Everyone is building faster AI agents. Faster code. Faster research. Faster everything. Nobody is asking the question that matters: how do you know the output is real?
This year, AI agents became a labor force. They draft the emails, close the tickets, sign the requests, move the money - increasingly while talking to other people's agents. Which makes one question the most expensive question in business: when an agent shows up claiming to act for someone, how do you know it's telling the truth?
The old internet had a trust problem. The AI internet has a trust crisis.
Sell Trust is the field manual for the layer that resolves it, and a map of the business opportunities that true agentic autonomy unlocks. The promise is the one every AI deployment is starved for: finally letting go of the review bottleneck - without letting go of accountability.
Written by a PhD in artificial intelligence who spent a decade building cryptographic trust for governments across Latin America - and who runs a fleet of AI agents on the very rails this book describes - it makes one argument from every angle that matters: the bottleneck of the AI era was never capability. It is verification. And verification has an architecture: identity you can prove, authority with edges, and a record that survives the story anyone tells about it later. A mandate in. A receipt out.
You'll learn why Google's rise is the precise blueprint for the trust economy, why "just use OAuth" is the most reasonable-sounding wrong answer in the room, why one of the most-starred repositories in GitHub history became a 543-vulnerability cautionary tale, and why the last human moat was never the work - it was clarity about what's worth doing, and proof of what was done.
In a gold rush, sell shovels. In an AI rush, sell trust.