The Data Hustle Transcript

Resumes Are Obsolete, the SaaSpocalypse and Going Freelance — Ian Allison

Episode 16 · Nov 3, 2026

Duration: 45:47

Source subtitle file: 2026-11-03__1yvcoI8pwWo__Resumes_Are_Obsolete_the_SaaSpocalypse_and_Going_Freelance_16_Ian_Allison.en.srt

Generated from exported YouTube subtitles. Speaker labels are approximate.

[0:01] Tony and Juan
You are listening to the Data Also podcast, where data is turned into business impact. Ian, thanks for joining the show. I just wanna dive straight into the first question here, which is: what do you think separates the top 1% of candidates for data and AI roles from the rest at the moment?

[0:27] Ian Allison
Yeah, I, I think the biggest thing is, curiosity. And I think that that's been, the driving indicator of those who are naturally inherently curious, from the, the rest of everyone else. So, and that's not just like a data and AI thing that's kind of created that. I think that that's been something I've observed, for years. I think it was about ten years ago now. I was interviewing, this candidate, and I, I had two open roles at the time, and one was a data architect and one was like a, just a enterprise analyst, right? And so, I was interviewing for this enterprise analyst and, this guy was definitely like qualified for the enterprise analyst role.

[1:21] Ian Allison
Absolutely insanely unqualified for the architect role. And I'd been interviewing both for a while. And this guy was so like s- taking notes and was like so emphatically, like genuinely curious. Like, we'd ask a question and he was like, "Okay, I'm researching that." And he was just so excited to learn that, at that time I had told my boss, we had interviewed like probably like fifty different data architects and, I said, "I want this guy for my-- for, for this, for this role." And he was like, "Oh yeah, we're definitely gonna hire him for the, enterprise analyst role." I was like, "No, no, no, no, you didn't hear me. I want him for the architect role." And I, I don't think that's changed.

[2:05] Ian Allison
and so the people who are like hungry in their curiosity is really what defines the people that are like really pushing the ball forward. And the other piece is those who have the ability to discern value. And so, there's the curiosity piece where they can just run off and they're just like so focused on learning that they just work on the next big flashy thing, and they have no discipline. so it's a combination of that piece and then also their ability to actually succinctly identify and articulate value. And so, if I had to say like they have to have both in order to be a one percenter. and so if, if they have just one, you end up getting to a place where the value person is going to end up like getting into holes they can't kind of dig themselves out of because they don't have the curiosity to kind of like take them to the next level and explore solutions that are much more like developed.

[3:14] Ian Allison
The curious person, if they just run off, they're the type of person, I used to have a, a mentor of mine who is Australian, he called it, the magpie syndrome. You just chase the next shiniest thing. And so, so you have to have a discipline of both, otherwise you go off the rails.

[3:33] Tony and Juan
Yeah. I've met people that have one or the other, but not both, and it's quite interesting just to think of those examples. I have a, a question for, like, more the modern times. So I think many of us are in the same boat that we have been playing a lot with AI, and we have been, like, changing the way that our field is done nowadays. How do you show people that you have both that curiosity and also, like, that they're-- Like, what are the things that you can do in a candidate today in 2026 to show both in the AI

[4:10] Ian Allison
Yeah, so the curiosity one's actually really easy to solve, and that is you ask some questions about things that they are curious about outside of their profession. And so, if they aren't curious about anything outside of their profession, they're either too stiff and too rigid to kind of like... And they're gonna be kind of difficult and close-handed to work with. so I usually kind of dismiss that. But I ask that, and, and then it's just probing questions from there. Like, if they're not excited about what they're curious about, then they're just throwing you an answer. but once I like... You get-- there was a, a f- a friend of mine I had. He, his name was Roy, and he actually was a World War II vet, and he was a pitcher, and actually pitched against Mich- Mickey Mantle, in Hawaii where they were both stationed during World War II.

