Collin Brown Releases AI You Can Actually Trust, Introducing the VERA Framework for Catching AI Errors Before They Reach Stakeholders

New book addresses the reliability gap as professionals face growing accountability for AI-generated mistakes.
Collin Brown, a technology leader specializing in AI reliability, today announced the release of AI You Can Actually Trust , a book that introduces the VERA framework for professionals who rely on artificial intelligence but cannot afford costly errors or reputational damage.

As AI becomes embedded in professional workflows across law, healthcare, finance, and nonprofit management, a consistent pattern is emerging. AI outputs often sound confident and authoritative while containing fabrications, outdated information, or internally consistent narratives that collapse under scrutiny. When those failures occur, responsibility does not fall on the systems themselves. It falls on the professionals who relied on them.

"The Deloitte analysts did not lack training. The federal judges did not lack experience," said Brown. "What they lacked were systematic practices for catching AI errors before those errors reached stakeholders. The solution is not better AI. It is better verification."

AI You Can Actually Trust uses case-based scenarios to illustrate how competent professionals can be misled by AI-generated output. One example opens with a $75,000 grant application undone by fabricated foundation research that appeared credible but was entirely false. These scenarios lead to the introduction of the VERA framework, a four-part system designed to help professionals detect errors before consequences become irreversible.

The VERA framework includes:

* Verification: Confirming AI outputs against authoritative sources.
* Error Detection: Identifying patterns that signal fabrication or unreliable reasoning.
* Reliability: Building systematic fallbacks before failures occur.
* Accountability: Documenting decisions and assumptions to support stakeholder confidence.

The book also examines an emerging risk Brown calls "cascade hallucination," a failure mode in which an initial AI error propagates through subsequent steps, producing outputs that appear coherent while being entirely fictional.

"We are already seeing this pattern in healthcare, legal research, and financial analysis," Brown said. "Organizations that build detection practices early will be far better positioned than those that learn only after a public failure."

AI You Can Actually Trust is available now in paperback and digital formats on Amazon.

About Collin Brown

Collin Brown is a technology leader and author specializing in AI reliability and verification in high-stakes decision-making
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