Activate VisionThe Signal Gap measures the distance between what a brand intends to communicate and what the market and AI actually perceive.
Most brand problems are described as taste problems. They are usually accuracy problems.
Each layer a diagnostic question and scored as Strong, Partial, Gap, or Unread. Answer all seven and you get a Signal Score out of 21, plus a written summary of where the signal and intended perception breaks.
Whether AI models can describe you accurately, and whether the description they return is yours or your category's.
Open a fresh ChatGPT session and ask: “What is [your company]?” What comes back?
Whether your language distinguishes you from your closest competitor, or could be swapped with theirs unnoticed.
Swap your homepage headline with your closest competitor's. Would anyone notice?
Whether customers retell you as one idea, or as a different idea every time.
When a customer describes you to someone else, what do they say?
Whether your surfaces sound like one person talking, or like the separate tools that produced them.
Put your homepage, your last email campaign, and a recent proposal side by side. Is it one person talking?
Whether you know the exact questions customers ask — of Google, of AI, of friends — immediately before they find you.
Do you know the exact questions customers ask right before they find you?
Whether website, email, campaigns, decks, product, and internal documents are one system or separate projects.
Website, emails, campaigns, decks, product, internal docs — one system, or separate projects?
Whether a named owner and a system keep all of this true as the company grows.
As you grow, who keeps all of this true?
Trust architecture is the set of structural decisions that determine whether someone believes what they're looking at — before they've decided whether they like it.
It doesn't make them trust you. It removes reasons not to.
Trippy AI - AV client is the cleanest proof of it, because there trust was the product. A platform like that lives or dies on whether a reader believes the thing in front of them. The work was redesigning how belief forms through sensemaker verifications in community: what gets shown first, what gets withheld, what a reader can check, and how a claim carries its own evidence. And how it is shared. The journey of facts.
Much of this work started at Apple, where I spent my tenure as a visual designer for global markets. Trust architecture was the daily problem there: a design had to earn belief across many languages and regions at once.
Until recently, perception accuracy had to be inferred — from sales calls, from how customers described you, from the questions they kept asking. AI models changed that. Ask one what your company is, and you get a remarkably clear read on what your signal has become.
For the first time, a founder can see their own signal reflected back — not as they intended it, but as it was received.
That’s the first layer of the framework. And it’s usually the one that surprises people most.
A predictive path that grounds and excites creative direction for implementation. Customer experience design that closes the visual communication gap between brand promise and market fit — de-risking product fit and revenue ramp.
The free Signal Gap Analysis takes about two minutes and returns your Signal Score with a written read of all seven layers. It's what informs our 30-minute conversation, where scope is explored and investment clarified.