[5:04] Ian Allison
And, this guy was a phenomenal salesman. He says, "Everybody has a button." And he says, "If you're a salesperson, if you can figure out that button and you can press that with them," he said, "they're gonna light up with joy, they're going to love you and be so excited about you because you're talking about the thing that they love, and you're getting them to engage in it." If you talk to somebody and ask them about like, "What are you curious about? What gets you excited?" And they're just deadpan and they're not like getting into it and telling you all about it, and then if you can't-- And then if you're like, "Oh, is there anything else?" And they're like, "Oh, I, before that I was doing this," immediately you know they have that curiosity flag.

[5:42] Ian Allison
So, so those are how you kind of address the curiosity side. The value proposition is very, very like, different per role, and s- you would expect it to be that, right? So, let's take for example like a business intelligence developer, right? So if, if I go to a B- BI guy and I say, "Hey, tell me about the last report or dashboard you built or solution you built And then they start telling me about it. And then I go, "Okay, now tell me, what was one practical thing that a user for that dashboard actually did and changed? And what value did it drive to the organization?" And if they can't do that on the report that they're the most excited about, they don't understand value.

[6:38] Ian Allison
They're a list taker. They're just gonna fulfill a task. So, the people who can ask- answer that type of a question where... And I use that as a BI example, but it's gonna be different apa- across different disciplines, right? So if you're going to, like, a, an AI engineer or a, formerly known as data scientist, like, you go to these types of guys, you're gonna frame it differently, right? So, like, if you end up getting to this end state with this ML algorithm that you're designing or engineering, what value is that driving to the organization? And at what ROI are you expecting it to do that at? and if they can't articulate that, then they haven't really understood how they're driving value.

[7:28] Ian Allison
and so those are, like, really kind of fundamental, easy questions to kind of just, You don't even have to be a technical expert to get those out of the way, if that makes sense.

[7:41] Tony and Juan
That's a very neat trick. I wish I would have known all of this when I was first applying for jobs.

[7:48] Ian Allison
Well, I mean, it's, it's also, like, a mentality, right? Like, and this is, like, when I try to mentor or when I'm working with and mentoring others, like, it's, it's training them to think about the value proposition, right? So, and then once you learn how to, like, teach that, then it's kind of like having to, like, rein that in and say, like, "Okay, now how do you communicate that?" Because you don't wanna be the guy who goes, "Well, I'm not working on that," and you become this person who's not able to collaborate because you're like, "That's a low-value priority. I'm never-- I'm not gonna work on that." Right? and so you have... You'll find a...

[8:30] Ian Allison
probably you've worked with those people who are like, "Oh, given my priority list, I'm not helping you." so you have to find that proper balance.

[8:41] Tony and Juan
Interesting. So... Maybe going a bit beyond this, one question that I really am curious about and that you may be in a great position to tell us is, how is the market right now for people that want to go as freelance?

[9:03] Ian Allison
that's, that's a tough question. Okay, so when we're talking about freelance, at what level makes a huge difference, and then what type of client base they're looking at. So, sorry, I'm not trying to, like, push back, but it i- it's a little bit more nuanced fair, fair. So...

[9:21] Tony and Juan
and this-- The, the context there is every now and then, a lot of my colleagues, former colleagues, we're talking mostly like very senior professionals. I cannot tell you a percentage, but there is always a big chunk of them that think, "Oh, this is the year that I go freelance." But especially in the last couple of years, we've heard a lot of noise, a lot of please don't do it, the market this, or we're waiting for that, or I've even heard people saying like, "No, it's, it's great, like, people should start like going freelance again." I'm curious, what are your thoughts? And maybe let's park it at people that are already senior-ish

[9:59] Ian Allison
so senior, senior-level people, and we're assuming we're not talking about fractional executive roles. so i- if you're talking about that level, I think, and a- again, this is just my, my own personal perception, is if you're not moonlighting freelancing, then there's no reason for you to jump in both feet. the most difficult thing for freelancing is booking new clients, and booking them at rates that are acceptable to both parties. So, what I would recommend is start with moonlighting and then if you're finding that the scope of work goes beyond what they are wanting, then you make that transition, to doing freelancing. and ideally, you should be trying to do, like, multiple small freelancing jobs 'cause I think once you get into a place where you're doing it full time, you're, you're just a contractor at that point.

