Builder Reveals How Hard It Is to Make an AI Agent Genuinely Disagree

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A developer building an AI tool called 'Something' found that getting AI models to offer genuine criticism is surprisingly difficult, as most default to agreeable, softened responses even when prompted to find flaws. To work around this, the team engineered a two-agent system where one agent looks for growth potential while the other is explicitly tasked with finding disqualifying flaws. A reconciliation step then merges both outputs into a single conviction score, giving users a clearer verdict rather than two contradictory paragraphs. The project, aimed at founders, has opened a public waitlist. The developer is now seeking input from others who have tackled similar 'sycophancy' problems in adversarial AI setups.

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