Meeting Title: Brainforge Interview w- Demilade Date: 2026-03-13 Meeting participants: Chadd McNicholas, Demilade Agboola
Demilade Agboola: Hi, Chad. Chadd McNicholas: Hello? Demilade Agboola: Hi, how are you? Chadd McNicholas: I’m going good, how about yourself? Demilade Agboola: I am doing very well. Glad to be able to… Have this call with you, and just, like, get… An idea of how, like, you think, and how you work, and how, We’re able to, like, fit together. So this will largely just be, like, a technical system design sort of interview. I just want to understand how you process things, and how you… Chadd McNicholas: Oh, okay. Demilade Agboola: you know, kind of, like, evaluate systems, so, like, there’s no, like, live coding or anything, it’s just, like… Chadd McNicholas: so I don’t need to worry about window functions and CTEs and all that stuff then. Okay. Fair enough, or recursion and… Demilade Agboola: Okay. Okay, sounds good. So, first things first, I mean, I know you had a call with Echoish. I would just like to have an idea of, like, your background, and what you’ve worked on in the past, and then from there, we can kind of talk about scenarios. And how you would handle those scenarios. Chadd McNicholas: Okay, sure. Yeah, a quick background on me. I have a very long, diverse career, to get to where I am today. But I started out in electrical engineering, quickly transitioned into analytics, and, kind of data infrastructure management, and then went to a startup where I was the entire BI department, and then became a solutions architect at Tableau Software, building out entire BI deployments for companies. And then, was an analytics engineer for General Motors, doing, data pipelines, mostly prototypical, but we’re talking multi-trillion record data sets and, entirely on HDFS, and then building pipelines from that out to the reporting layer, based on various, needs of my internal customers. And then, And then finally, Indeed, as our 6 years, definitely a player coach. I was less hands-on than I was at, like, at General Motors’ previous jobs, because I was a senior manager, so I was managing a team that did a lot of the work, but I was still very hands-on and helping to provide direction and prototyping. But, there, I… it was more of a strategic role, kind of driving the, Driving a data-driven culture at the company, trying to democratize analytics for everyone, as opposed to letting a centralized team do all that analyt… analytics for everybody. Onboarded multiple orgs, got the entire company onboarded. 95% of the company was using the platform when I was done, with 70% of them being monthly active users, and this was up from 20% when I got there. Did two major, migrations, one was from on-prem. Excuse me. an on-prem data center in Texas to AWS, and then later on, Tableau Server, which is a self-hosted, platform to Tableau Cloud, which is their Salesforce’s, SaaS, solution, which was… and I drove that end-to-end, that was a 10-month, migration project, extensive communication, Working with, networking, security, legal, even, and then also, senior leadership of the different verticals, along with end users, so, and then, you know, sprint planning, cohorts, and so on. Demilade Agboola: Yeah. Chadd McNicholas: And did a lot of… I also did a lot… I did… I did do analytics-wise there, mostly to assist teams with their work as, like, a mentor or coach, but also doing, extensive analytics on the platform itself for, like, license management, improving, user workflows, and stuff like that. Demilade Agboola: Okay, just out of curiosity, like, where would you say your, like, strongest, areas will be? Would you be, like, AE, being an analyst, or would it just be, like, an intersection of that? Chadd McNicholas: I’m really a jack-of-all-trades. When I get into it… Demilade Agboola: I hope. Chadd McNicholas: What? Demilade Agboola: I said, master of all, I hope. Chadd McNicholas: Yeah, that’s right. Not a master of… no, no, no. I very quickly adapt to, like, the work I’m doing, so, like, if you ask me to write a Python script right now, I’d be like, but tomorrow I’d be right back to where I was, you know, a year ago. But, like, analytics in general, just, looking at data, identifying problems, and, data cleansing, and… just taking a step back and just looking at what the big problem is, and boiling that down to what needs to get done. Understanding customer use cases specifically, because when a customer asks for something, that’s not necessarily what they need. So you have to seek to understand what they actually need, and then building a solution that would actually benefit from them, versus what they just specifically asked for. So I’d say that’s my specialties, there. Demilade Agboola: Okay. Chadd McNicholas: Yeah. Demilade Agboola: Alright, that’s