[10:57] Ian Allison
You're no longer just freelancing. So, that would be my, my recommendation to the audience or to anybody else who, who's looking and considering that. As to where the market's at with it, I think that there's, The market's tightening up, right? So, I was helping out somebody build out a data mart about a month or two ago, and it was astonishing to me. The data mart was exclusive to one data source and so, so keep that in mind. and I was able to have the full extraction and the data mart built in less than a week, right? And when you're... When you put up the proper AI harnesses and setups, like, that would've been a previously, like, at least a month, right?

[11:53] Ian Allison
Maybe two. And now I'm delivering it in less than a week. And so a lot of teams are able to be significantly more efficient, especially for the, the, better developers. what we've found, or at least what I've found, you guys can tell me your thoughts on this, is that- AI augments, and what I mean by that is, is it augments whatever your performance and your quality is. So if you're delivering at like a super high bar, you're gonna be able to go like from like producing at like a 2X to like a 10X everyone else. If you're a mediocre to subpar, you're just gonna be producing a whole lot of slop at a much faster pace. And so it augments your skill range, right?

[12:45] Ian Allison
And so, so I'm finding that there's a lot of organizations that are paring down their teams, and so them looking for freelancers, is gonna be much more in the SMB market, like the small, small to medium-sized businesses, and not so much the large corporations. So, so I, I would say like that's probably where you're gonna end up finding that space. I think the large corporations are, in many ways downsizing or just not backfilling. So...

[13:20] Tony and Juan
Yeah, of course. If a company just fired a lot of people, then they're probably going to be very careful about who they hire and how they do it. And that makes a lot of sense. But I do see that a lot of smaller to medium-sized companies are now seeing a lot of possibilities and said, "Hey, we never had capacity to build, I don't know, a data lake, but now that it's a lot easier, then maybe let's tackle this project with AI." So they're becoming a bit more ambitious.

[13:50] Ian Allison
Yeah, I mean, I think that there's, there is a huge and growing marketplace for those who've-- I think I mentioned either before the call or, in this call, there's a growing, gap where there's those people who have woken up to AI, and how to use and leverage it properly, and those who are just dead asleep, right? That are just like single prompting, a code and then like reviewing and editing it and then making a question about how to edit that one piece of code that they just did as opposed to, engineering proper, harnesses and using agentic workflows and having Markdown file or like whole Markdown files to actually set up architectural principles and frameworks so that way when things get built, they buil- get built with proper quality and then doing those code reviews to just-- and then those actual data quality reviews.

[14:57] Ian Allison
And so, I think that there's gonna be, a huge space in consulting for being able to go into the SMB business and standing up, whole replacements for existing solutions. Like doing, if you're not already familiar with seeing some of the peop- like, we just, had a full Informatica MDM replacement, and we built it all off of Python, and it operated better than the previous im- implementation, right? And so I think that there's gonna be a place where, the, all the software was built in-house. And so like we're gonna see like the SaaSpocalypse is real. And so coming into an organization and saying like, "Now we're gonna build a piece of software that's specifically custom to you," and not having to go and build, having a, a canned solution and then trying to force it into your existing ecosystem and workflows.

[16:03] Ian Allison
And I think that there's just gonna be a huge market space for building and integrating in solutions that are far outstanding just one component of a AI solution or of a software solution. But that's what we're gonna start seeing a whole lot more of, right? Is, people coming in and being able to freelance and do consulting, and saying, "Hey, we're gonna come in and, and build this solution." And it's gonna look very much kind of like, when you had people coming in and standing up, like computers back in like the '80s and '90s for companies and then saying like, "Okay, now we're gonna train your team on how to use it," and then we go on to the next place and set up that environment.

[16:54] Ian Allison
so I th- I think we're gonna see that going on for the next two to three years. I don't know where we'll be after that, but I think that there's a huge window of time where that marketplace is gonna be booming, if that makes sense.

