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Engineering Enablement
Research and perspectives on developer productivity.
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Don’t measure AI Code Percentage on its own
October 7th, 2026
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How Meta reduced diff authoring time by 40%
October 2nd, 2026
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Do you really need another framework?
September 30th, 2026
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Introducing CAFE(S): A framework for defining AI context quality
September 24th, 2026
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Your agent doesn't have a model problem
September 16th, 2026
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How Okta sets guardrails and context for AI agents
September 11th, 2026
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AI accelerates output, not innovation
September 9th, 2026
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The quality paradox of AI-generated code
September 2nd, 2026
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Code Quality & AI Readiness at Capital One
August 26th, 2026
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Can “Predictable Delivery” be measured?
August 21st, 2026
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Is there a relationship between cycle time and PR throughput?
August 19th, 2026
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AI in engineering: Q2 2026 benchmarks & research readout
August 14th, 2026
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“Your benchmarks don't apply to us"
August 14th, 2026
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DX Annual 2027: San Francisco and London
August 11th, 2026
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How Microsoft sees engineering bottlenecks changing with AI
August 7th, 2026
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What are code reviews even for?
August 5th, 2026
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The unexpected things developer metrics can measure
July 31st, 2026
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Measuring the impact of AI coding tools: Capacity, not horsepower
July 29th, 2026
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Research briefing with Brian Houck: Measuring AI agents and revisiting the Core 4
July 24th, 2026
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The State of AI Impact in Engineering: Q2 2026
July 22nd, 2026
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