Thesis - The System of Trust
What Comes After Action
by Christopher Bartlett, CEO Founder of tapestry®
In 2023, the phrase “System of Action” entered the technology lexicon — popularised by David Yuan as the next evolution of Geoffrey Moore’s “Systems of Engagement” and the earlier “Systems of Record" that defined the SaaS era. Systems of Action don’t just record or inform decisions — they execute them: real-time, dynamic, embedded.
But beneath every action lies a more human question:
Can I trust this?
The next inevitable shift is the System of Trust — where predictions are tied to proof, outcomes are verified, and confidence compounds into adoption and growth.
Spend five minutes with ChatGPT and you’ve likely felt it — that flicker of hesitation, that gut check: wait, is this true?
AI now tells us what to stock, who to target, what to do next. And yet CEOs, operators, and individuals pause. Why? Because recommendations without transparency trigger doubt:
This hesitation isn’t just emotional. It’s mathematical.
AI outputs are probabilities, not facts. A forecast, a match score, a fraud alert — all are distributions, not certainties.
The problem:
The solution: feedback loops that collapse uncertainty.
Every real-world outcome — sales, behaviour, loyalty — becomes a proof point. Each proof shrinks the gap, compounds confidence, and accelerates adoption.
AI without feedback is just a probability machine spinning into doubt.
AI with feedback compounds into trust.
Sales data is the ultimate signal.
It is the most complete expression of commercial reality — where pricing, supply chain, customer behaviour, and competition intersect.
Feeding sales performance back into AI doesn’t just sharpen accuracy. It aligns the system to what actually matters:
Sales data doesn’t just reflect the business — it steers it, by integrating directly into the AI feedback loop.
Markets don’t exist in a vacuum. Culture, politics, and sentiment shape them.
Platforms like Amplify in Australia are beginning to measure civic sentiment and loop it into decision-making.
If sales data is the macro signal, personal data is the micro signal.
Each of us carries a map of affinities — the products, people, and experiences we value. Misread them, and trust collapses: loyalty drops, engagement withdraws, adoption stalls.
Personalisation is not convenience — it is confidence. But confidence compounds only under governance.
The equation is simple:
Thus the System of Trust requires both layers:
The confidence gap is not a minor hesitation. It is the invisible tax on every AI-powered decision.
Without trust, AI stalls.
With trust, AI compounds.
Trust compounds like interest.
Each proof point doesn’t just add confidence — it multiplies it. Each loop tightens the bond between system and outcome, user and platform. Over time, this creates acceleration, not just adoption.
The equation is simple:
Trust = Proof of Performance + Confidence in Alignment + Control of Data
And trust is systematically mispriced. In markets, an increase in trust lowers CAC, shortens sales cycles, raises ALV, improves NPS, and drives virality.
This is the true network effect: compounding trust.
To build a System of Trust, new infrastructure must be developed and integrated:
A full System of Trust requires:
For the first time, real-time data is already being bought and sold. Trust is no longer abstract — it is transactable.
The System of Record gave us memory.
The System of Action gave us speed.
The System of Trust gives us certainty.
Where there is doubt, there is hesitation.
Where there is hesitation, growth is lost.
That is the confidence gap.
Which is where we are standing, and why —
The System of Trust isn’t optional. It is inevitable.
For AI. For commerce. For society.
Christopher Bartlett is the founder of tapestry®, an AI-powered platform transforming how retailers, brands, and partners make decisions. At its core is Hank, an AI co-pilot that connects data, insight, and action—helping businesses move faster and smarter.
tapestry® is trusted by Fortune 500 companies and built to power a $25T market. It enables real-time data trading, unlocks new revenue, and delivers instant visibility across the retail network.
With 15 years of experience and over 90 software products to his name, Christopher has founded and sold companies, worked with global brands like Uber, Kmart, and Hoyts, and spent over a decade developing the proprietary tech behind tapestry.
He’s building not just intelligence—but the infrastructure for the future of commerce.