[17:06] Tony and Juan
Yeah, it makes sense. And, and probably like one part that I'll be curious is, I think tools are gonna go back to being a lot more modular, similar to like the beginning of the cloud, because even if you can write code things, you might probably think, "Oh, but, authentication store, let's use this tool, and for payment, let's use Stripe, and for..." Yep. People are probably gonna build their solutions, but still connect it to third-party services that do something smaller. That's at least what I've seen a lot of.

[17:36] Ian Allison
Yeah, I think, the software companies that will survive are gonna be predicated on financial services and, security-related features. And I say that because those are the ones that are going to be the places where people do not want to replicate that using, So financial services, there's whole regulatory compliance issues, right? So like with Stripe and all those types of things, you-- they don't-- you just don't wanna get your ass sued off. and then in addition to that, from a security perspective, do you really want to have something that was vibe coding managing cre-credit cards or whatever, things of that nature? the answer is absolutely not.

[18:17] Ian Allison
So I think, I think those company-- software companies, like you said, that are gonna be very like, unique in a specific discipline, that are addressing all of the corporate bureau-- or all of the bureaucracy from a government perspective or from like a fiduciary or from a s-- from like a security compliance perspective. So yeah, I totally agree with, with that perspective. Wow.

[18:47] Tony and Juan
You know, Ian, y-you mentioned something before that I kinda want to go back to because I-I've been thinking about it, and it's interesting. You said that some people have like-- that are, I don't know, much better, much more proficient, or that they woken up when it comes to using AI, and I think the bar is always a bit different. I- I'm having trouble to think like what constitutes like basic usage and what is like... So maybe my concrete question is: what are the things that you see in a person, you say, "Oh, this person is like really good at working with AI"?

[19:24] Ian Allison
Yeah. So, so what makes a good person like in the category of woken up? one is, do they know what AI cannot do? Do they know where are the quality gates that they need to be checking and validating and those types of things? So let's assume that those pieces, which are core principles, the-- to somebody who's competent in AI. what I mean by w- people who've woken up is, So I was at, a, conf-- two s- two separate conferences within the last like three weeks, where it's about a hundred and fifty or more, chief data officers and chief a- AI officers, in one conference, and then the next one was, chief, information officers. So, at those two conferences, right, it was very distinctive.

[20:23] Ian Allison
There was probably like Two or three people who had gone through an experience where, some other-- some executive leadership member, went and vibe coding a bunch of his-- bunch of things, stitched together using MCP and their local credentialing to source systems, and stitched together some sort of software application or reporting or whatever, right? And then turned around and put the data and AI teams and IT completely on their heels and saying, "If I can do this in a weekend, how come I don't have this? How come I don't have that?" And it put everybody on the reality that, like, the citizen developer is now going to be sitting at the executive tables and demanding and expecting a throughput and a pace that's n- at a never-foreseen or chartered territory.

[21:26] Ian Allison
And those who I say who haven't woken up is saying like, "Okay, what do we do about vibe coding and these types of things? How do we interface and how do we interact with this? How do we ensure quality? How do we ensure, security? How do we ensure, all of the different integrations are being done properly?" And things of that nature, right? So, so when I say woken up, what I mean by that is like understand the cha- the pace and the change of what's occurring and how to use and leverage those things. So, part of that is, when you talk to the people who I say have woken up, like they truly understand building out a proper AI harness, right? And setting up those frameworks in such a way where you're giving the LLMs the latitude to do vibe coding, within a very controlled ecosystem, and having it do like formal CI/CD and actual like, the approval gates in like Git or whatever you're using is being done by formal review with an individual.

