A better way to interview

What's up, everyone? This is Alex, the host of Founders Journal. As you may know, I built Morning Brew from my senior year of college until we sold the business in 2020. And now I'm building a variety of businesses in different spaces and different stages. I'm basically averaging 1 to 2 new businesses per year. And because of that, I have had the opportunity to test a ton of different products and services, ultimately landing on a core software stack that serves as my business operating system whenever I start a new company. I have my go-to banking service. I have my go-to formation service. I have my go-to domain hosting service. But probably the most important of them all is my HR service, Gusto. If you're a longtime Founders Journal listener, you know how much I think about people in the context of business. A business is nothing without its people, which means a platform that helps me manage and take care of my people is invaluable. And that means I've tried every HR platform under the sun, always with the same exact goals in mind. First, I want a product that's intuitive and delightful to use. As a non-HR person, I find the intricacies of payroll, benefits, taxes, compliance, and expenses to be painful. So I just want something that makes my life easier. Second, I want it to be affordable.

I'm a bootstrapper at heart.

I started Morning Brew with $0 and I started StoryArc with $0 as well, which means I don't have infinite dollars to drop on SaaS products. And third, I want a platform that acts as my one-stop shop for all things people. I want it to handle payroll, benefits, hiring, onboarding, and taxes, all while integrating with all of the other tools in my business stack, whether it be QuickBooks, Slack, or Google Workspace. Well, Gusto hit the trifecta, which is why I am a customer and use it for every single one of my businesses. Yes, this is a paid sponsorship by the amazing team at Gusto, but I would sing their praises even if I wasn't being paid to do so. So if you're looking for a platform that takes the pain out of payroll, benefits, and HR, I highly recommend you check out Gusto. And if you sign up at gusto.com/alex, you will get your first 3 Now onto the episode.

