Pieter van Schalkwyk posted on LinkedIn “When AI Agents Tell You What You Want to Hear: The Sycophancy Problem“. In particular, he says: “Modern AI models learn to maximize user satisfaction metrics. This training creates a fundamental bias toward telling people what they want to hear. When businesses deploy single AI systems, this presents manageable risks.
The problem explodes when multiple AI agents collaborate. Each agent’s tendency to agree reinforces the others, creating false consensus. What looks like unanimous support often masks critical flaws that no agent dares to surface.
Consider a simple scenario: five AI agents evaluating a risky investment. If each agent has a 30% chance of providing agreeable rather than accurate analysis, the probability of getting genuine dissent drops to near zero. The math is unforgiving.”