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- [00:00]
Danny Fortson
This episode of the Times Tech Podcast is sponsored by Adobe Acrobat Studio.
- [00:05]
Times Tech Podcast Announcer
A lot of us lead very busy lives, including the tech bosses you hear from. On this podcast. We're dealing with more information than ever before, often across disconnected tools and working in hybrid teams.
- [00:16]
Danny Fortson
If this sounds familiar and you're someone whose life involves scrolling through contracts, reports or pitches with important data buried in long documents or different sources, then you'll know it can sometimes be a struggle
- [00:27]
Times Tech Podcast Announcer
to keep up, or at least to do so in a timely way.
- [00:30]
Danny Fortson
Adobe, the company that invented the PDF back in 1993, is changing that with Adobe Acrobat Studio. It's a modern workspace designed to help you work smarter and save time.
- [00:40]
Times Tech Podcast Announcer
Acrobat Studio isn't just for essential PDF tasks like editing or signing documents. It's an AI powered space built to help you use simple language prompts to get information quickly from multiple documents and sources, including PDFs, Office 365 files and web pages.
- [00:56]
Danny Fortson
It's for people with busy, demanding jobs who want to spend less time on
- [01:00]
Times Tech Podcast Announcer
admin and more time on the work that really matters.
- [01:03]
Danny Fortson
Check out Adobe Acrobat Studio and its new features now.
- [01:06]
Times Tech Podcast Announcer
This episode of the Times Tech Podcast is sponsored by PwC.
- [01:11]
Danny Fortson
How do you use AI in ways that drive real business value? It isn't just about the tech, it's a new way of thinking going further, faster. This is where PwC comes in. Shaping AI to fit your business to help you innovate with impact, empower your people and accelerate growth. Working with you side by side, bringing deep industry know how with expert change management to unlock real value and drive lasting impact.
- [01:37]
Times Tech Podcast Announcer
PwC knows how your business works so you can put AI to work for your business. Discover more at pwc.co.uk
- [01:49]
Danny Fortson
hello, I am Danny Fortson and this is the Times Tech Podcast. Once again I am writing solo, but fear not Ken, Katie Prescott, my fabulous co host who's been out for a few weeks now. She's gonna be back next week, I promise. But in the meantime we're continuing, we're soldiering on. For this week we're talking AI. In the past few years there's been ominous predictions of a quote white collar recession as companies start replacing more and more of their human staff with AI. Darya Amadeh, the CEO of Anthropic, friend of the pod. He recently predicted 50% 50 of entry level white collar jobs could be gone within five years. And you're certainly seeing bits and pieces of that out here where you see the big tech companies Growing very fast, but also cutting staff. And there was a really interesting note that Satya Nadella from Microsoft just put out talking about the irony of being a fast growing tech company, while also he's cut 15,000 jobs this year. People were really kind of freaked out by it because he's like, look, we're doing better than ever. Record profits, record share prices, things going like gangbusters and people need to do more with AI. Basically he can do more with less. It was a real just kind of moment for one of the largest companies on the planet to be like, this is the irony of running a successful company with the arrival of news technology is that we can get rid of a bunch of people and we can still do quite well. So, you know, pretty terrifying for anybody in a desk job. And it's clear that some white collar jobs will be hit harder than others. But what's on the chopping block, you might ask? What is kind of like the front lines? One possible area, the law. So much of being a lawyer revolves around combing through huge mountains of documents, making sense of them. And this is something that AI tools are particularly good at. Goldman Sachs predicted that 44% of legal services could be automated in the future. So real sea change coming for that profession. And at the heart of this change are companies like Luminance, which is another UK based startup like our friends from Limbic last week. And they complete tasks that once took lawyers hours, they can do it in seconds. And they're really centered on contract review and really focusing on lawyers inside big companies who, you know, can spend days and days and days and days just going through contracts. They basically become an expert on a company's data and then use this to mark up and analyze incoming contracts, flag risks, make sure everything aligns with the company's goals, et cetera. You can think of them as kind of a synthetic in house legal brain on steroids. So it's a really interesting idea. And Luminance is run by their CEO, Eleanor Lightbody. Luminance just raised 75 million dollars at a 400 million doll valuation. They're growing like a weed. And so I want to explore this kind of brave, ish new world of legal AI and the shock that is actually reverberating through the law industry as we speak. How long before we don't have lawyers anymore?