fair. Chadd McNicholas: But yes, definitely a lot of analytics, it, it, yeah, it’s just sometimes, particularly my most recent role, it’s been, less frequent, but I love, I love doing it. It’s a lot of fun diving into data. Demilade Agboola: Fair enough, fair enough. Don’t worry, like, I relate to that as well, because I really love, like, just the entire process, and… I personally… that’s one of my favorite parts of, like, just the entire thing, is, like, being able to put together… understand the problem and put together, like, solutions towards that problem, and there’s that feeling of satisfaction when you see the end result. Alright, so let’s kind of join some, like, high-level, like, architecture. design. Chadd McNicholas: Okay. Demilade Agboola: So, it’ll probably be nothing too crazy, just if a client wanted to integrate… Stripe. Google Analytics, and Salesforce. how would you… and they wanted to have, like, a daily, like, revenue reporting, you know, marked. How would you go about designing that, or what would you… what are the things you look out for? And how would you go from just data sources to… the daily… Chadd McNicholas: Yeah, I’m wondering how detailed or reductionist I should be. At a very high level, it’s going to be just getting the data into one place. So, that’ll be, like, S3 buckets, Hadoop, probably not Hadoop, because we’re not talking big data… well, Stripe could get really big. Even Google Analytics can. No, Google Analytics is already kind of aggregated, but Stripe definitely can get big. But let’s just say, let’s just say S3 buckets or something. Just get the data in there, and… we use, I don’t know, like, Fivetran or something. I know a lot of companies build their own solutions, just working with APIs directly, because they have their own sometimes, Fivetran, for example, doesn’t have exactly what you need, so you’re better off just building your own. So just get everything into buckets, and then I would go through, Understanding what the, analytic and reporting needs are of with the data, so what questions are you trying to answer? I mean, some of them are obviously going to be obvious, so, I mean, like, you know, lifetime value, first, Was it time to first, revenue, for customers, churn, probably, you’ll get, like, customer churn. also, if you’re doing Google Analytics, you’ll probably be looking at, like, funnel. analytics. Also, Salesforce, obviously, is, you know, lead generation to funnel, also. So, get the relevant, assets into… so, okay, so we have everything… relevant assets into just… into buckets, and then, I would… then I would use something like dbt or Databricks or something to start building out my layers. Start with a bronze layer, just basically ingesting the data, just get everything into appropriate table forms. And then I do, like, the silver, and then gold, and then… maybe a Platinum, but probably not. Demilade Agboola: Okay. Chadd McNicholas: Yeah, I just, I don’t know, there’s that… Demilade Agboola: I mean, how… yeah, that’s pretty good. I think what I’ll… another… area, like, maybe we could just go in… To, like, the technical considerations you might do, especially for, like, the ingestion. Are there any things you’ll be, you know, wary about, or you’ll be looking out for, in terms of that? Like, honesty answer is pretty good. I’m just trying to see, like. Chadd McNicholas: Oh, yeah, yeah, yeah, totally. Demilade Agboola: Those technical concentrations will be for that data. Chadd McNicholas: Obviously, there’ll be API limits and whatnot with the vendor sources that we’d have to be cognizant of. Also, from… A lot of my experience with working with vendor APIs is the data. are generally bad. I think… I think, like, Google Analytics… I think these three sources are probably really good data, but, like, when you start working with, like, Slack, or Workday, or, what’s the other one we had that was really bad? That doesn’t matter, but it’s like, if you don’t have pro… if you test your data and don’t have problems, you’re like, wow, this is amazing, but normally you have to have all these contingencies in your ELT code. So, definitely that… so we got, just, watching for limits, ensuring, we have, clean, good data coming in, or subsequent, scrubbing done necessary. What else? I’m talking… okay, let’s keep a… are you talking about getting into security and governance, too, or is that aside for now? Demilade Agboola: I mean, you could also think of that, like, it’s not, again, the idea of this is just to get an idea of how you think. Chadd McNicholas: Okay. Demilade Agboola: wherever direction you want to take it, I just want to understand how, like, you process the data. what your considerations are. So this really is sort of open-ended. Chadd McNicholas: Okay. Demilade Agboola: I truly