AI In UX: Achieve More With Less<\/h1>\nPaul Boag<\/address>\n 2025-10-17T08:00:00+00:00
\n 2025-10-23T20:33:09+00:00
\n <\/header>\n
I have made a lot of mistakes with AI over the past couple of years. I have wasted hours trying to get it to do things it simply cannot do. I have fed it terrible prompts and received terrible output. And I have definitely spent more time fighting with it than I care to admit.<\/p>\n
But I have also discovered that when you stop treating AI like magic and start treating it like what it actually is (a very enthusiastic intern with zero life experience), things start to make more sense.<\/p>\n
Let me share what I have learned from working with AI on real client projects across user research, design, development, and content creation.<\/p>\n
How To Work With AI<\/h2>\n
Here is the mental model that has been most helpful for me. Treat AI like an intern with zero experience<\/strong>.<\/p>\nAn intern fresh out of university has lots of enthusiasm and qualifications, but no real-world experience. You would not trust them to do anything unsupervised. You would explain tasks in detail. You would expect to review their work multiple times. You would give feedback and ask them to try again.<\/p>\n
This is exactly how you should work with AI.<\/p>\n
The Basics Of Prompting<\/h3>\n
I am not going to pretend to be an expert. I have just spent way too much time playing with this stuff because I like anything shiny and new. But here is what works for me.<\/p>\n
\n- Define the role.<\/strong>
\nStart with something like \u201cAct as a user researcher\u201d<\/em> or \u201cAct as a copywriter.\u201d<\/em> This gives the AI context for how to respond.<\/li>\n- Break it into steps.<\/strong>
\nDo not just say \u201cAnalyze these interview transcripts.\u201d<\/em> Instead, say \u201cI want you to complete the following steps. One, identify recurring themes. Two, look for questions users are trying to answer. Three, note any objections that come up. Four, output a summary of each.\u201d<\/em><\/li>\n- Define success.<\/strong>
\nTell it what good looks like. \u201cI am looking for a report that gives a clear indication of recurring themes and questions in a format I can send to stakeholders. Do not use research terminology because they will not understand it.\u201d<\/em><\/li>\n- Make it think.<\/strong>
\nTell it to think deeply about its approach before responding. Get it to create a way to test for success (known as a rubric) and iterate on its work until it passes that test.<\/li>\n<\/ul>\nHere is a real prompt I use for online research:<\/p>\n
Act as a user researcher. I would like you to carry out deep research online into [brand name]. In particular, I would like you to focus on what people are saying about the brand, what the overall sentiment is, what questions people have, and what objections people mention. The goal is to create a detailed report that helps me better understand the brand perception.<\/p>\n
Think deeply about your approach before carrying out the research. Create a rubric for the report to ensure it is as useful as possible. Keep iterating until the report scores extremely high on the rubric. Only then, output the report.<\/p><\/blockquote>\n
That second paragraph (the bit about thinking deeply and creating a rubric), I basically copy and paste into everything now. It is a universal way to get better output.<\/p>\n
Learn When To Trust It<\/h3>\n
You should never fully trust AI. Just like you would never fully trust an intern you have only just met.<\/p>\n
To begin with, double-check absolutely everything. Over time, you will get a sense of when it is losing its way. You will spot the patterns. You will know when to start a fresh conversation because the current one has gone off the rails.<\/p>\n
But even after months of working with it daily, I still check its work. I still challenge it. I still make it cite sources<\/strong> and explain its reasoning<\/strong>.<\/p>\nThe key is that even with all that checking, it is still faster than doing it yourself. Much faster.<\/p>\n
\n
\n 2025-10-23T20:33:09+00:00
\n <\/header>\n
An intern fresh out of university has lots of enthusiasm and qualifications, but no real-world experience. You would not trust them to do anything unsupervised. You would explain tasks in detail. You would expect to review their work multiple times. You would give feedback and ask them to try again.<\/p>\n
This is exactly how you should work with AI.<\/p>\n
The Basics Of Prompting<\/h3>\n
I am not going to pretend to be an expert. I have just spent way too much time playing with this stuff because I like anything shiny and new. But here is what works for me.<\/p>\n
- \n
- Define the role.<\/strong>
\nStart with something like \u201cAct as a user researcher\u201d<\/em> or \u201cAct as a copywriter.\u201d<\/em> This gives the AI context for how to respond.<\/li>\n- Break it into steps.<\/strong>
\nDo not just say \u201cAnalyze these interview transcripts.\u201d<\/em> Instead, say \u201cI want you to complete the following steps. One, identify recurring themes. Two, look for questions users are trying to answer. Three, note any objections that come up. Four, output a summary of each.\u201d<\/em><\/li>\n- Define success.<\/strong>
\nTell it what good looks like. \u201cI am looking for a report that gives a clear indication of recurring themes and questions in a format I can send to stakeholders. Do not use research terminology because they will not understand it.\u201d<\/em><\/li>\n- Make it think.<\/strong>
\nTell it to think deeply about its approach before responding. Get it to create a way to test for success (known as a rubric) and iterate on its work until it passes that test.<\/li>\n<\/ul>\nHere is a real prompt I use for online research:<\/p>\n
Act as a user researcher. I would like you to carry out deep research online into [brand name]. In particular, I would like you to focus on what people are saying about the brand, what the overall sentiment is, what questions people have, and what objections people mention. The goal is to create a detailed report that helps me better understand the brand perception.<\/p>\n
Think deeply about your approach before carrying out the research. Create a rubric for the report to ensure it is as useful as possible. Keep iterating until the report scores extremely high on the rubric. Only then, output the report.<\/p><\/blockquote>\n
That second paragraph (the bit about thinking deeply and creating a rubric), I basically copy and paste into everything now. It is a universal way to get better output.<\/p>\n
Learn When To Trust It<\/h3>\n
You should never fully trust AI. Just like you would never fully trust an intern you have only just met.<\/p>\n
To begin with, double-check absolutely everything. Over time, you will get a sense of when it is losing its way. You will spot the patterns. You will know when to start a fresh conversation because the current one has gone off the rails.<\/p>\n
But even after months of working with it daily, I still check its work. I still challenge it. I still make it cite sources<\/strong> and explain its reasoning<\/strong>.<\/p>\n
The key is that even with all that checking, it is still faster than doing it yourself. Much faster.<\/p>\n
\n - Break it into steps.<\/strong>