- [05:10]
Eleanor Lightbody
Oh, how long until we don't have lawyers? I think, sadly for your listeners, we are quite far out on that one. But how many lawyers is a different question. Machine learning's been around for a Long time. And AI actually has been around for a very long time. And I think that lawyers were. Well, I know that lawyers were using machine learning tools since they were on the market, but the rate of adoption has massively accelerated with the introduction of these generative models. And why is that? I think because previously limerence and whoever was building technologies for law firms or flaws were slightly capped with what they could give their end customers. And so I think that what they were doing is that they were probably, they were, they were producing results that were almost, that were 2x beneficial to the customer. But I think to change behaviors and to really get people using technology on a daily basis, you almost have to see a 10x in productivity. And that's what the introduction of LLMs into these systems created. This is that you almost like crossed the chasm and suddenly it was like, okay, this is no longer nice to have. And I'm only going to use it on certain situations where like it's not feasible to hire hundreds of lawyers to. I want to use this every single day. And I can see more and more value the more that I use it.
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Danny Fortson
Yeah, it has to feel almost like magic for people to be like, yeah, okay, I'm going to use this now.
- [06:36]
Eleanor Lightbody
Yeah, we always talk about, about the hook. What's going to drive someone to keep on coming back? What is it that it did today that it didn't do yesterday? What value is it providing you that you might not necessarily have thought about? And actually the legal profession is a really interesting one because a lot of the work, as you said, it's text heavy. There's a huge amount of information that you can start learning from. But actually a lot of the work that we focus on in house legal teams, a lot of the work in house legal teams are faced with on a daily basis is pretty repetitive. And they were coming to us and saying like, oh, we've got mountains of work that we're having to hire many paralegals to, to do and many kind of first year, second years to help out with. But they're not getting to the work that we want them to get to. And so I think that's what's really drive the usage. Originally 2 years ago it was like, I want to focus on the low value, high volume work. Now obviously that's changed and it's being used for a much wider array of use cases. But that was the start.
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Danny Fortson
Well, speaking of the start, can we go back to the beginning? Because you guys have been doing this AI thing before. It was cool.
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Eleanor Lightbody
It Was trendy before.
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Danny Fortson
Yes. So what year did the company start and what was the idea then?
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Eleanor Lightbody
We're celebrating our 10th year anniversary.
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Danny Fortson
10 years.
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Eleanor Lightbody
10 years, Danny.
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Danny Fortson
I haven't been as a tech startup. That's like. You guys are like a dinosaur. That's crazy.
- [07:54]
Eleanor Lightbody
I know. And we're still here, which is. And we're growing at, you know, 5x Ari over the last year, so growing faster than ever before, which is really exciting. Ten years ago, it was founded by two mathematicians from the University of Cambridge who were to speak very openly, I think quite fed up of conversations that they were having with friends of theirs who are lawyers, who were complaining about the hours that they were putting into huge pieces of due diligence work. And so they looked at each other and they thought technology is going to help humans get through data faster. Like that's inevitable. And they created the first iterations of Luminance and took it to a law firm here in the UK called slaughtermate, one of the most reputable law firms. And Slaughters were so impressed with the first platform that it not only became our first customer and gave us access to their data so we could start training, but also became one of our first early investors. And the first five years, the team really focused on selling to law firms for a few reasons. The first one was that they knew that data was absolutely crucial in this world. And this is before most of the world knew. Today we talk about how valuable data is, but three years ago ago, no one really knew how valuable or no one really thought that. So we're getting access to this very, very rich data set, which for legal, we can talk about this later, but is super, super important because you want to build a specialized system that understands whether a question is right or wrong in the legal context. The second thing is that because lawyers were using it, it was getting trained on the fly. So every single time a lawyer was kind of logging in and verifying things or teaching it, our systems got smarter and smarter. Then of course, the instructions of transformer based models, generative models, we were able to adapt very, very quickly because we've always been in the AI space. And about three and a half years ago, we were seeing that many more in house legal teams were coming to us and saying, what you're building is really useful. Actually for us, this is not just an M and A platform, but we want to use you across all of our contracts, whether that's creating contracts, whether that's negotiating contracts, or whether that's finding key information within your contracts. And so we expanded out to work with in house legal teams and that's the product that's just flown off the shelves. I'm saying metaphorically because Obviously it's a SaaS platform.