kind of understand, okay, so do you, like… so now if you say security and governance, I understand your considerations around that. Chadd McNicholas: Yeah. Demilade Agboola: tell me stuff around, like, you know, API limit handling, I would get an idea of how you handle that. If you’re telling me, like, oh, batch versus streaming, I get an idea of how you, like. Chadd McNicholas: Okay. Demilade Agboola: It just gives me a context of how you, as a person, are designing architecting systems, and what. Chadd McNicholas: Yeah. Demilade Agboola: Cooper. Chadd McNicholas: Okay, well… Demilade Agboola: Depends. Chadd McNicholas: See, you did mention batch versus streaming, which I didn’t bring up. I don’t think streaming would be, an integration methodology for either… any of these sources. It’s not, like, real time… I mean, Stripe might be, But I think that this would probably be batch, and also we’re not looking for real-time analytics anyway, so we don’t need to set up, like, a Kafka feed and all that. I could be wrong. But I think this would be mostly just batch. And then let’s see, what else? But, yeah, definitely once we get to, like, like, the… When we get to the gold layer, that’s when we really have to start seeing who can see what and everything, and when the silver and the bronze, it’s already gonna be a limited set of users, mostly developers. let’s see… And then when we start getting into… I don’t know, I could, like, start talking about reporting, like what we were trying to see, although I did kind of already talk about that, like, some of the KPIs and metrics that we’d probably want. that our user would probably want, that we want to build for. Let’s see… Yeah, That’s all I can think of right now. Demilade Agboola: Okay, alright, sounds good then. Alright, so, like, let’s… still within the same architecture, Would you, want to build out, like, your marks using, like, a star schema, or a normalized schema? And, like. What would you say the pros and cons, slash, when would you want to use either would be? Chadd McNicholas: So I would generally lean towards a star schema. I, I, I’ve… so I, I inherited a… horrendous snowflake schema, when I was, at Modernize, and… Demilade Agboola: Okay. Chadd McNicholas: it was so unnecessarily normalized that basic queries was just a pain in the butt, and I… over time, I gradually, condensed it down to only areas where it really needed to have bridge tables and stuff like that. I try to keep that to a minimum, really. Just keep it simple, you know? Particularly with, modern platforms, database platforms, they’re pretty well optimized. So, they’re a little more forgiving. Not saying that you should take full advantage of it, but you don’t have to be hyper-normalized, much. If you’re getting into, like, the data fabric. Realm, yeah, but most, most places are mesh, anyway. So… Trying to, trying to think, But yeah, I mean, we’re gonna say, yeah, we’re gonna have our event, you know, our main fact event tables, and we’ll have the associated dimension tables, and we’ll have SEDs on relevant ones, so we can track history. We’ll make sure we have, like, time warp and stuff in our silver layer, make sure, you know, our bronze layer is only, you know, append, and stuff like that, Yeah, I don’t know, I’m just rattling some things off, but… I mean, those are definitely considerations I would have. Demilade Agboola: Okay, that’s fair. I think the next question, so, like, off of that, so we have architecture, we have our schema. And then over time, we’ve noticed that, one of our tables has It’s blown up. And now we have a query that takes forever to run, right? Chadd McNicholas: Okay. Demilade Agboola: So, if you were to troubleshoot that query, assuming worst case scenario. What are the things you’d be looking out for, and how would you be trying to optimize this, you know, blank query? Chadd McNicholas: I’ll do a quick anecdote, and then I’ll go back to what you’re doing. So, my largest customer and most heavily used dataset at Indeed. When I say customer-employee teams, it was the BI finance team, and I fought a losing battle for many years, where they had a single denormalized table of 140 columns, and… 300 to 500 million rows, and they had their own dedicated Tableau server that they paid for to do the, extract generation. They did a full refresh every time because they couldn’t do upserts and such. Anyway… I finally… when we migrated to cloud, we couldn’t do that anymore. I actually did some things before, but when we migrated to cloud, I’m like, hey, now you have to take my advice, and we got them doing live connections on Snowflake, with, the joins and stuff ready to go, as opposed to denormalizing everything, and then they could finally do their upserts and everything. Okay, back to your question, which was, I’m