<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>DORA on Revelara</title><link>https://revelara.ai/tags/dora/</link><description>Recent content in DORA on Revelara</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 04 May 2026 08:00:00 -0700</lastBuildDate><atom:link href="https://revelara.ai/tags/dora/index.xml" rel="self" type="application/rss+xml"/><item><title>What the DORA 2026 J-Curve Actually Says About Reliability and Vibe Coding</title><link>https://revelara.ai/blog/dora-2026-j-curve-reliability-vibe-coding/</link><pubDate>Mon, 04 May 2026 08:00:00 -0700</pubDate><guid>https://revelara.ai/blog/dora-2026-j-curve-reliability-vibe-coding/</guid><description>&lt;p&gt;DORA shipped &lt;em&gt;The ROI of AI-Assisted Software Development&lt;/em&gt; recently. There&amp;rsquo;s an interesting number from that report that ties back to a Google Cloud 2025 report on the ROI of AI; 78% of executives from organizations with C-level AI sponsorship report seeing ROI now on at least one generative AI use case. The new report shares a number I have not seen quoted before, a 15% productivity drop used as the default in its sample ROI calculator. The report is explicit that the actual depth and duration of the dip are unpredictable; 15% is a placeholder input, not a measurement. On a 500-engineer organization at $176,000 fully loaded salary, that is $3.3 million in lost capacity over three months. The report calls this the &amp;ldquo;tuition cost&amp;rdquo; of AI adoption. It includes the line item in its example budget. Then it moves on.&lt;/p&gt;</description></item></channel></rss>