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Danny Fortson
There's no shelf.
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Eleanor Lightbody
Exactly. There's no shelf flown off the website. And we've welcomed the likes of DHL Alliance, Koch Industries, Maryland and many more. So that for us is really what we're focused on and that's building these legal brains within organizations to understand the organizations, understand the legal departments, understand the legal user, and can help automate and augment that every single interaction that a team might have with a contract on a daily basis.
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Danny Fortson
But going back to that 10 years ago, were you guys like a voice in the wilderness?
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Eleanor Lightbody
Ten years ago there was a lot of work on educating the end user and there was a lot of skepticism, much more so than there is today. And so the teams really had to focus on what was the value and what was the future value of this as well. Because the end users now, today you go in and you can ask any questions and even if it hasn't seen anything, it will give you an answer. Whereas 10 years ago, if the systems hadn't seen something, you'd have to train it on the fly. So it's a lot of like, okay, how do we get this bespoke and smarter to you as an organization?
- [11:20]
Danny Fortson
How did the arrival of ChatGPT change things? Because obviously it, broadly speaking, woke the world up to AI. Everybody's like, oh my goodness. But Luminance by that point had been around for 7ish years. Did it allow you guys to do new things with the product or show you the way and how much of it was just the awareness of, oh, we are now in the AI age, everything is going to be AI. So customers are all of a sudden like, we need to figure out what we're doing here.
- [11:50]
Eleanor Lightbody
I think it's a combination of things. The first thing is, is that ChatGPT was the thing that woke everyone up to it. But we had been using Transformer based models for a year or kind of 18 months previous to that. So our customers had been interacting with generative models through our platform for a while before that. ChatGPT helped spark everyone's imagination. And in one sense that was incredible because the things that you could start doing with. And it's not just chatgpt, you know, whether it's Gemini, whether it's. There's so many different models that you can use for different tasks and actually some are very good at certain tasks and Some are better at other tasks and it's actually how you orchestrate them that gets you the best outcome for your customer. Especially in legal, when like accuracy is the most important thing. So it worked everyone's imagination to it what we could do with our platform. Obviously the value increased more and more to our end users. And what's incredible is even just this year the questions that have been asked on the platform have increased by 40x. I couldn't quite believe that number. I was like 40x in the space of 6 months.
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Danny Fortson
Wait, what has increased by 40x the
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Eleanor Lightbody
amount of usage within our platform over the last six months.
- [12:59]
Danny Fortson
Whoa.
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Eleanor Lightbody
Yeah, well, I think I was trying to figure out why that is and I was like, maybe it's like to do with the tariffs and people wanting to really understand quick. And actually that was only like a subsection of the questions that were being asked. But I think it's very representative of the growth that we've been on for the last few years. On the other hand though, which is quite an interesting point, which is suddenly everyone thought that they were maybe AI experts. And as you said, it was everywhere in the news that like legal was going to be disrupted. So you had a lot of, a lot of people playing around with models who were building quite specific solutions for very specific use cases. And so there was again another educational piece that we had to do to say, okay, like there's a difference between like a generalist system and that's probably quite useful for certain tasks, like giving you a first draft where you don't need it to be legally accurate, or giving you some advice when you don't need to necessarily trust the citations or trust the case law that's being used. But actually most people now, especially from what we're seeing from our customers, they want something that's going to capture that end to end. They don't want to have like one legal platform for one thing and one legal platform for another thing. They want to have something that's super robust, that helps for any different use case that they might be faced with, with contracts.
- [14:17]
Danny Fortson
And are you building on top of other LLMs like ChatGPT, like Claude, like Gemini, like Llama, et cetera, because there's like this universe of like these kind of general purpose AIs, they call them wrappers out here, where you just put a slap, a new wrapper on it and all of a sudden you have a legal AI and you have a medical AI and blah, blah, blah, and there's a whole like universe of companies doing that. Are you guys in that world as well?
