YouSaid · the spoken record

Matt Fitzpatrick

lines on the record: 93
first: 2025-12-31
most recent: 2025-12-31
sittings or episodes: 1
sources: podcast

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“And what I mean by that is if you take the fact that the models have improved exponentially over the last couple years and you say consumer adoption has been massive, right? Like KBMG had this report that 60% of consumers use this on a weekly basis. The adoption curve on enterprise is not going to be a question of generalizability. It's going to be a question of hyper-specific performance on a specific task, right? And so there isn't actually a benchmark for that. Let's take a investment summary document for a private equity firm, right? There's no benchmark to say firm one, this is how you write investment committee memos, does this generate something that looks with 99% precision like something you would roll out? There's no benchmark to do that. And so that's where what I see as the adoption curve is actually the fine-tuning and inference layer of actually testing that, getting into a place where that firm can say like this looks good. I'm okay with this. You've tested it like machine learning.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“Look, I think the benchmarks are a useful framework for society to gauge progress on this topic. And it's a very often discussed topic. So people want a way to answer the question about the model's improving. And I can tell you unequivocally the answer is yes. I mean, I think by every measure you look at they are and they're not only improving on the benchmarks, but even on specific tasks like research for investments, for example, you can see the models are much better at doing certain tasks. And I think what you're seeing start to happen is people, and we're doing this as well, are building very specific work benchmarks to calibrate certain things like how well does the model do on building an LBO model, for example. And you're going to see more and more benchmarks cited. Now, the complexity then becomes if you move from five main benchmarks, like SweetBench and others, to 600 benchmarks, then you kind of lose track of what's doing, who's doing well and which things. But I think my interesting view on that would be I'm not sure the benchmark progress is what determines enterprise adoption.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“It's true for legal. I actually think a lot of the training work, even to the model builder side now, one interesting view I have is people talk a lot about the public benchmarks. That tends to be one question you get a lot is like, are we reaching a point where models are not improving? I actually think about it very differently, which is the models are now all moving down hyper-specific things where there's not a public benchmark for them by definition, right? Like they're moving to more very specific tasks that are very different and not something you can publicly benchmark in the same way. And that's where we do see more and more model improvement every day, but both in model builders and enterprises on these specific tasks.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“Very niche about this one I use as an example to answer your question. So if you thought of it in that context, you've got a bunch of underwater unmanned vehicles and they're getting in all the drone and sensor data from the interaction patterns of those vehicles. And what they want to know is an object in the water near them. What do they do? Do they react? Do they pull back? Do they alert another drone? Do they engage? What are the topics of that? So fine-tuning a model to take in all that complex sensor data, fine-tune it, train it, and build decision-making framework for those drones. There's a lot of logic built into that. And I think that's why it's been a great partnership with SAIC and Vantor, because we built logic on how to do that. And I think that there is real sustainability and expertise you build up. And so the way I think about our enterprise motion, for example, is every sector is led by somebody with deep, deep sector expertise. And we do build real logic on those topics. And I think the same is true for multimodal video and audio.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, no, I think that if you've learned how to do a certain data task really well, there's incredible value in that. And let's take the enterprise context again, because I do think it's a good one. So I'll give you an example. We're doing a lot of fine-tuning on some pretty interesting topics. One example, we worked with SAIC, Vantor, and the U.S. Navy on fine-tuning a model for underwater drone swarms. And so the question on that, if you think about...”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“So, I actually don't think finite supply matters. And what I mean by that is I think the expertise needed varies so much month to month that if you tried to do a world where you bottled up whatever supply it is, it would change in three months. And we actually relish that concept. I actually think the dynamic, again, why I would use Uber and Lyft, you could use Airbnb and VRBO as the same context is I don't think experts go on five platforms, right? I think actually what you want to be is this is a two-way marketplace where you need enough demand for people to be interested and you need enough expertise that many experts. And I think the reason we get 1.3 million inbounds is because of that kind of supply demand balance. So I don't think this moves to a world. And actually, I would never say it moved to a world where there is one player coming out of this. I think there's benefits to everyone to having numerous players that do AI training. And so it's a question of being one of the players that has that balance.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“Absolutely. I think, you know, five years ago, this space was what I would call cat dog, cat dog, commodity labeling. I don't think anyone, and I think there was a lot of Google Sheets in that era, and you've seen some comments on that, like this sector has evolved the same way most technology sectors do, where it started with Google Sheets and Cat Dog labeling, and it's evolved to real digital assembly lines, huge velocity of expertise, and incredibly specific expertise. So like, you know, we have to give a funny example, we have to be able to validate an architectural expert on 17th century French architecture who speaks French. I mean, that is a complex thing to do on 24 hours notice, right? And so the ability to source, assess, validate, and I think one of the advantages for us is because we have five years of data on who's been good at what task, there's real institutional data memory in how you do that selection and assessment. I think that's one of the core advantages we have from them.