[22:34] Ian Allison
And so like when you're actually pushing and deploying things, you're doing it where it's necessary. So like if, if you're setting up an API to make certain data calls into some sort of application, right? Like knowing where to say like, "This is where I need to go and v- like do validation," and this is like, "Hey, I-- here's some sanity checks. It checked out. It's producing what I would expect it to." and not necessarily having to go into the code, if that makes sense. So knowing when to like do formal code reviews, knowing how to set up those frameworks, knowing how to check, how to check and where to check, those proper quality gates. Those are gonna be the people that I've said have woken up and are n- learning how to articulate how to pace the executive boardroom when they start going down those roads of saying, "Hey, look at this app that I've built.

[23:35] Ian Allison
Why can't you build this faster?" Or, "Why can't you deliver X, Y, and Z?" So these are serious conversations that I think that nobody's having that are needing to be had, months ago. And I'm seeing a serious drop in the attendance in people attending conferences, and I think a large degree of it is when you're talking to people who haven't woken up yet, it's kind of like, "Dude, like, this is what's going on. Like, you gotta get with the program. These are the conversations we need to be having." And then when you're having, And so when you're having those types of conversations over and over and over again at some of these conferences, and it's like, "That's what you're still talking about?" Like, guys, like, that's not the priority conversation right now.

[24:23] Ian Allison
So that's kinda what I mean by the difference between those who've woken up and those who, are still, kind of playing by the rules of the last couple years, if that makes sense.

[24:40] Tony and Juan
I- gonna guess most of us are in the same boat that we don't know exactly where we are in that scale of like, being AI beginners to advanced. Because it's very hard to know like, exactly today, how far is the average of the industry going. You go to a conference and sometimes you hear very beginner-focused things. But you can imagine there's probably a lot of like silent users doing crazy. I,

[25:06] Ian Allison
Yeah, I mean, that. sometimes-- Like, so one of those conferences I went to, I talked to a guy and, he, the things he was doing was on such a another level, right? Like, when you talk to people who are doing it right, you realize like, "I'm ahead of the ball, but I'm so far behind where I should be," right? And, having like the emotional discipline to not freak out and to just be like, "Okay," like, "what's next steps? How do I continue to move forward?" yeah, there's people who are doing absolutely phenomenal things where they're setting up their own like data centers and got their org-- their companies to turn around and say like, "Hey, look," like, you know, "token usage is being subsidized right now by these large LLM companies, and, here's how we're gonna set up our own models and frameworks and harnesses, and we can do this in our own ecosystem, and we can adjudicate the offset by sunsetting this breadth of software applications that we're

[26:13] Ian Allison
currently implementing," right? And these are top-level conversations that have to be had, and if you're not there, then it's, it's very difficult to get a seat at such tables. So-

[26:22] Tony and Juan
Yeah, this is definitely something I've, I've seen in my past conversations with, people in more managing roles and, ent- larger enterprises. They're looking at, you know, the The token subsidiation, and for those listening in, what this kind of refers to is the fact that if you have a two hundred dollar subscription, for example, with Claude or with Open, AI, you can get up to like five or ten thousand dollars in API cost equivalent out of that. That's gonna go away at some point. Everybody knows this. and I, I think it's very poignant that you de-describe this, that, the discussion is being had, and I'm seeing this happening in real time where, you know, companies are starting to plan out building more of their own capacity when it comes to running these models.

[27:18] Tony and Juan
And, it's a very interesting development. I mean, there could be some potential there, in the industry as well for those that are able to, supply that demand. Now, for some companies, it's gonna be catastrophic the moment they pull off the plug. Like all of a sudden, all of your developers don't remember how to code anymore, and, you don't have

[27:42] Ian Allison
Yes. Yeah, there's a, there's a huge, There's gonna be a huge gap that, with the automation of knowledge workers, right, and the augmentation of them, the entry into, the space becomes, insurmountable, right? Because now you take, a top-level engineer who's operating at 10X because they've been augmented through AI, but it took them fifteen, twenty years to get to that level of competency. And now you have people coming in, and it's like, okay, how do you bridge some of those, those knowledge gaps, especially when you're talking about legacy systems, right? And, and so it-it's gonna be-- I did a whole podcast with somebody who basically was talking about, like, how do you build out a ML algorithm that evaluates financial forecasting, right?