- [14:45]
Eleanor Lightbody
We're not a wrapper at all, but we use lots of the models that you just spoke underneath the hood. So for us, we use some open source models, we use some foundational models, we use some models that we actually built ourselves. And we've got like access to some of the most rich legal data out there, so we can train all of these models. But that's only one piece of the puzzle because large language models are non deterministic by nature. And so what you'll find is sometimes you will ask the same question four times and you might get six different answers. And so it's actually the way that you orchestrate the models together to check each other's homework to make sure that like there is probabilistic consensus in the answers that are being given to the lawyer. Because, you know, in an industry where creativity is really important, like it might not matter that you might not have consensus in the answers that you're getting back. That actually might be a good thing. But a lawyer, as soon as they don't trust the answer that they're being given, you're done. You'll see that rate of adoption. Yeah, massively decline.
- [15:45]
Danny Fortson
The reason I ask is because there's a recent case which you may have seen of this company Windsurf out here, which is one of these AI coding assistants. And OpenAI was like, we're going to buy this company for $3 billion. But Windserve was built on top of Claude. And then Anthropic's like, you know what? We're going to cut off access to our API. And all of a sudden it's like, well, what is this company now? And then Google swoops in and hires a CEO and the top team. And then the company was like, what are we now? And then it got acquired by another company called. It was like this crazy succession of events. But I think it kind of opened a lot of people's eyes to like, well, what do you have in this world where Claude chatgpt these companies are throwing billions of dollars to create these really powerful models that you can either build on top of or, you know, next week Anthropic might be, you know what, here's our new legal AI. It's the most powerful. Blah, blah, blah, blah, blah, blah, blah, blah. I'm wondering how you navigate this world where literally every week it's like, oh, this new model is more powerful than anything previously seen as of a week ago. And it's just constantly evolving like that.
- [17:00]
Eleanor Lightbody
Well, I think that's really, really key. I think it's not being too reliant on one model. As I said, we have all these different models that we use because actually one model is very good at text summarization, but another model will be actually very good at calculating different costs within a contract. Another model is actually much better at understanding the jurisdictions. And so we have like this leaderboard in Cambridge where we have all the different models and what we're like, testing them for. And as soon as there's a model update that comes out, we will check it against everything else. And the key thing here, Danny, is that you've got to not just test for what your product's doing today. You've got to test for. A lot of the conversations I have with our team is like, cool. Of course these model updates are going to hopefully improve whatever we're looking at today. But what can they do that we can't do? What are we building, thinking about what's to come? And that's a really, I think that's a hard thing for businesses. But the really exciting thing, which is it's almost like with chips, you always wanted to build much smaller chips because you know that they're coming. It's like with the models, you know, the models are becoming more and more powerful. So you need to make sure that you're building use cases that as soon as they're there, you can be at the forefront of delivering something that, like, people are like, wow, I didn't even know that this could even exist.
- [18:14]
Danny Fortson
Let's pause there for a moment to talk about today's sponsor, Adobe Acrobat Studio.
- [18:18]
Times Tech Podcast Announcer
Acrobat Studio helps documents work harder, organizing projects, extracting insights quickly, and creating professional content from the files you already have.
- [18:28]
Danny Fortson
It's designed for individuals, teams and businesses who need AI powered tools that are easy to deploy and use.
- [18:34]
Times Tech Podcast Announcer
And Adobe says your data stays secure and isn't used to train its AI models.
- [18:40]
Danny Fortson
So if you want to rethink what PDFs can do, check out Adobe Acrobat Studio and its new features now.
- [18:46]
Times Tech Podcast Announcer
This episode of the Times Tech Podcast is sponsored by PwC.
- [18:51]
Danny Fortson
Every leader is looking for that next opportunity for growth. But as technology and AI reshapes entire industries, the path forward isn't always clear. This is where PwC comes in. Helping you put AI to use in ways that drive real business value. Working alongside you, bringing the deep tech expertise, AI capabilities, strategic insight and industry knowledge you need to innovate with impact, empower your people and accelerate growth.
