CIO Leadership Live with Kory Jeffrey, Principal and VP, Technology, Inovia

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Welcome to CIO Leadership Live. I’m Lee Rennick, Executive Director of CIO Communities for cio.com and
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Unknown
I’m very excited and honored today to welcome and introduce Kory Jeffrey, Principal and VP, Technology, Inovia. Kory please introduce yourself and tell us about your current role.
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Unknown
Sure. Thanks for having me, Lee. I’m Kory, I, like you said I’m a Principal and VP technology. I know, yeah, Inovia is a, full stack, and venture capital investment firm and headquartered in Canada. Full stack. Just meaning we invest as early as company information all the way through to pre-IPO. So, it’s been around about 20 years.
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Unknown
One of the the largest VC firms in the country. And I know I wear two hats. One hat is the principal hat, and that means I do, early stage tech investing. So for me particularly, that’s sort of the company formation to series B, where I focus, mostly on practical applications of artificial intelligence companies like Cahir Spell, spellbook, Reliant, Venture IQ and others that I’ve been involved with.
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Unknown
And then I also wear a hat, which is a VP of technology, where I work, in the CTO office, where, that’s across the entire portfolio company. So that’s working, with companies, we’re very small or very, very large, and helping them build world class, tech and product organizations.
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Unknown
Yeah.
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Unknown
So congrats for that. And just yeah, sharing about your role. I think it’ll be really informative for our listeners who are listening in today.
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Unknown
And I really appreciate you joining us, Corey. So as I mentioned, we’ve really developed this series to support the technology leader and CIO in their tech and leadership journey. And so the first question that I ask everyone this question on the show, could you please tell me a little bit, perhaps about your own career path and leadership journey to date?
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Unknown
Any lessons learned along the way that you could share with our audience?
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Unknown
Yeah, sure. So I like to describe my career as sort of like sitting in the back of a moving truck, looking backwards and not. It’s not super intentional. I actually started my career academically, in, studying English literature and philosophy, epistemology and metaphysics. I was actually on my way to do my PhD in, in metaphysics, when, guy named Ian Clubman from Communitech pulled me aside and said, hey, why don’t you come and, help run this, startup technology accelerator with me and a couple other people?
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Unknown
You know, I said, I don’t know anything about that. And he said, oh, you’re smart, you’ll figure it out. And so that got me into the startup world where I spent two years investing in companies. And this was at the time when Y Combinator had just started. So it was like this, like accelerator boom. Through that, I learned all about technology, fell in love with products, you know, started becoming technical.
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Unknown
I was then, introduced to Steve Woods, who ran engineering in Canada for Google, and was recruited to join Google, where I spent the better part of a decade, did a couple of things. So I ran developer relations in Canada. So that was you know, running developer communities, launching developer products, things like that.
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Unknown
I then spent a bunch of time in emerging markets where the next billion users were coming on to the internet Indonesia, India, Brazil, and got to understand what markets that were skipping, who had skipped the desktop revolution and went straight to mobile, how they were coming online and how they were building products. And then I started having kids.
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Unknown
That was around 2016. And so it was time to have more of, a local role than spending. I think in 2016, I spent 100 days on an airplane, out of country, and I almost ran into tax problems, actually. So, then I switched over to be the chief of staff of engineering for Canada, where I helped grow the engineering organization in Canada for Google, for, about 200 when I started to just over 2000 when I left across all sorts of different product areas, research areas, all of the things the the transformer paper was published when I was there.
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Unknown
We got to see that go through first party products, work a little bit with Jeff Hinton’s team. All those sorts of things. I would say a major lesson through all of that is that it’s all about people. You can do some really amazing, hard, inspiring things with great people and have it feel, fun and not easy.
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Unknown
But, you know, it’s, invigorating. And you can do some really easy things, that feel absolutely terrible with crappy people. And so, you know, trust matters, people matters. Investing in people matters. So when past mentors of mine, Steve Woods being one of them, who had mentioned and then another guy named Patrick Bouchard, who is the CFO at Google, when I started there, they came and pitched me, I know, and I followed that and became took that opportunity to work with some great people that I’d worked with in the past.