[28:45] Ian Allison
developed and used for senior-level financial analysts. And when, you have them using it, it augments them. And the entry-level people, all they do is rely on it, so they're, they end up running into ser-- significant issues because they haven't had to go through the forging process of actually learning the tasks themselves. So, I think there's gonna be an interesting space where there's gonna be a huge knowledge gap loss. And I don't know if this is, gonna be different in history, as the advent of technology has always created a, a loss of knowledge, right, in different avenues and respects. The question is, is, is it the pace that we're moving at, going to be the differentiating factor?

[29:47] Ian Allison
Is this going to be different than history because we've been moving at a faster pace of subsuming historical knowledge? If that makes sense. So, I don't know. All

[30:01] Tony and Juan
Yeah. So a lot to ponder about. I guess something, something lighter for those listening in, it, it might seem catastrophic and insurmountable if you're on the other end of, of the spectrum where you either rightfully or unrightfully so believe that you're, you're on the low end of AI adoption, and you might become irrelevant. When should people reach out and work with a recruiter, and how can it help them in the process?

[30:34] Ian Allison
Yeah, so, like, if you're trying to identify, when do you work with a recruiter, right, on identifying AI talent. I think, the whole reason I created Salient Insights, right, was that I got to a place where I identified that if I wanted to be successful as a middle manager or above, then it was absolutely critical that the people who were underneath me were at the top level of talent, right? So the difference between an A person and a B person is significant. And so in order to identify those candidates, I, I had to go through, easily over fifty interviews or more. And I found resumes is not an assessment of talent at any capacity. In fact, I found some of the people with the worst resumes had some of-- were some of the best talent you could find.

[31:34] Ian Allison
So, resumes, have really become obsolete because, most, most organization-- or most people now are just, AI spoofing their resumes to the job description and having agents do that. And then, so you have that element going on, and then you have on the, on the hiring side, right, most HR teams end up having, their application tracking systems or ATS using LLMs to process these resumes. And so now it's just this, like, cat and mouse game where everybody's trying to, like, game that ATS, ATS are trying to figure out how to read these resumes. And at the end of the day, anybody who's, who's actually gone through proper interviewing and looking for top quality talent knows a resume has low to no bearing on...

[32:36] Ian Allison
Like, I can't tell you how many times I've looked at a resume and was like, "This is an all-star right here." I brought them in, and within, like, two questions, I'm like, "Get them out of the room." Like, this guy-- I'm so disappointed that this resume is not reflected in the individual I'm speaking to. And so, so the space that Salient Insights was created was predicated on the fact that, like, it's a huge volume of work to identify top quality talent for a hiring manager who's already understaffed. And so what we end up doing is we actually end up running full pre-screen interviews, right? So we do those assessments on curiosity. Do we do those assessments on do they understand value, right?

[33:20] Ian Allison
do they understand the technical requirements of what they're needing to accomplish? And sometimes that's just even working with the hiring manager and properly understanding that. Like, most, most recruiters from a HR perspective or even from, like, a third-party recruiting firm that you work with, they can't discern, where there is a cross sk-cross-skill evaluation, right? So it's like, "Oh, like we're needing somebody that's, exclusively a Snowflake or exclusively a Databricks guy." And you're like, "Okay, but why?" And then it's like, "Well, actually, as long as they understand these fundamental principles." You're like, "Yeah, okay." So these skills are transferable skills, and the platform that they're using is agnostic, right?

[34:05] Ian Allison
and so there's a lot of pieces like that. So when should somebody identify that? When you're, when you're w-want to do the due diligence of f-finding the top talent at no cost or time to you, would you work with someone like Salient Insights. So, most of our recruiters or most of our placements, we give one person, and it's actually unnerving to somebody for the first time because they get the one candidate, and they're like, "You're not gonna give us more?" And I'm like, "No. Like, this is the top person you're gonna get for this role." And then they interview them, and then they're like, "Okay. Yeah, yeah. We'll, we'll extend the, the, the, the offer." And then, like, couple months later, they'll come back and be like, "Dude, I knew he was good, but I had no idea he was this good." And I'm like...