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“Work in a really complicated context. Very few companies know how to do that on the enterprise side or on the training side for that matter. And so I thought that was a really unique institutional memory context. It is a digital assembly line, no different than an auto factory. And I think that is a hard thing to replicate. Yeah.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“In the enterprise yet, and that whole process we're in the first inning of. So I think the market demand is going to continue to grow pretty materially for a decade. Hamilton Helmer framework is an interesting one because my favorite example is he talks a little about what he calls institutional memory. He mentions the Toyota production system as an example, right, where Toyota would literally say to people, this is exactly how our factories are set up and nobody could replicate it, right? I think the interesting thing about this space and why you've had a consistent set of folks doing it for a while is to go through the process of every week having to spin up, we have 1.3 million active agents or kind of experts that come into the pool. At any given week, we have 26,000 of those that we've selected that have to start in 24 hours and produce perfect data. Think about the challenge of scaling an organization that for five years can do that at really high quality and consistently turn and evolve to the different permutations of the market, new ideas of training. It's really hard to do. And I think that was what got me most excited when I took the Invisible Job was the question of can you make AI work?”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“With a southern accent. That paradigm is actually incredibly hard to train on. And we're still in the first inning of a lot of those permutations of complexity, is what I would say. For a multi-stage reasoning test that requires a PhD in multi-different languages and human feedback is going to be important in that for the next decade. I have a strong belief on that. And that was actually one of when I chose to take this job. That was actually one of my core convictions is the enterprise is going to need that too. Because actually a lot of if you take legal services, for example, a lot of the way you're going to need to validate that is with legal expertise. There's no corporate information you can train from. So I would start with the idea that I think the market tailwind for the next 10 years, we're actually in the first inning because there's the LMs, then there's the more sophisticated enterprises and then there's everyone else that needs to train, validate, and move to fine-tuning. So again, contrasting, there's like the pre-training and LM work, but then to fine-tune a model to a specific context, most companies don't even know what that is.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, so let me take that. I'll actually start with the market context and then I'll actually use Seven Powers because it is a great book. I'll use one of his frameworks for that. I think the market context that is somewhat misunderstood here is the way that human data becomes more and more important over the next decade. And I think the reason for that is if you thought of the different types of things you could train off of. So synthetic data gets mentioned a lot. But like most of the time synthetic data is useful for things like, let's say base truth information like math where there is a clear output that is right or wrong. Now let's take all of the different reasoning tasks, like a multi-step reasoning task. Like, I mean, even a simple one, like what movie would I select based on, you know, these five preferences? And then let's take that question and add into it audio, video, multimodal language, the ability to do it in 45 language, language context. So the ability to think about computational biology in Hindi versus French versus English versus English in”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“I think it's an exaggeration. I think in any, if you think about classic economics, people are willing to pay a fair price for good data. And so I don't think we operate in a model of trying to give anything unreasonable. I think there's actually fairly standard price bounds across all the players here.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“I think people are willing to pay for good data. That's my simple friend. If you think about the importance of these models, if you think about the cost of compute that is actually a huge chunk of the cost base, if you think about one week of bad data burns a lot of compute, I think what we've seen, the reason it's been the same four to five players in this market for a couple of years now, is it's really hard to do well. And so people are willing to pay for good data. And so I think we have a very collaborative dynamic with all of our customers on that front. I think that when you provide a service that's helpful, people are willing to pay for it. And if you provide a service that doesn't work, people don't pay for it. And so the interesting thing I would say on that front is the discussion topics anchor around, again, proven value. So we'll get a topic that'll come in like a multimodal audio model, for example, and we'll go head to head with somebody on that week. And at the end of it, we win or we lose. And so if you win and your data is way better, people are willing to pay for that.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“Statistically validate for an enterprise use case like claims processing, it's the same motion. Like, I actually think AI training will be used next in banking and healthcare and then after that in many other different enterprise contexts. And so the historical business I took over in 2024 was pretty materially weighted to the AI training side of the house, but I came in with a thesis that enterprise would be a huge source of growth and I think as you see next year evolve, I think we've confirmed 12 enterprise deals in the last 45 days. So we see pretty good momentum on that side of the business. I think that's where we will evolve is to doing both. I think the five core platforms we have allow us to serve a whole host of different end markets. And I do think that's very different than the other AI training players you mentioned. I think we're the only player that spans that broad-based view in the same way.