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Unknown
Yeah.
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Unknown
Yep.
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Unknown
I mean.
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Unknown
Yeah. I think that’s a that’s a good question. And it. I spent a lot of time doing due diligence on tech companies at various stages. You know, what they’re missing often is dependent on the stage they’re in and the levels of sophistication and how early versus later you are. But there’s a lot of themes. And so we sort of break it down into four buckets.
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Unknown
The first is always and this is in order of importance in my in my view, the first is always people. And we talked a little bit about that and I’ll dive into it a little more. Then it’s product and product thinking and then it’s your engineering practice and then it’s technology. Like what are you actually using?
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Unknown
Building the how. And so in the first case, I mean, it seems like an obvious one, but you can’t have a high performing engineering team and take like, ride a wave of a new technology. Well, if you don’t have great people. And this is a little ironic because a lot of the conversation is around a world where everyone’s talking about automating away your need for more knowledge workers.
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Unknown
Right. And so there’s a bit of a dichotomy here, right? But the thing that’s true is like, you know, there’s, there’s a guy on my team named Noah who’s who’s a wonderfully smart, and he’s always like, look, 20 years ago, if your doctor told you, you know, they didn’t have a smartphone, you might have been okay with that.
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Unknown
If your doctor told you that today, you would not be okay if your doctor said, I don’t use the internet and you would be, you wouldn’t want to have that doctor right? And the argument here is,
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Unknown
you know, the top 10% of your workers are going to get exponentially better and your middle and lower workers, well, those are the ones that, you know, get phased out over time.
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Unknown
So it’s not AI taking your job. It’s someone using AI. Right. That’ll that’ll get the left. So that means that having your top performers and we’ve always talked about these in my career is drivers. Having drivers within your organization is more critical now than it’s ever been. And drivers are those people who it doesn’t matter whose team they’re on.
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Unknown
If they see a problem, they just have to fix it. And when they move to fix it, they bring people together to get things done across organizations. And they act as a force multiplier. Right. And you probably think in your career of like someone who just everything they touched, like, and it had these ripple effects, right? These people are absolutely worth their weight in gold.
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Unknown
And at a moment where everything is in flux and everything’s moving around, if you don’t have these people in your organization, you need them now more than ever. So a lot of our time is spent evaluating whether or not companies have drivers. And then for those that we’ve invested in, then in helping them make sure they get drivers in key areas and empowering them to do things.
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Unknown
So that’s that’s number one. The other big one is product thinking is actually extremely rare. And so if you think about product thinking, it’s it’s a combination of like strategic insight, user empathy and executional excellence. Right.
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Unknown
Great product leaders. In my experience, even within large organization sort of function as many CEOs, in the fact that they work across everything.
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Unknown
Right? And they bring people together. And a lot of times companies have pieces of the product puzzle, but miss the other pieces and often those pieces that they miss fall into archetypal gaps. Like, I’ll let you know what I mean a little bit about that. So one is like, you have a company, maybe they pride themselves on being extremely scrappy, right?
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Unknown
So they’re really quick at iterating and experiment and getting things out. But they fall so much into that. Like, let’s just try another thing. Let’s just try another thing that they miss, that sort of, strategic insight and miss when to go deep. Right. So that’s one archetype. The other is, a deeply technical company that cares quite a lot about the system they’re building and the classic, like, Fall in Love with the technology.
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Unknown
And the, the bold sort of truth is, nobody gives a shit what technology you’re using. They care about the functionality that you provide as an outcome. And so those companies often miss having customer empathy. Right. And so they miss that in the product thinking, and then you have the classic sales led company where the product organization is sort of beleaguered by the 50 things that they need to do and change their roadmap on consistently.
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Unknown
And when that happens, like obviously changing your roadmap based on customer feedback makes a lot of sense. But if you do it too often, you miss being strategic at all because now you’re reacting all the time versus having a market view. So a lot of the time we spend a lot of time common advice on drivers and then filling the product thinking gap so that you can actually be strategic, empathetic and execute against a product goal.
