Why AI models keep getting Convex components wrong

We expanded the Convex LLM benchmark from 73 to 109 evals, adding newer APIs and dedicated tests for components including Aggregate, Rate Limiter, Workpool, and Agent. The results expose a recurring problem: without Convex guidelines, models often hand-roll solutions instead of choosing battle-tested components. See the Convex LLM leaderboard: https://convex.dev/llm-leaderboard Build with Convex: https://convex.dev #Convex #AICoding #LLMEvals