Example of an AI CV

[00:00 - 00:14] Just as a kind of a demonstration, I'm going to take a job description, one that I took from LinkedIn the other day, and I'm going to use AI to generate a CV for it. And I'm gonna go through what it does well, what it does badly.

[00:15 - 00:22] Again, I'm not advocating for this. It is going to write a very good CV for a fictional person, maybe with summations, but we'll get to that.

[00:23 - 00:30] First, let's look at the job description. So this was a job posted several days ago on LinkedIn, based in Dublin.

[00:31 - 00:42] I picked it because it seemed pretty generic, possibly written by AI. Oh yeah, you have a really simple introduction here, asking for a senior QA engineering role.

[00:43 - 01:02] It's talking in very general terms about what the senior automation QA engineer does. We have again, the responsibilities are exactly what you'd expect to find and implement the automation testing frameworks, review scripts, talking about CI/CD integration.

[01:03 - 01:14] That's a pretty big part of your day-to-day if you're an automation engineer. And yeah, some of the other stuff, that's a little bit boilerplate, which does make me think this was maybe written with AI.

[01:15 - 01:23] Established best practice evaluates, maintains support the other. And here we talk about the minimum requirements.

[01:24 - 01:40] This is where the bulk of your keywords are going to come from, but it's very good to check between these two and see which keywords appear in both places, and those kind of weights them. Yeah, lastly for five years, automation experience.

[01:41 - 01:47] We have some technologies here, cypress Selenium, or web UI automation. We have some coding languages.

[01:48 - 02:03] We have some kind of boilerplate about scalable automation frameworks. And on account, we have CI/CD mentioned, and on some specific tools like Jenkins GitLab, GitHub Actions, et cetera.

[02:04 - 02:11] Yeah, API integration, microservices. And then it's got a little bit of, usually this is called Nice to Have.

[02:12 - 02:21] This one is actually pretty generic, except for the need for another European language being Nice to Have. So this stuff is generic, right?

[02:22 - 02:30] Work on multiple deadlines, highly motivated. All right, so I've already pasted the job description in here.

[02:31 - 02:44] I'm just going to use our generator CV just to show you what it does well and what it does badly. So draft them ideal CV for John Hireman for the job description that we just talked about.

[02:45 - 02:59] I'm probably going to pay particular attention to the selection criteria, highlight important keywords and list that was an indebted to the CV. So that just means that at the end, we're going to get a list of the keywords that were used in crafting the CV.

[03:00 - 03:11] Let's see how good, how well it does. And bear in mind, I said an ideal CV.

[03:12 - 03:24] So you have your basic structure. It does take into account the remote in the location, but obviously everything here is fictional.

[03:25 - 03:36] These links are not going to go to anywhere or they're going to go to an arbitrary person that actually exists and would not consent to be reached out to. So make sure that all of these are real.

[03:37 - 03:46] This section feels a little bit superfluous. I would often mix this with the title, but maybe this will parse better.

[03:47 - 03:51] I don't know. I think that's just a preference thing. Let's look at the overall structure actually first.

[03:52 - 04:00] So we have a professional summary. We have a poor competencies, professional experience, education certifications and then tools and technologies, right?

[04:01 - 04:07] You've got a nice little table here. And it does mention languages here at the bottom.

[04:08 - 04:19] We have all of the keywords and obviously it put all of them into the CV. Yeah, they seem to roughly come in the order that they appear in the job description.

[04:20 - 04:26] Some of it is the kind of very obvious and implicit curail or machine experience. Obviously that is the number one thing.

[04:27 - 04:34] Automation testing framework. You have your surface, your Selenium JavaScript, JavaScript Python, all of that.

[04:35 - 04:45] So you can see that the structure is pretty predictable, right? This thing is maybe not something I would put in a separate section.

[04:46 - 04:55] Yeah, so be careful with the assets that you're getting reviewed very correctly . Immigam really remembered that this is going, this is for a fictional person.