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Unknown
And then you get into how you build it. And then to me, that matters actually less.
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Unknown
Yeah.
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Unknown
Yeah.
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Unknown
Sure.
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Unknown
Totally.
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Unknown
Yeah, that’s exactly it. And one of the things that I think think about a lot. Because, look, you’re running a big org. You have a bunch of things to do. You’re the things on fire. Always take precedent. And then also, you know, there’s the the bureaucratic cruft that just takes up time. Right. And so a lot of what in my career, what I’ve seen work, is we used to run what’s called a 70 2010 model.
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Unknown
And so across all those thousands of engineers at Google in Canada, Steve and I were really, really specific about, okay, 70% of everybody’s time should be on core product, right? Like trains on time. We’ve got commitments. We make our commitments. That’s the that’s our reputation within the company. And, that’s that’s table stakes 20% of people’s time should be on the edge of those core products.
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Unknown
So innovation on the edge of those products, you know, there’s always things that you wish you could do, but maybe you need to do more, you know, technical debt. But no, you got to actually make sure that on Mars, 20% of the time you’re moving something innovative forward and then 10% of your time is on something that’s unrelated and so crazy that it’s definitely not going to work.
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Unknown
But if it does work, this is a real game changer for the business, right? And so as an organizational leader like this doesn’t it’s not 70, 2010 per like a person’s time. It’s across your org. And so you really need to protect that experimental time in order to allow like that vendor problem to not become everything. Right. So you still have pieces of your organization that are innovating.
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Unknown
They’re using new tools that are whatever it is you need to do. Otherwise you’ll just always get stuck in in
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Unknown
Replatforming.
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Unknown
Yep. That.
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Unknown
Was wild. Yeah.
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Unknown
Totally. And it’s how you train drivers too, right? Because your drivers are people who get their work done and then are looking for other things. So you give them that thing, you give them somebody who has the potential right to work alongside them. And then that’s how you train the next thing. And then they spin off and do something else.
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Unknown
Right. And it’s, it’s a, it’s a it’s a great methodology for your innovation, but also on your investing employees so that they don’t find their next opportunity somewhere else.
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Unknown
We’re talking a little bit, a little bit. It all about excuse me already, but just around structuring teams and talent. So we’ve talked a little bit about that. Some of the ways you invest in your employees, you know, to make sure that like you said, they want to stick around because you are doing that work.
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Unknown
That’s really exciting for them. So but, you know, for the CIO listening in or the tech leaders, I want to talk a little bit about roadmaps for business and the types of things they should maybe look at around structuring and upskilling tech teams. You know, especially with LMS and Gen I, I was just talking to our head of research, and you know, what they’re finding from some of our research is that, you know, this genetic AI is a piece that now we’ll probably follow into some training with teams and upskilling and that type of thing.
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Unknown
So I would love to really understand a bit more of your insights on, you know, the people, the team building in the tech building and planning.
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Unknown
Yeah. I mean, it’s one of those interesting questions where it’s. How far do you go into the new thing? Right. And one of the things that I think people who have worked a lot with, whether directly with models or model based tools or LMS, it’s not a panacea of an answer for everything, right? It’s, it’s a hammer.
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Unknown
It’s a new hammer that, you know, you put in your, your tool belt and use where appropriate. And right now, people are hitting a lot of nails with it or things that look like nails, and not everything’s a nail. And so that’s a tough part for CIOs and other people to look at and be like, well, where am I actually getting value here for the investment?
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Unknown
Right. And so a lot of the conversation we’ve been having and we talk to our portfolio companies about is, you know, you take an approach where which part of your core value proposition, whether this is on like your internal infrastructure side or on your product side or whatever it is, what are that is do you think is going to be commoditized?
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Unknown
Right. Like what of that can be handed to an LLC and eventually it’s going to get sophisticated enough and then what do you add that’s like special and core.
