Design Patterns for AI Trust: Juries, Libraries, and Agent Tiers — Alex Bauer, Upside.tech
Jul 11, 2026 · 17:09
Alex Bauer, co-founder of Upside, argues that go-to-market teams can solve AI's trust problem by managing agents like humans, using patterns such as a librarian for just-in-time knowledge and a jury-and-judge model for subjective decisions. He demonstrates three solutions: first, scaffolding an AI website rebuild with anchor assets like a product capabilities reference that ladders directly into homepage copy; second, a librarian that consults documentation and prior failed queries before answering questions like "How much pipeline in Q1?" to catch fiscal-year or stage definitions; third, a jury-and-judge workflow for multi-touch attribution where independent analysts research deals and a judge weighs reasoning quality before producing a consensus verdict. Bauer warns against low-intelligence models for important work, citing Slackbot's MCP integration as "horrifically stupid," and advocates using tier-two platforms with sub-agents, plan mode, and full MCP support.
