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DX · Technology

Engineering Enablement by DX

The show focused on developer productivity and the teams and leaders dedicated to improving it. Each episode features in-depth interviews with Platform and DevEx teams, along with the latest research and approaches for measuring developer productivity. Presented by DX (getdx.com), the developer intelligence platform designed by researchers.

Episodes

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How Meta reduced diff authoring time by 40%

02 Oct 2026
46m
AI processed

Diff authoring time (DAT) serves as a critical metric for quantifying the active effort developers spend on engineering, reviewing, and testing code changes. By tracking these units of work with high precision, organizations can conduct controlled A/B experiments on development tools and frameworks, shifting engineerin...

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How Okta sets guardrails and context for AI agents

11 Sep 2026
37m
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Code Quality & AI Readiness at Capital One

26 Aug 2026
42m
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AI integration in software development amplifies existing organizational strengths and weaknesses, making foundational engineering principles more critical than ever. Rather than replacing core skills, AI necessitates a shift toward clearer communication, design intent, and problem definition. While AI excels at refact...

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AI in engineering: Q2 2026 benchmarks & research readout

14 Aug 2026
38m
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AI adoption in software engineering has reached near-saturation, shifting the industry focus from simple usage to the sophistication of AI integration. While PR throughput and developer time savings continue to climb, these gains are accompanied by a concerning increase in PR size and volatility, which threatens code m...

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How Microsoft sees engineering bottlenecks changing with AI

07 Aug 2026
39m
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Research briefing with Brian Houck: Measuring AI agents, revisiting the Core 4, and more

24 Jul 2026
46m
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Adopting the product operating model at Priceline

10 Jul 2026
42m
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Priceline’s transition to a product operating model centers on aligning organizational structure with developer experience to eliminate functional silos and improve delivery speed. By moving from a project-based approach to autonomous, product-aligned teams, the organization empowers engineers to identify and resolve b...

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2x the power users: How structured AI training scaled developer productivity

29 Jun 2026
40m
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From PR throughput to product velocity: How Dropbox is rethinking productivity in the agentic era

29 Jun 2026
21m
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AI and engineering productivity: Debating the headlines

29 Jun 2026
39m
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AI integration in software development functions primarily as an amplifier of existing engineering workflows rather than a direct replacement for human developers. While AI accelerates code generation, the primary bottlenecks in software delivery remain organizational factors like planning, prioritization, and human co...

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Beyond the CLI: Agentic AI for async workloads and non-developers

22 Jun 2026
37m
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Uber’s journey of measuring AI impact on developer productivity

22 Jun 2026
41m
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The future of engineering at Nationwide, Comcast, TD, and HPE

22 Jun 2026
36m
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From AI experiments to organizational shift: Lessons from Mercari’s transformation (Michael Galloway and Snehal Shinde)

15 Jun 2026
44m
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Mercari’s transition to an AI-native organization reveals that AI adoption is not a finish line but a catalyst for exposing deep-seated organizational bottlenecks. While AI significantly accelerates coding, it often hits friction in legacy systems, manual approval gates, and fragile CI/CD pipelines, leading to a "W cur...

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Doubling the productivity of your engineering team using AI (Brian Scanlan)

15 Jun 2026
39m
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Augmented, accelerated, autonomized: How Vanguard is embedding AI across the product lifecycle (Kelly Anne Pipe and Nicole Scribner)

15 Jun 2026
39m
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Prioritization as code: An AI-supported framework for platform engineering (Eleanor Millman and Mina Tawadrous)

15 Jun 2026
38m
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Platform engineering teams often struggle to prioritize work without clear revenue-linked metrics. SiriusXM addressed this by developing a weighted prioritization formula incorporating seven impact factors: development speed, runtime reliability, security, cost reduction, platform efficiency, user trust, and data-drive...

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Beyond AI tools: Evolving software engineering organizations for the agentic era

08 Jun 2026
29m
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The current impact of AI on engineering velocity: What 400 companies are seeing (Abi Noda & Brian Houck)

08 Jun 2026
26m
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AI adoption in software engineering yields modest productivity gains, with organizations reporting a median 8% increase in pull request throughput rather than the anticipated exponential growth. Because coding occupies only 14% of a developer's total time, AI-driven improvements to code generation have a limited impact...

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Mapping the new SDLC at BNY: Codifying AI into every step of the delivery lifecycle (Jason Valentino)

08 Jun 2026
33m
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