- [19:19]
Times Tech Podcast Announcer
PwC knows how your business works so you can put AI to work for your business. Discover more at pwc.co.uk.
- [19:31]
Danny Fortson
howdy, howdy ho, and welcome to Fantasy Fan Fellas. I'm Hayden, producer of the Fantasy Fangirls podcast and your resident lover of all things Sanderson. And I'm Stephen, your bookish Internet goofball, but you can call me the Smash Daddy. And we are currently deep diving Brandon Sanderson's fantasy epic Mistborn. But here's the catch. Steven here has not read Mistborn before. That's right.
- [19:52]
Eleanor Lightbody
Hey.
- [19:53]
Danny Fortson
Hey. So each week, you'll get my unfiltered
- [19:55]
Eleanor Lightbody
raw reactions to every single single chapter.
- [19:57]
Danny Fortson
And along the way, we'll do character deep dives, magic explainers, and Steven will even try to guess what's next.
- [20:02]
Eleanor Lightbody
Spoiler alert. He'll be wrong.
- [20:04]
Danny Fortson
News flash.
- [20:05]
Eleanor Lightbody
I'm never wrong.
- [20:06]
Danny Fortson
Episodes come out every Wednesday, and you can find Fantasy Fan fellows wherever you get your podcasts. And how do you navigate this idea that models lie, they manipulate, they make stuff up. I mentioned it on an earlier pod. This woman who asked ChatGPT to help her choose, she's a writer. She's like, I'm gonna make a proposal to a literary agent. Can you read my stuff? It's like, yeah, I'll read all your articles. Blah, blah. And then it turns out, like ChatGPT said, it read it. It actually didn't read anything. It made up the content of which it read, that it then analyzed. It was such an elaborate web of lies. And then when it got caught, it, like, doubled down and said, no, no, I read every word. And then it was like, you know what? Actually, I didn't. I lied. And it was such a kind of colorful example of these things are very good at being confidently wrong. And how do you deal with that? As to your point, in the legal world, you can't afford that the first time a lawyer is like, oh, this thing is making things up, or this thing is just wrong or lying, it's down tools.
- [21:13]
Eleanor Lightbody
Yeah, absolutely. So I think the two elements of that. The first one is getting the different models to check their own homework. And so, like, if you've got eight different models all saying the answer is the same, then you can pretty much confidently think that the answer is the same. But if there isn't probabilistic consensus, we actually have, like, on top of all of our models, an orchestration layer. And it's almost like the supreme judge who basically looks through the answers and goes, you know what? I'm actually not sure that you guys are correct on this. And so I'm going to hand it back to, to the human. There's a huge amount of work that we've done so that if the AI is not sure in the platform, it will color code something yellow and it will say this cause this answer.
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Danny Fortson
So there's like an AI judge judging the other AIs.
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Eleanor Lightbody
Exactly. And that AI judge is not an LLM.
- [21:59]
Danny Fortson
Got you. The other thing is, you mentioned it earlier, it's like, well this thing has to be like 10x better than anything that's come before. And I don't know if you saw there was a recent study by this company meter of AI coding assistance because coding is another like area where there's been a huge amount of kind of investment and hype and excitement. And it found that, it did a study of human coders using AI coding assistance and it found that they're actually 20% slower than people who are not using assistants. And I probably because that's something to do with them like double checking or triple checking or maybe they're just still trying to figure out how best to work with it or whatever. But it wasn't like this kind of night to day revolution of like oh my goodness, now I can just do twice or ten times as much work or whatever it may be. Does that ring true at all? Do you see any aspects of that as people start adopting these things?
- [22:56]
Eleanor Lightbody
Look, I think first of all there's a lot of hype. So cutting through the noise and trying to understand what's happening. We always talk about return on investment. What's the business case? Why would someone adopt this rather than it just be kind of a new egotistical thing or something that you're like this is great, but like actually can't quite communicate what the value is when it comes to things like coding. We obviously use AI to help our developers, but we've seen that with our experienced developers it will have a huge amount of impact. But with our junior developers, that's where it just causes a lot more time to get code out there. And we do triple checking code review. And so I haven't read this report and I'd be interested to read it. But for us there's definitely a, there's a difference between who's using it and how they're using it. And then again to check tests and to like write pretty like mundane code. Super efficient. But anything that you want to be like super, like slightly more creative or anything that you're introducing to maybe like a Web of complexity, then yeah, someone that knows that code base better is still more efficient.
