AI Foundations: How to Build Effective Prompts

Prompt engineering was supposed to be the essential new skill. It was not. Where prompts still matter is work you repeat and need right every time.

Jed Mahrle sat down with Kyle Vamvouris, founder and CEO of SalesThread, for part five of the AI Foundations series. Kyle's read on why the hype cooled: the models got very good, and the harness built around them got good enough to absorb sloppy prompting.

So when is a real prompt worth writing?

Only for repeatable work. Kyle's test is to ask what task needs the output right every single time. For one-offs, a sentence or two is fine. He also notes a prompt and a skill are close to the same thing, a skill usually having a prompt at its base.

Stop telling it not to hallucinate

Kyle's most useful reframe. The entire output is a hallucination. There is no mechanical difference between a hallucination and a correct answer, because the model has no concept of either, so "do not hallucinate" does nothing.

His model for why prompt quality still matters: every possible output already exists in the training data, and your prompt selects a region of that space. A vague prompt gets you roughly eighty percent of what you wanted. A refined prompt makes your ideal output one of the candidates the model can pick.

The three parts of a strong prompt

Objective. Give step-by-step instructions, and Kyle's bar is whether a junior colleague could follow them and do a decent job. Focus on the sequence of actions required, and be specific.

Data. Only give it the context it actually needs. Kyle is blunt that more context being better is backwards, which is why the field moved to context engineering. Specify the output structure or you get thirty pages. And include examples of the input, not just the ideal output, so it can pattern match.

Design. He cites the Lost in the Middle research on models prioritising the top and bottom of the context window while instructions in the middle get missed. So put the important things first and last. His structure: objective, rules, steps, examples, output format.

Prompts should be written by leaders and handed to the team