[04:56 - 05:00] If you're doing it for you, it is going to get things wrong. It is going to miss contextual things.

[05:01 - 05:10] This part with the professional summary, lots of paragraph. This is one that in particular bears a lot of human intervention, right?

[05:11 - 05:24] Because this sounds very generic. Okay, it hits some of the keywords and it is important to include the keywords in this section, as well as in your professional experience, right?

[05:25 - 05:39] Because as we discussed, summarizes are going to pick up on stuff that's embedded in sentences quite well. And having it multiple times reinforces both about the machine translation level and for a human reader that will potentially read this.

[05:40 - 05:57] So yeah, we're testing, we're hitting a lot of the keywords there, but this is a little bit bland. One thing that you could do and that in AI is definitely not going to be able to do is to brag about a project that was very high impact that you've worked on, especially if you led a project.

[05:58 - 06:06] I like to work that into this section somehow. I think that'll make you stand out, especially for a, especially once it gets to a hiring manager.

[06:07 - 06:17] Okay, so you have your core competencies, your professional experience. Now there's a bit of overlap between core competencies and tools and technologies.

[06:18 - 06:26] I'm not always a fan of how LMS will do this and will delineate this. So there's some kind of repetition redundancy here.

[06:27 - 06:42] So I would consider potentially molding those two together. Because yeah, there is some kind of redundancy there and you are limited by page camp, right?

[06:43 - 06:55] Some of these also don't super embed well together, but anyway, let's look at the professional experience. This is the part that I think is the most useful for templating.

[06:56 - 07:01] And it's also the part where you're going to get the most value for money. I think if you're using AI review tool.

[07:02 - 07:12] So let's look at, okay, obviously completely fictitious jobs, completely fictitious examples. Spearheaded the design and implementation of moderately reusable automation framework in Cyprus with that script.

[07:13 - 07:17] Reducing maintenance by 4.0 percent. Okay. So we have a strong verb.

[07:18 - 07:25] We have keywords. And we have something quantifiable in my issue.

[07:26 - 07:30] Right. If you look through all of them are probably going to be like this migrated legacy Selenium.

[07:31 - 07:32] Yeah. Keywords.

[07:33 - 07:44] Reduced execution time, test reliability. And you'll also notice that these, there's not really much reuse of the verbs here.

[07:45 - 07:49] Right. So it's usually it's not using the same strong verb twice.

[07:50 - 08:20] And again, it can be really difficult to pull examples from your own, from your own experience, especially if you like, if you know you did something that was a strong example, because it was years ago, because you don't have those quantifiable metrics, that's kind of difficult context, but when I eyes, maybe not going to be able to produce. That's where it's going to be weak.

[08:21 - 08:45] I don't think a lot of these percentages being given are particularly realistic , for example, for this, again, very fictitious person that does not exist. So that's something to be aware of. You'll also notice that as we go back in time towards more junior positions, these things get less detailed and a little bit less quantifiable and there's less bullets as well.

[08:46 - 08:56] I think that's actually a pretty good format to follow personally. Because obviously your most recent experience is going to be hopefully the most relevant to the role you're applying for.

[08:57 - 09:10] And it's not at the very least going to show you the stage of your career where you've had the most growth and you have the most come. So you just write, so you want to show higher responsibilities and your scope has expanded over the years and this is a good way to do that.

[09:11 - 09:34] Yeah, education certifications certifications definitely do not let AI generate this for very obvious reasons. This is not a real thing. AWS certs, I'm not sure if this is even using the right title, but you can link to the actual form of all title of the AWS cert and includes the year you got it, right?

[09:35 - 09:52] Yeah, I do this little, this little table. There is doing this more than once or actually giving an existing CV to whatever tool you're using and asking it to just loosen up, but again, be very careful.

[09:53 - 10:09] I hope this kind of case study has showed you what AI does well, where you can use it to improve your chances and where does not. It's hard to see how bad does on context unless you try and actually do it for yourself.

[10:10 - 10:15] If you do that, generally you'll see that it's you'll see where it's lacking.