[34:52] Ian Allison
Or she, right? And it's like, "Yes. The, that's, that's the whole point," right? So we really try to make sure that what we do is we, we, we end up going through and getting out that whole process of, like, evaluating that candidate, so that way hiring managers can stay focused on what they're trying to accomplish, and then they get given that top person. So...

[35:18] Tony and Juan
So for the people listening, what will be the, let's call it the six months roadmap to appear in that top percent of your search, Ian?

[35:29] Ian Allison
yeah, so I think, So first, the way we identify candidates is, one, we go into our internal network. So, on my website, there's a way to, like, kind of get into our network, right? And, once we identify somebody that's in our network and we say, "Hey, this is a person who's been well-respected," I'll go and say, "Hey, Tony, you have, expertise in this area. do you know anybody that you would highly recommend?" And so we tap our network first. and then after tapping our network and we've exhausted that for a particular role, then we go for people who are off-market. so oftentimes people who are not looking for work, and not actively applying, we re-we do-- we'll do-- end up doing cold outreach that way.

[36:25] Ian Allison
and so whether that be from something they've posted on Reddit or something they've posted on Stack Overflow, if you still post there, or just even their Git library, things of that nature, we have a bunch of things to go and scrape and identify like, "Hey, look, this is a person who's, publicly identified talent in this particular space." and even on LinkedIn, right? I can't emphasize enough, the future is gonna be built on personal branding. and so if you're not, like, talking about some of the cool things you're doing on LinkedIn, like, start doing that, whether it's for my firm or not. Like, that's one of the biggest recommendations I can give.

[37:10] Ian Allison
and you'll start getting picked up, right? Like, I was talking to, to an individual who is a CIO who got placed at a, very large corporation, and, he, As we were talking, he was just like, "Hey, you know, like, why don't you, like, make a post, or do a bunch of posts about the solutions that you're talking about for these things?" He's like, "I guarantee you'll land, a seven-figure job, no problem. Like, people will reach out to you based off of what you're talking about." And, and so I haven't had that experience. I haven't actually posted some of the things that we've talked about, so, but he said that that worked for him. And he said, you know, like, once I kind of like laid out the details of how we were going about doing X, Y, and Z, and, he was able to demonstrate that and create that social proofing.

[38:08] Ian Allison
So I think, social proofing, whether it be on LinkedIn or a YouTube channel, whatever, I get it. I'm, I'm a data guy, so I absolutely hated socials, and, I've only started and been on them for the express purpose of working on my business. But, That's a, that's a question you kind of have to ask yourself, where do you see the future going? And I think you're, you're gonna have to create a new way to personal brand because I think that that's gonna be the future, so.

[38:38] Tony and Juan
Yeah, especially if CVs are becoming less important, like you mentioned

[38:42] Ian Allison
Oh, they're, they're-- in my estimation, they're totally irrelevant. Like, the last placement I did, I didn't even look at the resume. Like, didn't even look at it before I presented the candidate, and I had full confidence this guy is legit, like you're gonna love this person. So like that's, that's a totally different experience, and I think it's the, the way things are gonna go into the future, so.

[39:07] Tony and Juan
Which-- Somewhere hidden in there is also, like, the people that you network with because if that's the first place where you start looking for, then knowing the right person is also gonna be an interesting way of landing a job. Yeah,

[39:22] Ian Allison
Yeah. Yeah, networking is huge. I think, people are doing a disservice to themselves by not showing up to networking groups. and here's a really odd thought, but it's something people need to be aware of is you need to be networking with the person who is hiring for... How do I articulate this? You're always networking for today and tomorrow. And what I mean by that is like, if you're trying to get a chief data officer role, right? And you're trying to network, and you're networking in exclusively the chief data officer communities, you're never gonna be offered a job from another chief data officer. So you have to network with CIOs. You have to network with chief financial officers.