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“I actually think the AI training space has many different players that do have many different business models within it. There's four to five, but actually they're all quite different. I think of us much more as an AI training platform than just a talent marketplace, meaning we have 1.3 million experts that come through the marketplace, but a lot of the expertise we've built over the last 10 years is the ability to, here's the simplistic question, I think, that AI training asks. You have to be able to source any expert in the world in 24 hours notice. You have to be able to source a PhD in astrophysics from Oxford, put them into a digital assembly line in four days later, generate perfect statistically validated data that will be compared head-to-head somebody else's data and make sure that that is perfect at the end. That is an incredibly difficult thing to do. And so actually a lot of what I saw when I took over Invisible was that motion was incredibly applicable to actually the next phase of the enterprise as well, which is the fine-tuning motions, the training, the ability to sit.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“But machine learning has been around the enterprise for I was building machine learning when I was 10 years ago. That's always been a motion that looked like this. So what's happening now is we're starting to realize that the Gen AI adoption paradigm in the enterprise works the same way that ML did.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“Every one of the major insurer techs like a Duck Creek. What they have is a set of core data schemas, a series of analytical logic and a front end. And the ones that did really well had momentum and push from the SIs that got them going. And so their economics were geared by having somebody else do all your services around what you did and then you got something up standing up at the end that worked. I think the challenge with GNAI is that motion doesn't really work because what ends up being built at the end of the day is something that is hyper specific to that customer. Like if you actually think about the nature of fine-tuning an LLM or creating a knowledge management system, it's not a box. It's not. It is something that uses a lot of different consistent tooling, but it has to be customized. And so the way we do that is we stand that up, we get it working. And at the end of it, usually two to three months in, the payment happens when we pass user acceptance testing and validation, and it works. And here's the other thing I'll say is we use SaaS as a paradigm because that's how softwares work.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“Set me back for a second. I think an interesting thing if you look at the economics of Sassan Enterprise five to ten years ago, and I think it's an interesting look at any large public enterprise software business and then look at how much of their revenue is actually services. And I think you could kind of argue that out of the box software has always been a lie to some degree. It's a weird thing to say, but they always had a ton of configuration and they just dressed it up to some degree. I think SaaS was even more challenging than that because often the unit economics of SaaS you're selling a much smaller cost per customer. The SaaS businesses that worked was actually about selling something where the out-of-the-box setup was quick enough that you could make it work with a sales team where you didn't have to do lots of configuration because the minute you had to bring in FDEs in a SaaS context, your economics broke in instantly, right? And what I'd say then on the enterprise side, the way people made it work was that's why Accenture grew so much. That's why cognizant. That's why TCS grew so much is I'll give an example, like if you take insure text as an example.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“I think it depends a lot on the nature of the business and what you're trying to build. If you're trying to build a knowledge management system of public filings for finance, for example, you don't need FDs because what you're building there is a repository of information that people can access. You've seen similar things in healthcare, for example. If you're trying to change workflows, you do need FDs. I think that's the simple paradigm difference in my mind. If you're building something where the hardest part is getting adoption and workflow embedding and you need to actually change the way a company works, then yes, for deployed engineers are the only way to do it. It's interesting. There aren't that many folks that have expertise doing that. So it's a hard thing to train and learn, but I do think it is the only way to get the enterprise working.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“I think it goes back to my general premise that the best way to differentiate in this market is to prove that your tech works. And so the way that we do this is we say you will pay when the software is up and running and we're able to do with one to two person small FDE teams a lot. And so once that's stood up and running, then we do have ongoing software that is, you know, I think the paradigm that we're evolving from is over the last 20 years, you had kind of the system of record layer was where a lot of the value sat. And what we're building is hyperpersonalized system of agility layers, kind of what sits atop that. I think the Accenture paradigm is what people are afraid of, and it's very hard to convince somebody you're going to pay time and materials until it gets working. And so I spend less on sellers and more on four-deployed engineers. That's my simple math.