sorry, what was it? So… Demilade Agboola: You have this query that’s not. Chadd McNicholas: Oh, okay, yeah. Demilade Agboola: Gotcha. How would you go about, like, what would you… what were the things you’d be looking out for to optimize this query? So, again… Chadd McNicholas: Okay, so it may not just be a big table, it may just be a bad query. Demilade Agboola: Okay. Chadd McNicholas: Fully written query, yeah, so we’re gonna look… Demilade Agboola: Sorry to interrupt, do you use dbt? Have you worked with dbt? Chadd McNicholas: I’ve taken… I’ve taken the train, I understand the concepts. I have not applied it in my professional, like, actual work. Demilade Agboola: Okay, no, that’s fine. I just wanted to… again, dbt is just basically SQL on steroids, so again, if you… if you’re comfortable with, like, SQL, dbt is not a problem. I just wanted to, like, understand… I wanted to make it a dbt use case, like, oh, if it’s a dbt, you know, model, but generally, just think of it like a SQL query. Chadd McNicholas: Yeah, no, I, no, I did actually take, like, the foundational course in DBT. It’s a tool, not a practice, you know? It just… it enables you to do your work better. So, I would look so obvious, our appropriate indexing on the tables that are being queried, and relationship definitions. I would, ensure that we’re applying appropriate filters and aggregations early in the query. I would… Let’s see, yeah, favor window functions, Where necessary, as opposed to, like, self-joins. And, what else? Also, yeah, and then also when it comes to that, if it’s a big table, if we need to go back… so if the query itself is fine, we’ve done everything we could do, we could go back and, to the table and say, okay, is this trying to boil the ocean, or should this be broken apart, and such that the queries are only grabbing the data they need, as opposed to querying this entire table with, like, perhaps, you know, fields with horrible cardinality or something. Yeah, and then, you know, make sure that the… well, if you’re in, like, Snowflake or BigQuery, you’re already in a calmer data store anyway, but if you’re in, like, you know, Maria or MySQL or something, you may actually explicitly have to define it accordingly. So there are definitely optimizations in that realm, too. Also, making sure your data types are appropriately defined, yeah, things like that. Demilade Agboola: Okay, alright, that’s fair, that’s fair. Alright, so a couple… so now we’ve built out our architecture, How do you ensure that the data quality that the client gets in their dashboard is consistently up to par? Chadd McNicholas: Now, this is where dbt is, like, awesome. It does all the testing and stuff, like, you could have it all scheduled and everything. I’ve seen, actually, a lot of people who ditched dbt and just went straight to, like, just using Airflow for all of it, too. But still, same idea. So we’d make sure that we’d be… checking that we’re getting consistent number of rows… well, actually, so Avia the first is checking for, duplicates, nulls, and stuff where we would not expect those. And then, on, like, a second order, also make sure that we’re getting, an expected, order of magnitude of rows and, that are coming in. And perhaps. optionally, start actually doing some mild aggregations to make sure that, like, for example, because you could be getting, like, sales numbers in, for example, and they’re all just coming out as zero. So, all your, like, hard data checks would say, hey, this is fine. They’re all, they’re all decimal, and they’re… and they’re not null. Demilade Agboola: Yeah. Chadd McNicholas: But you could have a gross reality check just saying, hey, it’s outside of our standard deviation, and flag that way, too. And that could actually all be done in DBT, also. What else? Yeah, because this is, like, the fun part. I mean, it’s like, once you get past this, and it’s like, the rest is just kind of boring, but once you have all the clean data, like, that’s great. What else? I just want to make sure I’m not rambling, let’s see what else, Yeah, nulls, dupes, ags, and yeah. Demilade Agboola: Okay. Chadd McNicholas: Yeah. Demilade Agboola: That’s fair. Alright, so this is, like, my final question. Chadd McNicholas: Okay. Demilade Agboola: So this… so let’s step aside from the architecture we’ve built. So right now, you’re on a client, because I’m sure… I’m sure you know what we do in Brainforge. So, you know, like, you’re on a client, the client wants… a dashboard, right? But that’s all they’re really saying, like, oh, we need this dashboard. How do you get… specific metrics? Like, how’d you go from just, like, hey… We want a dashboard to, like, this is… the dashboard that we need. And two, say you finally do finally get that, How do you handle… if they want a solution