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3 articles tagged SDLC Optimization.
Dee Wilcox, CTO at NuCela, details how AI adoption shifts engineering bottlenecks from development to review and planning. Learn how to use baseline KPIs, centralized ML teams, and iterative asset tracking to manage AI transformation ROI and maintain quality gates.
DX's longitudinal research reveals AI boosts engineering throughput by 8-15%, debunking 10x hype. Coding optimization hits structural limits as coding comprises only 14% of dev time. Leaders must avoid false velocity, expand AI across the SDLC, and prioritize cultural adoption to realize outlier performance and sustainable business value.
Linear B CEO Ori Karen predicts that 2026 will be a year of normalization for AI in engineering. While code generation hype persists, true ROI will emerge from optimizing downstream SDLC processes, implementing risk-based code reviews, and shifting metrics from adoption to impact.