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, one thing I'll say is forward deployed engineering has come to mean a lot of different things. So a lot of forward deployed engineering, I think, across the broader market is more like kind of solutions engineering where the people that kind of answer your questions and show up at your office. I think for deployed engineering done well is executing a very specific workflow build. So you're effectively configuring a set of core platforms to build something hyper specific for that customer. And usually one of the questions is it depends on how good your platform is because, for example, you could argue Accenture is forward engineering, right? But that build may take three years. And in our case, I think we've built modularity and built a lot of the new software workflow development workflows into what we do. And so usually our four deployed engineering motions are about three months. We will come on board.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“I don't think you can. So we've doubled down. A huge part of what we do is for deployed engineers. So we now have eight offices, eight cities, 450 people. We're fully focused on four deployed engineering. And I can tell you from a decade in my prior life, you just cannot do this without-of-the-box Saess. It does not work.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“And to fine tune a model to do that. And then we actually do also on top of that build lots of specific custom agents for things like scheduling. So what you get at the end of that is a transformed tech enabled business with all of those different components. Now that does take us a little while to stand up, but once that is there, it's effectively hyperpersonalized software. And that is my view on where this whole industry goes is you move from SaaS out of the box SAS to much more hyperpersonalization using the specific data of an individual customer. And that is what we do.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“The US and internationally. And what we're doing for them is we're building them an entire tech backbone where they have an enormous amount of fragmented data across EHRs, CRM, ERP systems, notes, everything else, all of their data sits in a pretty fragmented format. And so we're using Neuron to bring all that data together. We do that very, very fast. So if Accenture would take two years, we can usually do it in two to three months. We're then on the back of that building a lot of different intelligence and reporting so they can look at things like patient journeys over time, labs, genomics data, how much you use like the Aura ring or anything else like that, but they want to look at wearables, how all that content is looking. So they have a lot of detail on what any patient is doing at one time. And then on top of that, we layer things like we have the ability to interrogate the data and ask lots of different questions, like, let me look at who's used peptides. It's a male between 36 and 50 and what have been the results. So we're using Axon to build all that. And then we build.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“It is and it's not. So let me give you an example of how one of our deployments works because I think fair enough if the answer is that it takes you two years to build anything. But I'll give you an example. So our AI software platform is effectively five modular components. So Neuron, which is our data platform, brings together structured unstructured data. Axon, which is our AI agent builder, Atomic, which is effectively a process builder, we can build any custom software workflow. And then we have a Meridial Expert Marketplace, which is we have 1.3 million experts a year on any topic you can imagine that we bring into those workflows and then Synapse, which is our valuation platform and all of it. Now, we can take those five things and configure them to almost any different enterprise context. So just an example, we serve food and beverage, public sector, asset management, agriculture, sports, oil and gas, a whole host of different sectors using that same modular architecture. I think we end up scaling pretty materially once we show what the tech works. We're working with a company called Lifespan MD, which is a concierge medicine business.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“Risk, right? So I think the simplest advice I give, and by the way, this is how we sell quote unquote, is start with proof of concepts, start with we call solution sprints, don't pay a dollar until you prove the tech works. So like we don't actually sell anything. We meet a customer. We say we will do it for free for eight weeks and prove to you the tech works. And that's a very simple way. If your tech works, you'll show it.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“I think this is the other big challenge of Gen AI adoption you're an average CTO, COO, you've got 250 of vendors a week pitching you. All of them sound pretty similar. In fact, I was with a customer yesterday who literally started the meeting by saying, how are you different than the other 250 people that have pitched me this week? So this is the dynamic of we have an oversaturation of companies that all sound relatively similar relative to agents. To make your question even more pointed, a lot of them don't work. I think you've got a fair number of the enterprise Asian companies that like Salesforce AI research releases this report that if you test a lot of the out of the box agents on single-term and multi-term workflows, they're about 58% accurate on single turn and 33% accurate on multi-term workflows, which means they don't really work. And so you've got this challenge of 250 companies a week pitching you. You don't really know how to select it. And you're worried you're going to pick someone as effectively Charlatan and it won't work. And the more you have a market where there's a lot of excitement, the more you do have that.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“Don't locate it in the tech function. That's the main advice I give people your Gen AI initiative should be led by the business and figure out that could be your head of call center, that could be your head of operations. But each of those people with clear operational KPIs will get their stuff working. And there are a bunch of companies that have, but it's just a very different approach than I'm building Gen AI as an example.