Sales and marketing teams are racing to adopt AI agents, but according to Alex Bauer, founder and CEO of Upside.tech, they're walking into a trap. The industry spent years worrying about hallucination, but Bauer, speaking on the AI Engineer podcast, argues that's been replaced by a trust problem: AI confidently hands out wrong answers that look exactly like right ones. His solution is to manage agents like human employees, giving them onboarding, structured documentation, and the "why" behind every task, a principle borrowed from military doctrine called Commander's Intent. He outlined three concrete patterns Upside uses: scaffolding output with curated reference documents; a Librarian agent providing just-in-time context; and a Jury and Judge workflow that spins up multiple independent AI analysts for problems with no single correct answer. Bauer warned that cheap model tiers produce "agent tears," and that the cost-cutting impulse sweeping across corporate AI programs—from Tesla's $200 weekly cap to broader enterprise pullbacks—could backfire. His closing message: the real dragon is the assumption that one model call, unsupported, will be enough. Bauer also compared AI to the bicycle, saying "Claude does for building basically what the bicycle did for mobility," making it accessible. Two years ago, redesigning a company website meant assembling a cross-functional team for two months; today, he can scaffold the same project over a weekend.