that you know doesn’t scale. Like, you’re like, hey, they need this, this is how they want it, but you’re aware that, like, this is just… this will just be a band-aid. How do you, you know, navigate those waters in terms of communicating with them? Chadd McNicholas: Yeah, so this is, yeah, this is the kind of the fun part. There’s a whole practice of not telling the customer no, which I can get into, but the first thing is, is that they said they want a dashboard, and that you go, okay, great. What, actionable insights are you trying to make with this dashboard? Let’s get those written down in plain English. As a VP of Sales, I want to, you know, we’re talking our standard, you know, project manager. you know, user stories, and let’s get those written down. It’s mundane, but it’s good. And then we’re gonna translate that into the actual, analytic logic required. So what, you know, what questions are you trying to answer? What actual insights are you gaining? So, like, what do you do when you see this? That will help us determine priority. What is the impact of these insights? And we’re going to get those as metrics in the top, you know, normally at the top of the dashboard or whatever. This will be tailored to the users, because the VP of Sales, the VP of Marketing, the CIO, and so on are all going to have different questions to ask of perhaps exactly the same data. Demilade Agboola: Yeah. Chadd McNicholas: So. make sure that we have those appropriate questions, determine if they want them in a… if we should have them in a single dashboard, multiple dashboards, and so on. As for… unrealistic requests, which never happen. I’m kidding. They, like, for example, I want to filter on every little thing in the dashboard, and I want it to be sub-second response, and it’s like, every time you change a filter, it’s going to query and change all the other filters, and then it’s going to render the dashboard, and they don’t want to hear all that, right? So, you reframe the angle, just saying, okay, but this report is going to be, counterintuitive for your other users. And then… you will have to lightly explain that, you know, all these filters will slow down the report, and you don’t tell them no. You say, is that an acceptable cost of having these features. If not, let’s perhaps, ha… excuse me, have a report, and then we can enable drill down so people can dig into it and dig into other reports from those data for much more performance. And start working out a solution that way. Demilade Agboola: Okay. Alright, that’s, that’s all, that’s all I hoped for. Chadd McNicholas: Yeah. Demilade Agboola: You have a lot of cough going on. Chadd McNicholas: It’s allergy season where I am right now. Demilade Agboola: Oh, okay. Chadd McNicholas: Where are you? Demilade Agboola: I live in Malta, where’d you stay? Chadd McNicholas: I am in Texas. Demilade Agboola: Oh, you’re Dallas, Houston… Chadd McNicholas: Austin. Demilade Agboola: Austin, okay. I actually have a friend who lives in Austin. Chadd McNicholas: Okay. Demilade Agboola: Yeah, I think Otram’s also in Austin, actually. Did you know that? Chadd McNicholas: Wait, what was that? Demilade Agboola: Bhutam is also in Austin. Chadd McNicholas: Well, Austin is the town. Demilade Agboola: Yeah. like, I know… I know Utam, our CEO, he lives in Austin, so that’s… Chadd McNicholas: Yeah, so yeah, so, yeah, yeah, I saw that he lives in Austin, but Austin, yeah, Austin is the town, but it’s like, Austin’s in the center, pretty much the center of Texas, more or less. Houston is east, and then Dallas is north. Demilade Agboola: Fair enough. Chadd McNicholas: Yeah. Cool. Demilade Agboola: Did you have Questions. Chadd McNicholas: I’ve never been to Malta, I’d have a lot of questions about that, but, I have a map up, I’m sorry. Okay, I’ve done… I’ve been… I’ve done the Mediterranean cruise, and I’ve hit a bunch of… but I didn’t, No, it ended in Rome, so it didn’t… it… we turned north before all that, before getting to Malta. Okay, yeah, my questions, Trying to find my tab, there we go. Let’s see, what, so you’ve been there a year, right? . Demilade Agboola: I’ve been here for, like, 3 years, actually. Chadd McNicholas: Oh, okay. Demilade Agboola: Yeah. Chadd McNicholas: Oh, okay, yeah, oh, were you acquired? Was your company acquired, or… Demilade Agboola: Oh, no, no, I just, so I just leave here. As a. Chadd McNicholas: Well, I mean at the company, I’m sorry. At Brain Forge. At Brain Forge. Demilade Agboola: So, Brainforge is based in, like, Otam’s the CEO, he is based in Austin. Chadd McNicholas: Yeah. Demilade Agboola: Brainforge is registered in the US. I just leave here, because we’re, like, globally distributed company, so I am here in Malta by myself, and I got… I got hired by Brainforge, like, a year ago, but