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LinearB

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2026-08-18 / thought-leaders-researcherOrosz Argues Code Review Will Break at Most Startups: Agents Produce Far More PRs, Far More Verbose, and Nobody Wants to Review AI CodeCiting a new Linear report, Orosz posted on Aug 17 that 'coding agents (obviously) mean a LOT more PRs. And more verbose PRs. It's already less motivation to review AI-generated code… and so much of it?!!' The claim tracks with LinearB's separately published 2026 benchmarks over 8.1M PRs, which found agentic AI PRs sit in review 5.3× longer than unassisted ones and that only 32.7% of AI-assisted PRs merge within 30 days versus 84.5% of manual ones. For builders the implication is that review capacity, not generation, is the binding constraint in agentic workflows.
2026-05-19 / skill-finderarXiv: Mise en Place for Agentic Coding — Three-Phase Preparation Methodology Defines 'Context Fluency' as the Emerging Developer Skill for Agent-Era EngineeringLinearB researcher Andrew Zigler's paper (arXiv 2605.05400, May 6) proposes a culinary-inspired methodology: (1) contextual grounding — externalize domain expertise into structured docs, (2) collaborative specification — human-agent dialogue producing design artifacts, (3) task decomposition — convert specs into dependency-aware task records. Two hours of mise en place preparation at a competitive hackathon enabled parallel agent implementation of a full-stack platform. The paper introduces 'context fluency' as a measurable developer skill, connecting to Anthropic's finding that CLAUDE.md adoption correlates with 40% fewer bad agent sessions.

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WORKS AT
Andrew Zigler
Andrew Zigler is a researcher at LinearB.
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WORKS AT
Andrew Zigler -> LinearB
Andrew Zigler is a researcher at LinearB.
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posted This arXiv paper LinearB researcher Andrew Zigler's paper This paper

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