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41 articles tagged Engineering Management.
Analysis of the One Billion Row Challenge reveals strategic insights on balancing computational performance with code maintainability. Explores runtime selection, hardware-aware engineering, and community-driven talent acquisition for technology leadership.
Linear B's 2026 report reveals AI adoption is universal but impact lags, with AI PRs merging at half the rate of human code due to review bottlenecks, larger PR sizes, and technical debt accumulation.
An executive analysis of the shift toward AI compute as a compensation component, the rise of harness engineering for agentic workflows, and the operational risks associated with rapid AI adoption in enterprise environments.
James Everingham of guild.ai shares how Meta’s DevInfra team shifted from AI autocomplete to agentic infrastructure. Learn why centralized control planes are essential for governing agent workflows, reducing onboarding time, and eliminating code freezes through organic, challenge-driven adoption.
Monday.com VP of RD Sergey Lykoveski details how the company paused its roadmap for 30 days to enable AI across 700 engineers. This strategy prioritized foundational infrastructure over quick wins, resulting in a four-tier AI product suite and significant operational efficiency gains.
Dex Horthy analyzes the unit economics of autonomous coding loops, revealing a cost of approximately $10.42 per hour for software execution. The discussion highlights the shift from code generation to context engineering, emphasizing that planning and intermediate artifacts are now the primary drivers of engineering velocity and quality.
DORA research and industry experts analyze how GenAI acts as an amplifier for software delivery. This brief covers the shift from code writing to context engineering, the strategic value of specs, and actionable steps for leaders to manage AI-driven throughput and risk.
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.
