Some time ago I read a LinkedIn post claiming that one of my favorite artists had saved 47 dogs from an uncertain fate. The title: “Bob Dylan Buys a Dog Rescue Center That's About to Close - But What He Did to the Dogs Has the Internet surprised....”
The phrase “What He Did to the Dogs” could be the setup of a Quentin Tarantino storyline about an aging rocker who makes 47 dubious decisions involving labradoodles. The post itself was standard AI slop: smoothly written, plausibly structured, emotionally manipulative, unburdened by reality. It ended with Dylan adopting an elderly, arthritic retriever named Sam. “He's waited the longest," Dylan said softly. “Now I'll wait with him.”
This fable illustrates a core challenge for any organization or individual trying to build authority in an age of ambient intelligence. When anyone can sound like an expert on any topic by firing up an LLM, how do audiences know who to trust?
Scarce trust
The Dylan puppy rescue story was absurd. The trust problem behind it is not. It belongs to a broader environment in which plausibility is abundant and trust is harder to earn.
Edelman’s 2026 Trust Barometer describes a world where trust is scarce and increasingly conditional. This year, Edelman surveyed nearly 34,000 people across 28 countries. The study found that 70% of respondents are unwilling or hesitant to trust someone with different values, backgrounds, approaches, or information sources.
Nearly seven in 10 fear institutional leaders are deliberately misleading the public. Misinformation and the growing use of generative AI platforms rank among the forces reshaping trust.
Frames are claimed through evidence.
This is the market every company now speaks into: confident claims are easy to generate, shared trust is weaker, and audiences are more likely to discount authority unless it is backed by evidence.
The good news is that business still has a trust advantage. Business remains trusted by 64% of the general population, while “My Employer” is trusted by 78% of employees. In a low-trust environment, companies still have a platform from which to speak.
That is what makes the current moment so risky. Companies are in real danger of squandering the trust they have worked so hard to build.
The danger is not AI-generated content per se. Used carefully, AI can make communication faster, clearer, and more consistent. The danger is over-reliance on content that looks authoritative but is not anchored in evidence.
Corporate websites and social feeds are increasingly stuffed with material that displays all the surface markers of expertise: confidence, polish, strategic urgency, customer-centricity, and AI fluency. But surface authority is not the same as earned authority.
Unless those claims are backed by proprietary data, operating experience, customer evidence, or original research, they blur into the same re-swizzled conventional wisdom everyone else is publishing. The result is not immediate distrust. It’s something quieter and more corrosive: indifference.
The positioning trap
In my experience, companies often misdiagnose why their story isn’t landing. They assume they need better language: sharper messaging, cleaner category descriptions, snappier taglines, a more differentiated narrative.
Sometimes that’s true. Words matter. But more often, weak language is a symptom of a deeper problem: the company hasn't given its audience enough reason to believe. The claim may be smart. The strategy may be sound. The ambition may be real. But without proof, the story has nothing to stand on.
The answer to the Dylan puppy problem is not better copy. It’s better proof, which can take many forms: proprietary data, customer outcomes, operating insight, research, benchmarks, adoption patterns, behavioral signals, technical evidence, and field intelligence.
It can even be a movie made by manipulating atoms.
Atomic yo-yo
In 2013, IBM Research released A Boy and His Atom, a stop-motion film made by moving carbon monoxide molecules with a scanning tunneling microscope. The film, recognized by Guinness World Records as the world’s smallest stop-motion movie, shows a tiny stick figure playing with a yo-yo.
To date, this 90-second video has attracted more than 27 million views on YouTube.
The film was charming, but its charm was not the point. IBM could have just said it was doing advanced research in nanoscale data storage. Instead, it made the capability concrete. The artifact was the argument: here is what it means to manipulate matter at the atomic scale.
That’s the differencebetween positioning and proof. Positioning says, “We are a leader in nanoscale research.” Proof says, “Here is a movie made by moving atoms.” The story worked because it didn’t ask the audience to accept IBM’s authority on faith. Instead it gave people something they could see, repeat, and remember.
Payroll proof
ADP did something similar in a different domain. The company processes payroll for thousands of companies across the United States. As a result, it hosts a treasure trove of data about private-sector hiring trends.
Since 2006, ADP has been using aggregated, anonymized payroll data to create the ADP National Employment Report, a monthly view of the U.S. labor market produced by the ADP Research Institute in collaboration with the Stanford Digital Economy Lab.
The report is based on payroll data covering more than 26 million private-sector employees across the country. ADP offers it as a resource for investors, policymakers, business leaders and the general public.
ADP’s analysis became especially valuable during the federal government shutdown of fall 2025, when official labor market reports were delayed. In that gap, private-sector signals like ADP’s became more important to analysts trying to gauge the direction of the labor market.
ADP didn’t build lasting authority just by being an efficient payroll processor. Instead the company created a recurring body of evidence that helps the market understand hiring and pay trends.
Proof needs a system
In markets crowded with confident claims, positioning can quickly become interchangeable. Nowadays, just about every company claims to be AI-native, enterprise-grade,outcome-driven, customer-centric, transformational.
The question is not whether the claim sounds good. The question is whether the company can prove it in a way the market recognizes. Good proof does more than validate a claim. It changes what the market pays attention to. It gives buyers, analysts, journalists, investors, and employees a better way to understand the category.
Most companies have proof scattered everywhere: in product telemetry, customer stories, sales call summaries, analyst conversations, implementation work, support tickets, research, executive intuition.
Few have a system for extracting that evidence, shaping it, and turning it into market authority.This is where Walled City comes in: we help companies turn buried proof into a defensible market frame.
Frames are claimed through evidence. The market won’t adopt your position just because you state it clearly. It adopts your position when your proof makes the old frame harder to sustain. Proof beats positioning because proof changes what the market can see.