- [24:03]
Danny Fortson
Are there any parallels with, you know, junior lawyers versus very senior lawyers using your software?
- [24:11]
Eleanor Lightbody
Weirdly, I see the inverse, because with junior lawyers, a lot of us, you know, regardless of whether you're a lawyer or not, you learn through repetition and you learn through insights. And so the great thing about junior lawyers using luminance is that the AI will tell you why another user has done something in the past and how they've done something in the past. So actually it can upskill them at much faster rates. And also it then allows for businesses to have assurance that, like, institutional knowledge stays within an organization.
- [24:42]
Danny Fortson
What do you mean?
- [24:43]
Eleanor Lightbody
I mean like, AI is not going to leave you. Let's hope it's not going to leave you unless you stop paying for it. And then we'll, we'll cancel your subscription and we'll take all the learnings away from you. But it's there and it, and it gets more and more powerful and it learns like, why you as a business have done things and why as a user have done things. And so should someone leave, someone can pick up where they left off very quickly and get that in depth understanding. And it also doesn't sleep. It has that like longitude and latitude, context and memory. So I almost think that in legal it's even more powerful to a certain extent.
- [25:17]
Danny Fortson
Is it kind of like, I think one of the best businesses on the planet is like a therapist, because if you start therapy, you spend the first six months sharing all of your family history and your deepest, darkest secrets, and then this person knows you and then that like, then they can advise you. Their institutional knowledge of you is set and there's a whole lot of work involved with that. And you're like, I don't ever want to have to find a new therapist again. Is that kind of the luminance model? You're like the AI legal therapist of, like, once we know your organization, you're never going to leave us because we're just going to get smarter and smarter about you.
- [25:51]
Eleanor Lightbody
Well, I would hope that unlike a therapist where it might be a love hate relationship, that you might have a love love relationship with the Lumen and that you wouldn't entertain thinking about what was next. And therapy always has an endpoint. Well, you would hope that therapy has an endpoint, whereas with Lumen we had customers for many, many years. So yes, to a certain extent, but it's beyond that because it doesn't need six months to learn who you are. Like all you have to do is upload your existing contracts and upload your playbooks and your precedents and then it gets a very good understanding from day one on what you've done, why you've done it. Now, of course, if you as the end user are seeing new complex contracts that the AI has never seen before, every single time you interact with it, the more that it learns from you. And obviously that has that reinforcement learning into it. But unlike kind of legacy softwares where you almost had to like wait six months, months to get started, this people can try like totally for free and tomorrow they can start seeing value from it.
- [26:48]
Danny Fortson
I want to talk about humans and staffing because this is the other big question, right? Everybody's freaking out like, there's never going to be a human smarter than a machine ever again. On some, like, you know, I guess IQ level, that's probably true, but I think it's a little facile to be like, well, therefore, if that's true, then we're all going to be put out of a job sooner or later if it has to do with anything to do with like kind of white collar or kind of thinking, quote, unquote jobs. How do you see this playing out? Or what are you seeing already with your clients that are using this, using it more, as you say, the 40x increase in the last six months, which is, that's an astonishing figure. Like, how do you start seeing that trickle through these organizations?
