According to DeepLearning.AI on X (Twitter), Vercel CTO Malte Ubl argues that teams “need” technical debt because managed shortcuts enable faster iteration, tighter feedback loops, and quicker market learning for AI products, as shared in a promo for AI Dev 26 in San Francisco on April 28–29. As reported by DeepLearning.AI, the insight underscores a pragmatic engineering approach: intentionally incurred, well-tracked technical debt can compress time-to-value for AI features, letting startups validate model integrations, inference pathways, and user experience rapidly before refactoring. According to DeepLearning.AI, this creates three tangible business opportunities for AI teams: 1) speed-to-market for model-powered features and agent workflows, 2) disciplined debt registers to prioritize refactors tied to user impact, and 3) staged architecture upgrades aligned to usage telemetry and unit economics.