<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Prompt Engineering on Daniel Doezema's Blog</title><link>https://dan.doezema.com/tags/prompt-engineering/</link><description>Recent content in Prompt Engineering on Daniel Doezema's Blog</description><generator>Hugo</generator><language>en-US</language><copyright>&amp;copy; 2024 Daniel Doezema</copyright><lastBuildDate>Wed, 01 Jul 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://dan.doezema.com/tags/prompt-engineering/index.xml" rel="self" type="application/rss+xml"/><item><title>Illocutionary Force In Prompt Engineering</title><link>https://dan.doezema.com/2026/07/illocutionary-force-in-prompt-engineering/</link><pubDate>Wed, 01 Jul 2026 00:00:00 +0000</pubDate><guid>https://dan.doezema.com/2026/07/illocutionary-force-in-prompt-engineering/</guid><description>&lt;p&gt;While working with early GitHub Copilot I would use a lot of short utterances. (e.g., &amp;ldquo;can we do that?&amp;rdquo; or &amp;ldquo;That&amp;rsquo;s not right.&amp;rdquo;) I found that the model often would ignore the context of the conversation and answer in an overly literal way. I then would be forced to undo any changes and re-prompt with a more explicit request.&lt;/p&gt;
&lt;p&gt;Wanting to fix this problem, I thought &amp;ldquo;Why is it that a colleague and I can rapid fire debug an issue (using only a few words) while fully understanding each other? How do humans pick up on intent so naturally?&lt;/p&gt;</description></item></channel></rss>