How do you find a good AI agent when there are thousands of them? The same way you find a good plumber: you ask someone you trust.
That's the core argument in a growing conversation about AI agent discoverability. The premise is simple but has big implications: traditional search and SEO were built for a world where creating content was hard and discovering it was the bottleneck. AI flips that. Creating is now trivially easy. The bottleneck is figuring out what's actually good.
SEO rankings work because Google can crawl pages, measure backlinks, and estimate authority. But AI agents aren't web pages. They're services that do things - book flights, write code, analyze data. You can't evaluate them by reading a meta description. You evaluate them by whether they actually work, and whether people you trust say they work.
This points toward "reputation graphs" as the discovery layer for AI agents. Think of it like a web of trust (a concept borrowed from cryptography) where each agent builds a track record based on verified interactions. If an agent reliably handles expense reports for 500 small businesses, that reputation follows it. Other agents and users can reference that history when deciding whether to delegate tasks.
The practical version of this already exists in fragments. App store ratings are primitive reputation systems. GitHub stars signal developer trust. LinkedIn endorsements (for all their flaws) map professional credibility. The argument is that AI agents need something purpose-built: a system where trust is earned through successful task completion, verified by the people and agents involved, and portable across platforms.
For anyone building or selling AI tools, this has real consequences. Today, you market an AI product the same way you market any SaaS product: SEO, paid ads, review sites, word of mouth. If agent-to-agent trust networks become the primary discovery channel, the playbook changes entirely. Your agent's reputation score matters more than your landing page. Integration with trust protocols matters more than your Google ranking.
We're not there yet. No dominant reputation protocol exists for AI agents, and the big platforms (OpenAI, Google, Anthropic) will likely try to build their own closed versions. But the underlying logic is sound: when supply is infinite, curation through trust beats curation through algorithms. The companies building these trust layers now are betting on being the Google of the agent era - not by indexing content, but by mapping reliability.