[40:14] Ian Allison
So, and in that same way, you also wanna be like networking with the people who are going to be there. So who may not be there today, but will be there in five, 10 years. So if you're-- depending upon where you are in your career, like step back and say, "Hey, where is it that I want to go? Okay, these are the communities that I need to start interacting with," knowing that as they gr- as I grow, they will as well. And so, so it's interesting. It seems almost counterintuitive that like a lot of people will end up like going naturally into the places of networking that are specific to their domain, and, and I would argue that sometimes that's not-- that's kind of a little shortsighted, if that makes sense.

[41:07] Tony and Juan
It's, it's not because it feels like a cheap therapy, but I, I do understand the value of going to something completely different.

[41:15] Ian Allison
Yeah. I, I'm not saying don't go... Like, networking within your like, area of expertise, it drives you further if you get with the people who are like-minded in that, and they're gonna share with you things they're doing, and they're just gonna say, "Go review this. Go research that." and so it will like really push you. And like when you see what other people are doing, you'll be like, "Oh, wow, I'm so far behind. I, I wanna go study up on, ontologies. I, I really wanna go study up on, semantics or, You name the space, right? so, deep learning, whatever, right? So there's a lot of things when you go into those communities that really like push you to do better.

[42:01] Ian Allison
but I'm just saying from a, building a personal brand, explore networking beyond just that, so.

[42:13] Tony and Juan
Yeah, it m- it makes sense. If you go to like a data leadership conference, chances are that the people that you meet are the ones hiring. So that, that removes a little bit of the chain than if you have to meet a practitioner and they tell you, "I can introduce you to my boss," then...

[42:32] Ian Allison
Yeah, I mean, if, if you're a practitioner, go to da-data leadership conferences, right? understand what are the... What was that?

[42:42] Tony and Juan
Any short list of conference you would recommend?

[42:46] Ian Allison
Yeah, I think Chief Data Officer Magazine, I was recently published in them in December. they ha- they put on phenomenal conferences. Corinium does really good conferences. I really appreciate those ones. so Corinium, is a great conference. there's, depending upon what metro area you're in, there's, Gartner's C Communities. Usually, you have to be like a director level or above, for that. so those are good conferences. I mean, I think, Data Day Texas was probably the best conference in my estimation. it's no longer going on, but I know that Lynn, is, setting up smaller groups settings that's, more of like, Colloquial style conversations and not so much speaking events.

[43:50] Ian Allison
I believe there's one going on in September or October, of this year. So I would definitely, look for Lynn Bender, and I think Joe Reis oftentimes will post about that as well, so you could look up. If you can't find it through other means, those are also great places to go. so those would be the ones that, I personally would recommend.

[44:18] Tony and Juan
So Ian, what's next for you? Where people find you?

[44:23] Ian Allison
Yeah. So, I'm on LinkedIn, and then, salientinsights.com. That's, the recruiting and, consulting firm that, we just, previously discussed. And then, I'm also on YouTube and then, LinkedIn and TikTok, I'm gonna be doing a whole lot more shorts. So if you're interested in like how to interview, for specific roles, I'm gonna be doing a whole bunch of social media posting here in the next six months on how to interview for AI engi-- en-engineer, how to interview for data engineer, how to interview for data analysts, B-BI developer, right? So, so if you're looking for those types of things, you'll find those on YouTube, Instagram, and TikTok. and then also some of them will be posted on LinkedIn, if they perform well on the other platforms.

[45:14] Ian Allison
So, that's, that's where I'll be at, and, happy to talk to anybody that, specifically references, this podcast. So I'll set up, even a fifteen-minute meeting if they're interested, so.

[45:29] Tony and Juan
Well, we, very much enjoy your generosity of your time with the podcast and with helping people in the community. we'd like to thank you again, and, yeah, we wish you all the best.

[45:40] Ian Allison
Yeah. Thank you, guys. I really appreciate you taking the time to spend time with me on this call.

[45:44] Tony and Juan
Thank you so much for your time as well, Ian.

[45:47] Ian Allison
Yeah.