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“And it's an interesting concept, right? Because what ended up happening is you bought 50 apps, you had Accenture come in and you paid them $200 million over two years to try and layer them all together. And often you ended up a couple years in with no working data, no linkages between them. And that kind of layers of sediment has been how the tech paradigm worked in the enterprise for the last five years. And I think what's different now is if you're thinking about a specific Gen AI initiative like a contact center, let's say, you don't need to operate that way. You can think about what are the operational metrics you want in your contact center. You want to think about call resolution, call performance, cost per call, routing logic. You know, you can then look at both internal and a set of vendors who will deliver those metrics and make an evaluation. And if the vendor doesn't work, you fire them. And I think there's a very clear way to get ROI in this, which is figure out the list of three to four things that move the needle for your business. Focus on those three to four. Don't spend money on a thousand science projects. Take your best four operational leaders and put them on those four things.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, so I think one misconception is that that leader has to be highly technical to make that decision. And I would actually argue they don't at all. They just need the same muscle memory they've looked at in the past, which would be, what do you need to get a Gen AI initiative working? You need good data that you can work off of for that specific initiative. clear milestones and outputs, clear line ownership of the initiative, and then probably most importantly, you want to actually anchor it in milestones and outcomes where you pay as it works. So I think the other interesting context for a lot of this is what I would call the Accenture paradigm of the last 20 years, right? Which is a lot of times the way that if you think about the wrapper that's been around software for the last 20 years, our founder, Francis Berdaza, has the founding principle of Invisible was if there's an app for everything, how come nothing works?”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“It and I said at the end of it, how did you define if this agent worked or not? And like, well, we built, we built our own eval tool. It's not a joke. And we basically analyzed a mix of speed of call resolution and sentiment. The problem with that is what if the agent hallucinates and says, here's $2 million, that actually gets resolved quickly and the person's happy. And so they had built this entire system from first principles and what ended up happening was a couple months later they shut it down and moved back to a deterministic flow. And that's not surprising to me at all. And so I do think that's a little bit of the adoption curve we're in is over the next two years, you're going to see the CFO function put different guardrails on how this stuff is built and say, what is the ROI? What are you investing in? What's the metric? What's the return? And that will change the adoption curve. But right now there have been a lot of science projects. I think that is a realistic.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“Look, I think the amount of talent that knows how to do this well is not large. And so that finite group mostly works in AI startups of various forms, right? And large tech companies. And so I do think there's real risk to the process of figuring this out from first principles and enterprises, right? And I think that's part of the cycle that we're going through right now is a lot of internal groups have gone through the process of saying we must do this all internally. But the reality is if you think about that this is an open architecture ecosystem and you're going to adopt things like MCP or all the new voice agent that comes out, you actually want a modular open architecture where you can use all the best tech available and figure out how to link it together. And I think the desire to shape that all internally has been challenged. I'll give you one of the more interesting examples I can discuss. I was talking to an e-commerce retailer that had built an agent to handle their returns process. And they spent $25 million building this agent. And at the end of it, I said, well, how did you define, this was, I met them after they built it.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“And I don't think that discipline exists in the same way in internal builds. I also think that the talent levels often the internal teams have are challenging.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“So it's interesting if you look at the MIT report, which is the one I mentioned that says 5% of models are making a production right now. They actually cite a stat that externally driven builds are 2x as effective as internal team builds. I actually think there's an interesting kind of 10-year pattern on this, which is 10 years ago everyone bought software. That was your tech team did not try and build anything and you started to buy and you bought, you know, often you bought way too many apps, but you bought 15 different apps, and that was what the technology team did. And then I think with the advent of cloud, you started to have a world where the technology function started to start to think about building things. Like maybe they started to have some custom applications that wrapped around that. I think Gen AI has 5X that. We're now an internal team has given this enormous budget and said kind of go have at it. And I think that's complicated because I think when you hire somebody to build any vendor of any kind, you're pretty disciplined about what are you delivering on what timeline? What's the ROI of it? What are the milestones? How does that?”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“Yes. Yeah, it's a great question. I think it depends a bit on the sector. I think there are sectors like banking that are very focused on building this internally. I think that is a reality.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“The data infrastructure to support those models, it's the redesign of workflows, it's the process figuring out which operational leader takes accountability for that. And most importantly, it's trust, it's observability, it's all the things that I spent a decade building things like credit models in banking. And in those cases, you need to go through model risk management, testing, training, validation. And so I think that whole process is in the first inning in the enterprise. I think it's going to take a decade, not two years. And I do think that is the core mission that we think a lot about is I actually think the evolution of deployment of AI will be what the model builders have done for the last couple years. You'll see banks and healthcare firms start to do the same sort of testing and validation over this period. And then the rest of the enterprise will be over the next five, six years after that. And that's the journey that we're focused on.