I’ve been here for, like, 3 years. Chadd McNicholas: Oh, that’s what I meant. Demilade Agboola: Yeah, yeah, so that’s… that’s that, and there are people across the world, so we have people in the Philippines, we have people in Pakistan, we have people in, you know, the US, also across the US, New York, LA, Yeah. Yeah, Wish is in, Dubai, right? Oasis in Pakistan. Chadd McNicholas: Oh, Pakistan, okay. Demilade Agboola: Yeah, so I wish I was in Pakistan. So yeah, there’s a lot of, like, Hours overlapped. Chadd McNicholas: Yeah. Demilade Agboola: But yeah, most of the time, we just tend to work, like, 9 to 5. Eastern? So, most people map their hours according to that. Some, obviously, because of time zone, some people will log off a bit earlier than 5 o’clock Eastern, but just generally, yeah, most people work around those times. Chadd McNicholas: Yeah, yeah, yeah. Okay, cool. And so, like, so you’ve been there a year, you’ve probably worked with several… Demilade Agboola: I’ve been in Brain Forge a year. Chadd McNicholas: Yeah, that’s what I mean, yeah, Brainforge, exactly. Sorry for the confusion. I’m all to 3 years. No, Brainforge, you’ve been there a year. So, you’ve worked with several clients, like, what do you love about the work, perhaps compared to your other… Rolls. Demilade Agboola: What do I love about the work? I think what I love about the work is, number one, the team, the team’s pretty chill, very nice team, very supportive team. We always try to, like, be there for each other and cover for each other. That’s one. Two is also the fact that We’re driving… we’re trying to push a lot of, like, AI initiatives across the team, so people are getting, like, empowered that way. And so processes that usually used to take, like, you know, 2 days, 3 days, everyone on the team, so sales and marketing, they’re drafting SOWs in, like, 30 minutes, because now they’re using AI on the team to at least get a draft, and then proofread and, like, just tweak things around. We have an internal AI team that allows us to also build out Tools specifically for the company. you have an AI request, you’re like, hey, I feel like this process, if we’re able to have AI validate this data instead of, like, the process I would always go through every single time. That might speed up my process. The AI team puts it on their roadmap, and then they turn it off really quickly. Yeah, and because, again, it’s a smaller team, there’s also a lot of, like, flexibility. So ideas are easily heard at the very top, so it’s… if you have an idea, if you feel like, hey, I can speed up this process, or this could be a better way to go about the process, Utam and Robert are generally very open to, like, listening to that, so you can have those conversations and In, like, a week or two… in, like, a week or two. You can see, like, the changes start to happen, so there is a lot of, like, flexibility into how we do a lot of the things that we do. Chadd McNicholas: Okay, yeah, I’m… yeah, while you’re talking about that, I, I, noticed, so, Robert… Robert Tsang? Co-CEO? He’s been posting a lot about, Using AI, In your… in your company’s work. Demilade Agboola: Yes. Chadd McNicholas: Which is pretty cool. Yeah, I thought that was… because I was expecting to see a lot of, like, client this, client that, but, it’s… it looks like a lot of it’s, like, just how y’all are using AI to, like, improve your… Like, discover… like, lead generation, and discovery calls, and stuff like that, and how you’re using… I mean, that’s, like, really cool. Because when I first saw the company, I thought it was, like, how we’re using AI with your customers, which, obviously, you’d be doing, but I didn’t realize how much was going on internally, like… I mean, indeed, for example, we’re only, like, we were just barely, I mean, granted, a 13,000 person company. before the layoffs, smaller now. You know, we’re just barely getting AI, like, tools like Glean and stuff, and then as partnering with the BI folks to get AI working. But it was just, like, nothing was really concrete yet, while you guys are totally, like, doing this, this really cool stuff with, like, lead gen and, And, sales, which is… there’s just, like, one or two articles I’m looking at, and I’m sure you’re doing it everywhere else, too, but that’s really cool. Demilade Agboola: Yeah, like, trust me, I can’t, obviously cannot tell you all we do with AI, but trust me, like, we do, like, we have, like, literally have an internal AI team, and we, like. we have an AI ID- Slack channel, so, like, if you have an idea of, like, how AI could speed up your process. You’re just mentioning the team. We have, like, almost, like, everyone has, like, cursor on their, on their, like, on the team. We have ChatGPT plans, pro plans, and so the idea is we try to, like, encourage