<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Planning on Fernando Ruiz</title><link>https://www.fernandoux.com/tags/planning/</link><description>Recent content in Planning on Fernando Ruiz</description><generator>Hugo</generator><language>en-us</language><atom:link href="https://www.fernandoux.com/tags/planning/index.xml" rel="self" type="application/rss+xml"/><item><title>How to Build an AI Roadmap That Survives the Next Model</title><link>https://www.fernandoux.com/en/wiki/ai/ai-roadmap/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://www.fernandoux.com/en/wiki/ai/ai-roadmap/</guid><description>&lt;div class="info-panel"&gt;
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 &lt;span class="info-panel-label"&gt;Quick Definition&lt;/span&gt;
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 An &lt;strong&gt;AI roadmap&lt;/strong&gt; is a product plan that separates what is committed to with dates (concrete features in the near term) from what is committed to with outcomes (user problems in the long term), because the capabilities of models change in months. Its goal is that a new model version doesn&amp;rsquo;t make the whole plan obsolete.
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&lt;h2 id="why-does-a-traditional-roadmap-fail-with-ai"&gt;Why does a traditional roadmap fail with AI?&lt;/h2&gt;
&lt;p&gt;A twelve-month roadmap of features and dates assumes the underlying technology stands still. With AI it doesn&amp;rsquo;t. Pmtoolkit sums it up this way: a single model release can invalidate a twelve-month feature roadmap. Something deferred because the model was unreliable can become trivial months later, and a feature committed to with a date can stop being needed without anyone deciding so.&lt;/p&gt;</description></item></channel></rss>