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Unknown
And you want to you want to focus your efforts around the core stuff and then, you know, have a build versus buy decision and use tools for the things that you don’t need to be doing anymore so that you can go quickly.
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Unknown
When you do that, we see a lot of people. One of the traps, I think, that will play out over time for companies. We see a lot of people, get into what I call gross margin optimization, which is like knowledge workers output more, work more quickly using, LM based tools, you know, think tools like an internal search or velocity of code output or increase your ability to review contracts or just stuff like that.
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Unknown
Right. This is great. And you need to do all this stuff, but it’s sort of table stakes. And the way that I think about it is like there’s 50 startups who are coming straight at your value proposition in a garage somewhere, and they are moving way faster than they were two years ago because of all the technology that’s available to them.
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Unknown
And there’s a competitor of yours who’s doing something completely different on a product side, who’s focused on the customer experience, than they were doing it two years ago. And so if all you’re doing is looking internally at your operations, you’re probably missing piece of the puzzle that could cost you quite a bit. And so you don’t want to get stuck in that sort of navel gazing.
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Unknown
So that’s one piece of it. Sorry. Go ahead.
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Unknown
Yep. Totally. And and I and I feel for all the people in the, in these roles because,
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Unknown
you know, startups are able to throw whatever at experimentation. Because they don’t have the, the burden of, you know, systems that they need to maintain and customers that the, you know, the SLOs that they have to withhold and all those things hold up.
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Unknown
But the, the thing that you can do as a CIO is like, back to the experimentation piece is like, you need to be your 10%. You need to be working at it really hard. You need to have your best people figuring out what the actual use cases are that matter to you. And on the product side, and one of the things that I also would say is like, okay, so one sorry, before I do that tactically, the way that we’ve had these set up in the past is you take an, an executive leader who leaned in, you take a product person, a business function, know where they might be in marketing or sales or
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Unknown
wherever. I don’t know, it depends on your organization. And you take a couple engineers. These are your drivers and you just start building things, right? Like actually start building things because you can ask yourself,
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Unknown
how do I make sure that the next thing I get through my RFP process adds the most amount of value? But this changes so quickly that it’s actually worth more for you to be upskilling your people by getting them doing things hands on.
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Unknown
Right? Like that’s what you need. And then they can that can proliferate the organization. Another way to bootstrap this that we used to do is you are not going to learn from the person who’s been sitting in your organization for 15 years, is your senior developer, and is like, totally, you know, what do you call it, institutionalized in your build systems and the way that you work, like they’re great employees.
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Unknown
I’m not saying you shouldn’t have those employees. I’m saying they’re not the ones who are going to see how development is going to change. Right? That’s not the lens. Unless they’re super curious and they spend all their time at night doing things externally. So have interns like, again, it sounds simple. We used to always have. Across our offices in Canada, 13% of the offices were interns.
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Unknown
Always three like all year. And so that does a couple magical things. One, it pushes the bottom of your organization, right? It teaches your organization how to teach. Right. Which means you hold your standards. If you’re gonna have an intern, you have to know how things are supposed to work. And one of the risks of these lines in coding is that you take your worst people and make them ten times more efficient and crap, right.
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Unknown
And then also, it’s the 21 year old developer coming out of the University of Waterloo who’s going to teach you how people build things today. Right? And it might not. I’m not saying you need to throw all your stuff away and like, build like them, but that’s the insight, the energy that you need to look at that you can then compare that to what you do and like take the best parts of that.
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Unknown
And now move that across your your organization.
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Unknown
Yeah, yeah.
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Unknown
Yeah.
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Unknown
Yeah.
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Unknown
So final question here. You know, we’ve been talking about this a lot. But just, you know, a lot of I.T leaders have been saying like Jenny, I we’re using it to build productivity. I was at the CIA 100 in the US last year, and there are a lot of great use cases around this, right.
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Unknown
And they said, you know, we are bringing value to the business because we’re doing things 200% faster here. So now we can take some of this team and move them over here and have them learning about, you know, the next adoption stage, perhaps of, of AI. IDC just put out some research. They predicted that, you know, the AI pivot to build that I feel business model will be pretty strong in 25 and continue into 26.