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“That's a great piece of advice Yeah, and let me set the context, and I'll go into more detail later. But Invisible is an interesting business in that we both train all the large language models with reinforced learning human feedback, and we are at the core and a modular software platform where in enterprise context, we deploy all different enterprise use cases. And I think the cognitive dissonance that has occurred over the last couple of years is model performance has increased exponentially. I don't think anyone would doubt that. If you look at all the public benchmarks, models have increased 40 to 60 percent in performance over the last two years. And consumer adoption has been also exponential. So KPMG just released that 60% of consumers use Gen AI weekly now. But the enterprise has not. I think in the enterprise MIT just released this report that 5% of Gen AI deployments are working in any form. I think you've seen Gartner saying 40% of enterprise projects will likely be canceled by 2027. And I think the reason for that is deployment of the enterprise is a lot more than just models themselves.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“Walked him through the opportunity. I said, listen, it's big risk. And he goes, The only risk is if you don't take this and the amount of regret you'll have not given it a go.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“I'm not a particularly materialistic person. You know, I think when I was coming out of college, for example, everyone was focused on going into large finance jobs, which at that time were pre-financial crisis. Obviously, where a lot of that was. And I think a lot of what I think about is doing work day to day that I really enjoy with people I really enjoy and then building something. And I do think I really enjoy the decade I spent building at McKinsey. I think that was an incredibly interesting experience to stand up something of that scale within an existing institution. And then I do think about I read a ton about everything from military history to current entrepreneurs to enterprise executives I really admire. And then I have a group of kind of a small group of people whose opinions I ask pretty regularly and probably the most telling piece of advice my girlfriend and my main mentor both of them when I asked within two minutes were like absolutely do this my main mentor is a guy named Sesh Khanna who had been a senior partner at McKinsey for a long time is on the board of a whole variety of different companies today and I remember we got lunch”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“Look, I think when you walk away from a really stable job that you really enjoy, that's always difficult. The sliver of McKinsey that I was doing, I found to be one of the most intellectual day-to-day jobs ever. I was working with all the Fortune 1000 on every different AI topic daily, and particularly in the early machine learning days kind of 10 years ago, I think we built some really interesting stuff. But yeah, I think it was kind of a no-brainer in some ways because I think when you think about it, I think this is the most interesting time to run a company on a topic that has probably existed in our lifetime. Maybe the 2000s, but to run a company in AI right now is fascinating, the rate at which you can build, the people at which you can recruit, the interest of customers in this topic. And so I felt like I'd spent 10 years learning one topic. And now I had a chance to run a business and build it the way I wanted to build it on that topic. And that's just something you can't pass up. And even though, you know, walked away from a fair amount, but I think that I'm much more excited about building something for the next two decades out of this.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“They don't talk about it for two days, which is exactly, exactly. But I actually think it's one of the few events I've been to where people are not talking their own book. They're not trying to convince you of anything. And you just really actually, I've made a bunch of really good adult friendships out of that. And so Francis and I got to know each other from that four years ago. And there had been another CO kind of in the two years before I joined who was actually based in Australia, interestingly. And so when the business got to a certain scale, it was just time to have a US-based CEO that could help take the business to the next level. And it was actually Francis just approached me and kind of pretty directly said, do you want to be our next CEO? And that was kind of, that was kind of what happened.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“It's in many different locations. I really enjoy it because you actually don't talk about work at all. You're not allowed to talk about your job. You spend time talking about history, politics, technology.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source
“I would say my McKinsey journey was non traditional. I spent 12 years there. I was a senior partner, and I led a group called Quantum Black Labs, which is the firm's global tech development group. So about 10 years ago, McKinsey actually started hiring engineers, and I was a big part of this and a pretty big quantum. And when I started made about 100 engineers total infirm, by the time I left, we had 7,000. I oversaw about a fifth of that group. And all the application development, all of the data warehouse infrastructure and all of the Gen AI bills globally. And so that journey was really interesting. And over the course of it, spent a variety of my time competing with other large enterprise AI businesses. And I got to know the founder Francis really well about three years or four years ago now. We actually met totally not work related kind of social context where we were discussing it was basically a forum called dialogue. I don't know if you've heard it, but you basically talk about different ideas.”
2025-12-31 · The Twenty Minute VC · 20VC: Enterprises Will Not Adopt AI without Forward-Deployed Engineers | Who Wins the Data Labelling Race: How Does it Shake Out? | How Synthetic Data Threatens the Future of Human-Generated Data with Matt Fitzpatrick, CEO of Invisible Technologies · IDENTIFIED FROM THE TRANSCRIPT · source