die. Side B exists in that gap.
Brandon BreonPrincipal
My background is product design at enterprise scale — lead and senior
design roles across Deloitte, AEG,
Elsevier, where I led design for the Digital Commons product
group, Accenture, and West Marine. Much of the
recent work has been on enterprise AI products: figuring out what one should
actually do before anyone builds it. I studied business strategy at
Harvard Business School.
Twenty-something years of that work teaches you one thing above all: the
technology is almost never what decides whether something succeeds. What decides
it is whether anyone understood the actual job well enough to build the right
thing.
So when AI agents arrived, I did the obvious thing for someone with that habit
— I stopped writing about them and started building them. Not prototypes.
A research agent that pulls SEC insider filings and options flow and scores
conviction across dozens of stocks. A lead-generation agent that emails a sales
team a fresh, qualified, deduplicated list every weekday morning, running in the
cloud, without anybody's laptop being open. Both started the way good projects
usually do: somebody asked could AI do this? and meant it as a real
question.
Building those taught me things you cannot get from reading about AI. Where
models are unreliable and what that costs. How much of the work is data and how
little is the model. Why the second month is harder than the first. What "it
works" actually means once real people depend on it at 8am on a Monday.
That combination is what you're hiring: design judgment about what's worth
building, and enough engineering to build it — and to tell you honestly
when it can't be built well. Same person, both halves. No
handoff where the strategy meets the code and something quietly gets lost.
The name
Why "Side B."
The A-side was the single. The one the label was confident about, the one
engineered for radio. The B-side was where the interesting work happened
— the track somebody made because they wanted to hear it, that turned
out to be the one people kept.
AI right now is very loud on the A-side. Enormous claims, enormous budgets,
and a lot of demos that never make it into anybody's actual Tuesday. The work
that pays off is quieter: one process, done properly, running every day
without anyone thinking about it.
That's the side I work on.
How I work
Five things I believe, that shape every engagement.
01
Start where the pain is, not where the technology is
The most impressive available thing and the most valuable available thing are
rarely the same thing. I start from what's costing you time or money right now
and work backwards to the technology — sometimes arriving at something
unglamorous that saves eight hours a week.
02
Working beats impressive
A demo proves something is possible. It doesn't prove it survives your real
data, your edge cases, or the Thursday when the input arrives in a format nobody
anticipated. I'd rather ship something narrow that runs than something broad
that almost does.
03
You should be able to fire me
Everything comes documented, with the reasoning written down and the code and
prompts in your hands. If you'd rather take it in-house, or hand it to another
developer, nothing about how I've built it should make that painful.
04
Say the unwelcome thing early
If AI isn't the right answer, if your data isn't ready, if the vendor is
overselling — you'll hear it on the first call, not in week six.
That costs me some engagements. It also means the ones I take tend to work.
05
Design the human part too
Most AI failures aren't technical. Somebody didn't trust the output, or the
handoff was unclear, or nobody knew what to do when it was wrong. Deciding
where a person stays in the loop is a design problem, and it's usually the
one that determines whether any of it gets used.
—
And one practical note
I take a limited number of engagements at a time. It's the only way the work
gets real attention, and it's the reason I can be honest about scope instead of
saying yes to everything and hoping.
Currently Taking new clients.
Elsewhere
I write about this in public.
breon.ai is where I think out loud about AI agents,
design, and where the two meet — including the builds behind this practice.
research.breon.ai tracks how AI is changing
design work, refreshed monthly.
If you want to know how I think before you talk to me, start there. It's the same
voice you'll get on a call.
Thirty minutes, no pitch.
Tell me what's costing you the most right now and I'll tell you whether I can help.
If I can't, I'll usually know who can.