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Unknown
I would love to hear your thoughts on this. We’re still in January, just almost at the last day of January here doing this interview. Interview. Excuse me, but any predictions for 2025?
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Unknown
Yeah. I mean, that’s the great thing about being a VC is you always get to make predictions and put a little bit of money behind it and see if it pans out. As Steve and I, Steve’s partner of mine at, I know we wrote a white paper in 2024 which had a bunch of predictions in it, and we did.
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Unknown
Okay. I would say on on how that panned out to date and then very wrong in some other cases. But I think that, 2025 is sort of the year of what we would call being clever. Right? So you’ve kind of moved away from actually deep because has pulled this conversation into the, into the mainstream, I think. But there’s this, you know, all the compute in the world maximalism to get to the next breakthrough, mentality.
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Unknown
That I think Deepak has called into question. There’s a lot of other companies. Cohere is another one of these companies that is focused on, usefulness, data security and outcomes. But I think there’s a shift at 2025, which is that you’re going to see more and more, market attention around what is this good for versus some sort of end state of AGI, whatever that means.
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Unknown
Right. Which I think is helpful because a lot of the benchmarks that you see, and that people evaluate technology on are mostly useless. And I think a lot of the CIOs would agree it’s the internal benchmarks of your use case that are actually helpful versus like some abstract, you know, benchmark against some generic reasoning. So I think we’re going to get more specific, which means you’re going to get more vertical ized in the models.
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Unknown
You’re going to have hyper focus and virtualization. I think those with a focus on security and data security and trust and transparency will do a lot better. I think in particular in the enterprise, there was early adoption in what I would say toy applications, but now these sort of deep embedded applications, take time. Right. And, and this is sort of one of those cohere aabc things that we were talking about earlier.
00:26:13:02 – 00:26:26:21
Unknown
I also think that a lot of the big companies that are successful here, have a surprising amount of service attached to them because of the handholding that’s, that’s needed here, for implementation of, I
00:26:26:21 – 00:26:38:23
Unknown
think, off the shelf, one size fits all. Tools work for consumer and SMB and don’t really work for the enterprise. So I think you’ll see more of that.
00:26:38:23 – 00:27:00:13
Unknown
And I think companies who do a good job at the services side are going to, win overall. I think you’re going to see a lot of emergence in Lem stuff, as we’ve been seeing that goes beyond like a chat interface. Right? We’ve seen a lot of entry stuff. Interesting stuff in geospatial and synthetic data creation and simulation.
00:27:00:14 – 00:27:26:18
Unknown
You know, the hearts and minds were captured with ChatGPT, but this technology is is much, much broader than that. And then lastly, I would just say like reasoning reasoning, right, that these are not reasoning in the computer science reasoning, not reasoning like these things are sentient. Is a fundamentally different technology than than like what, what one shot ChatGPT does with, with, Transformers.
00:27:26:20 – 00:27:49:22
Unknown
And so, you know, reinforcement learning is an example of something else you need. And so one of the things a deep sort of brought the attention to was that, you know, there’s now going to be a thousand RL, researchers who are going to spend their time on the intersection of reinforcement learning and transformers because of the progress that it seems to be make.
00:27:50:00 – 00:28:07:06
Unknown
And so getting that reasoning into the hands of people at the application layer is going to be incredibly interesting. And oh three is, open AI model that will take this a step further as well, I think. So I think in 2025, we’re going to see, you know, when people say again, tech, everyone’s like, well, what the hell is a genetic mean?
00:28:07:06 – 00:28:28:08
Unknown
Right? It’s kind of like, so when someone says Web3, you’re like, well, I don’t know, like, what does that mean? Right? But for me, it’s just like something that creates has a plan and does multi-step processes. I think you’re going to start to see actual applications of that working, at a, at a, like at a commercial level, whereas today I think most of it is toys.
00:28:28:14 – 00:28:46:11
Unknown
So that’ll be interesting.
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Unknown
No worries. Thanks for having me, Lee.