everyone to use these things. We… we want AI to be, like, one of the first steps you use. To at least speed up the process, then you review, you ensure that what it’s doing what you need it to do. And so, ultimately, that, like, allows the team to be able to have that level of flexibility, across the team. And it’s pretty cool, like, sometimes you see what people are doing with AI in the team, so we have, like, client success managers and owners. We have, like, cursor commands where we can… Integrate the messages from… messages and calls from, like, the past couple of days, and it will draft up a quick message that you would be able to use to feed the client and say, hey, this is the pro… and also integrate it with, like, our project tracking board. tickets with, like, deliverables we’ve been able to achieve, this is what you’ve asked for, like… like, just basically summarizes all of that, and you can quickly send out messages. Obviously, again, the idea is you would have to read it and just be sure, like, everything is as it should be, but, like, think of the hours you would normally… It’s to go to all these different places to get all of that together, versus, like, all of this is in one place as a message, and now you can, like, okay, delete this line, add this instead, and, like, in, like, 10 minutes, you’re done with everything. Chadd McNicholas: Yeah, yeah, that’s pretty cool. I’ve used Cursor a couple times at Indeed, I barely got my license, like, a couple months before the layoff, but someone sent me some terrible data, and I was gonna have to write a Python script to, you know, clean it, and I was just like, you know, I’m gonna try Cursor. I literally, I took the file. put it in there, and I said, here’s the input, okay, these fields are, you know, it contains these data. I want output that looks like this. Boop. And I also made it clear that it was an ad hoc script, so I didn’t… I wasn’t looking for, like, thorough documentation. And I’d say about, like, it took… Maybe 2 iterations? to get it perfect. And I wrote zero code. And it saved me probably 4 hours of Python scripting. Just like that. It was really impressive, so… Oh, I know we’re… I know we’re… we’re way past time. I want to be cognizant of your, of your time. Although, I don’t know, you work 9 to 5 Eastern, so… Demilade Agboola: Yeah, yeah. Chadd McNicholas: Even on Fridays? Demilade Agboola: Fridays, sometimes not… not fully, because, like, I’m usually 6 hours ahead of the Eastern, but because of daylight savings, 5 hours ahead. So if I was to work till 5, that would put me at 11. Chadd McNicholas: Yeah. Demilade Agboola: was throughout the… like, so sometimes on Fridays, I’m just like, 9 o’clock, I’m like, alright. Chadd McNicholas: Yeah. It was nice, see you next week. Demilade Agboola: Usually, sometimes I’ve just, like, just, like, log off early on some days, especially, like, the days I’m just tired, and I will log off early. But again, the beauty of, like, the hours difference is that I can wake up early. Earlier than everyone. And… I get the work done, it does allow me to be able to free up some of my evenings as well. So, again. Chadd McNicholas: Yeah, yeah. Demilade Agboola: Give and take. Sometimes. Chadd McNicholas: Oh, of course. Demilade Agboola: So… Yeah, yeah, no, I just… no, because I worked with folks with, like, in India, and and… Chadd McNicholas: Fridays was like, okay, I’m gonna leave you alone. Because it was… yeah, basically, what was it, 6 AM was 8pm their time or something? Or something like that. It was… Demilade Agboola: Pretty close to that, and it’s just like… Chadd McNicholas: I’m not gonna bug you on a week, on a Friday night. So, yeah. Okay, cool. You answered all my questions. I think this is, I mean, a really cool company, and also a really interesting application process, which was kind of fun. You had to watch my video, I’m assuming? Demilade Agboola: Utam did, I… because I… Utam. Chadd McNicholas: Oh, okay. Demilade Agboola: And then awaits interviews, then I interview, and then there’s just, like, one more stage, and that’s it. Chadd McNicholas: Yeah. Okay, cool. Yeah, I got no more questions, so I’m good. Demilade Agboola: This was great, this was great. Like, I’ll get my feedback across to the recruiting team, and I’m sure they get in touch with you, like. Chadd McNicholas: Oh, and how do you pronounce your name? I didn’t get that. Demilade Agboola: Dimiladi. Chadd McNicholas: Demilade, okay, I would’ve… okay. Demilade Agboola: So it’s like… Yeah, it’s a Nigerian name, I’m from Nigeria, so… Chadd McNicholas: Okay, cool. Alright, I’m just Chad, so… Alright. Cool. Alright, hey, you have a great weekend, and a good Friday night. Demilade Agboola: You too. Alright, bye. Chadd McNicholas: See ya, cheers. Demilade Agboola: choice.