What's up everyone? This is Alex Lieberman and this is Founders Journal. For those who are longtime Founders Journal listeners, welcome back. For those who are new to the show, here's the deal. Founders Journal is my audio diary made public for the world. My goal is to increase your odds of success as an entrepreneur by sharing the stories, lessons, and tactics that I experience as I build my businesses. You can expect the podcast Monday and Wednesday with episodes that are under 20 minutes in length. And if you want to get notified when a new episode drops, episode comes out, make sure to subscribe wherever you listen. Today on the podcast, I'm talking about a better process for hiring and interviewing. I'm here in Hoboken, New Jersey with my dog Rambo, and so we're ready to do it. Let's hop in. So I had this thought today ahead of interviewing a bunch of engineering candidates for my new business that I feel like I'm actually pretty mediocre at hiring, even though I've hired and interviewed, I don't know, dozens to hundreds of people. I don't know the exact number. I actually just don't feel like I've improved all that much over time. And I started thinking about why is it that I don't think I'm that great at hiring and interviewing, even though it's arguably the most important thing you do in a business because your people are the most important component of your business. And as I thought about it, I think there's 2 things that come to mind. One is I largely don't have a standard process for interviewing. You know, I would say the most process that I have is like doing research on a candidate before writing down questions and asking those questions. But that is like the furthest that I'll go in terms of having a process. And then I also think because of that, because I don't have this standardized process, I often am too emotional. and not objective about my perception of a candidate. And oftentimes that emotion is really driven by just like, how well do I connect with this person? How well do we hit it off? Like, could I see them being a friend outside of work? And, and I would argue that is important. You know, you're going to spend a ton of time working with anyone you hire, but that can't be the only way that you're evaluating a candidate. And so basically I started asking myself, If I wanted to be less emotional about this process, if I wanted to have a more standardized way for interviewing candidates for a role, how would I go about it? What would the step-by-step be? And so what I'm going to walk you through is a process that literally I built out this morning ahead of interviewing a lot of these engineering candidates. I'm going to test it for the first time over the next few days. And so unclear if it's going to work, but I think there are a lot of things that you'll find interesting that you may want to take and apply to your own interview process. And then on an upcoming Founders Journal episode, what I'll do is just if it works, share more about what I learned through this process and I'll kind of give you access to kind of any of the frameworks or prompts or templates that I use to put this together. So here's the process I'm testing. First, I want to be crystal clear about what I am trying to get out of every single interview that I'm conducting. And so I basically wrote down 3 questions that I need answers to by the end of a 30-minute interview with any of these engineering candidates for my new business. The first question is, are they right for the role? Meaning, you know, you think about a job description that has the bullets of what is needed to succeed in the role. Are they actually going to succeed on those bullets? So are they right for the role is the first question I need an answer to. The second is, are they right for the company? And that basically is said differently. Do they embody the core values of the business? And then the third question is, are they right for me? And that goes more into like the emotional decision-making piece and like, am I willing to spend 12 hours a day with them for the next several years? So those are the 3 questions. Are they right for the role? Are they right for the company? And are they right for me? Second step, I want to plan out interview questions that map to the questions that I just shared to you. So basically, are they right for the role? There are certain traits that we need in an engineer at my new company, 10x, and I need to have questions mapped to each of those traits so I know whether the answer is yes or no. Are they right for the company? We have 7 core values as a company, and so then I should have at least one question in the interview process that is mapped to each one of the core values. And then are they right for me? What are questions that will reveal to me whether I'm going to get along with this person? So that's kind of how I'm thinking about planning out interview questions that map to each of these macro questions. Third, I want to ask each of these questions to every candidate so that every candidate can be compared apples to apples. This is a really important point that I want to make because at least for me, whenever I've gone about a recruiting process and interviewed candidates, I do not think I have ever standardized an interview in the sense of asking every candidate the exact same questions. And it sounds obvious when I say it, but how can I compare every candidate if I'm not putting them on a level playing field to respond to the same prompts that I'm giving them? So basically, I'm going to have an interview, basically like an interview rubric, and the same questions will be asked of every one of these engineering candidates. The 4th part, and I think this is probably the coolest part of the process and where I think really interesting learnings will happen. 4th step, I want to leverage AI to help me be less emotional and more organized with the interview process. So to implement AI into this whole thing, I started by prompting ChatGPT to create an interview rubric for me, and I'm going to read off what the exact prompt is. I'm not going to go through the whole thing because I literally go through like trait by trait under are they the right person for the role and core value by core value under are they the right person for the company? But I'll give you enough of the context of the prompt so that you could create this yourself for your company. This is the prompt I said. Can you create an interview rubric for me that can be filled in after talking to job candidates? The rubric should have a row for each of the attributes that we're looking for in our candidates, and then there should be a column where a grade that is yes, no, or unsure is assigned to each attribute based on the candidate's answers to the interview questions. I will be going through a list of interview questions that map to each one of the attributes. I will also share below what I will be looking looking for in the answers to these interview questions so that if I give you the interview transcript and ask you to grade the rubric yourself, you have some guidelines. See below. And so I'll just give you one example of a trait that I gave to ChatGPT in this prompt, how I shared what I'm looking for. And just imagine that I did this for every core value in our business and every trait that is required for them to succeed in the role. Trait number 1, technical prowess. The question that is mapped to it: explain a technical concept to me that you think is super important to understand. Do it as clearly and understandably as possible, knowing that I am not technical. And then I wrote what I'm looking for. How good is the candidate at understanding my level of technical knowledge? And then how clearly and simply can they explain a concept in a way that someone who isn't an engineer can understand? Basically, I'm seeing how good of a teacher they can be because because a sign that you understand something deeply is if you can explain it clearly to someone else. So that is step 1 in leveraging AI for the standardized interview process, is having ChatGPT create an interview rubric that has a list of all of the traits that we are assessing the engineering candidates on, a column where I can put yes, no, or unsure, basically the 3 possible grades after they've answered the question. And then I've included in the prompt, not just the interview questions that are mapped to each trait, but also what I am looking for in their answers that will signal whether it will be a yes, a no, or an unsure on that attribute. And I gave that information so that when I asked ChatGPT to actually grade the rubric itself, once I feed it the transcript from the interview, it will have kind of like a grading system for doing so. The next step in this process, and I actually still have to do this, is I'm going to create a spreadsheet or an Airtable sheet that will basically use this rubric, this interview rubric, as a template, and 3 things will happen in this template. I, Alex, will be able to grade each candidate on each of the traits that I'm looking for right after the interview is done. My co-founder Arman will be able to grade the candidate on all the traits he's looking for after he talks to them. And then what I'm going to do is I'm going to create an automation where the transcript from my interviews is automatically fed into ChatGPT, and then ChatGPT will score the candidate on each of the attributes based on the scoring guide that it created using the what am I looking for description that I added below each interview question. And by doing this, my hope is I'll be able to identify discrepancies in how I'm evaluating talent. And more specifically, if there is a discrepancy, I will be able to then have a conversation with ChatGPT to ask it what it heard, what key quotes it pulled out, what it specifically identified in the interview that caused it to score the candidate differently. on any of the traits than what I had done or what Arman had done. And my hope in bringing AI into this process and giving it a system for evaluating candidates is it will stop me from having to rely on my imperfect memories of how the interview went down. And also it will remove kind of any lingering emotions that are still hanging around from the call and having an impact on how I'm evaluating a candidate. And so, like I said, I'm putting this process to the test today. So I'll end up doing a follow-up episode at some point, sharing any learnings that I found, if it was helpful, and if it ended up being helpful, I'll share kind of the workflow, the exact prompts I used, and anything else that would allow you to run this process within your business. If I don't do a follow-up Founders Journal episode on this, you can just assume that this was not a good use of time. It was a fun AI test and I scrapped it. But I have a feeling that there's going to be value here. So stay tuned. That is it for today's Founders Journal. As always, thank you so much for listening to the podcast. If you want to say what's up, just shoot me an email at alex@storyarb.com. If you have any ideas for future episodes you want me to cover, make sure to let me know as well. But again, thanks so much, and I'll catch you next episode.