- [27:32]
Eleanor Lightbody
I obviously think about this quite a lot and I still come back to this idea that humans, we love to make work for ourselves. We have traditionally time and time again. And so it's not necessarily clear what that work might be. But I do, I back us humans in finding a way to not sit on a beach 247 if we wanted to. I suppose. What are we seeing in practice? Well, it depends on the company. But you know, you've got lots of companies who are saying, I just haven't had enough time to do the job that I was hired to do in the first place. Like, you know, if you think about a business, it's people, contracts and processes. And a lot of the contracts have rich data and like rich insights into how that business is doing, how it's operating, where it should go next. And actually lawyers and people adjacent to those have this very unique opportunity to be business enablers, to be strategic advisors. But if you speak to most people, they're like, I'm just spending time churning quite similar contracts because that's what I really need to do. So it's opening up this whole new area of work that is actually probably more interesting and why some of our customers got into law in the first place. Second to that, I think you'll start to see roles blend and change. So, yeah, you might see less paralegals, but you also might see more legal data analysts. You might see many more people be introduced to the environment to think about, okay, I've got a legal AI platform here and I also have a CRM here. How do they talk to each other like, and how do I make sure that they are, you know, and I've got agents now for my legal agent and I've got my API agent and I've got my, my search agent. How do those all fit in and how do I make sure that we're, we're delivering value for the business? So I think whilst there might be reductions in some areas, I would see, and I have started to see kind of either roles change and morph into other roles or totally new roles be introduced.
- [29:37]
Danny Fortson
Any totally new roles come to mind.
- [29:39]
Eleanor Lightbody
Vibe coder. I'm serious, like, we've just hired our first ever Vibe coder and I never thought we would hire.
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Danny Fortson
Hired a vibe coder.
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Eleanor Lightbody
We have hired a Vibe coder.
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Danny Fortson
Do you advertise luminance looking for a vibe coder or is it not that cool?
- [29:53]
Eleanor Lightbody
I can't remember exactly what exactly the spec was, but I do remember speaking to our product team and I said, look, let's just try something unique. And we found this person who didn't have an engineering background, but he had this incredible roster of things that he built using LLMs. And we were like, this is really cool. Let's just see, it's a small experiment in the grand scheme of things. Let's hire him and let's totally separate him from the engineering teams because we don't want to get them too distracted. Actually, some of the stuff that he's built is now going to make its way into product.
- [30:27]
Danny Fortson
And this is him basically telling the AIs what to build in natural language effectively.
- [30:32]
Eleanor Lightbody
Exactly, exactly.
- [30:34]
Danny Fortson
Right.
- [30:34]
Eleanor Lightbody
But without a computer science or kind of a coding background or anything like that. And so I was like, wow, this is a new role, this is a new. Now let's see how easy it's going to be to get his ideas into the product. That's the second thing and separate thing. But yeah, it's a whole new generation coming into the workforce.
- [30:52]
Danny Fortson
That's fascinating. The other thing is, is hype. Like, I'm here in Silicon Valley, I'm old. So I was here for the dot com boom and bust. That was kind of how I started my career. And so I've seen, in a way, I've seen this movie before, this new thing comes along. It's going to change everything. There's just like a deluge of money and hype and then fast forward two years, nine out of ten companies are gone. Most of them went bankrupt spectacularly, et cetera. You have companies, rivals like say, I don't know, Harvey, that are worth $3 billion. I think your last valuation was 400 million, is that right?
- [31:35]
Eleanor Lightbody
Yeah.
- [31:35]
Danny Fortson
How do you see this playing out?
- [31:37]
Eleanor Lightbody
Yeah, I think they're going to be some massive winners and they're going to be some massive losers like anything. So I think that there are some companies who are literally providing huge amount of value to their customers and who are being tested and rigorously tested before people are like buying them. And so that in itself shows that there must be some tangible benefits to them. But I also think there's a lot of recent examples of companies who have been super overvalued and didn't have much AI to their products at all. And there was a lot of kind of people around it rather than AI. When I think about like the market we're operating in, you know, valuations don't necessarily signify the potential future of the business. Like, we're very focused on the growth and like the fact that our AI over the last year, screw 5x and the fact that, as I said, usage is just totally through the roof, that's what we really focus on, driving what we know to be the most important things, which are product innovation and customer acquisition.
- [32:39]
Danny Fortson
So going forward, five years from now, what does Luminance look like and what does the legal industry look like? Is it fundamentally different?
- [32:48]
Eleanor Lightbody
Yeah, I mean, five years forward is a very long time scale to think about because I think things are moving at such rapid rates. The one thing I think about is, you know, at the moment, every company in the world will receive an email, they'll receive a contract, they'll click into the contract, hopefully they're using Luminance and they'll press a button and the AI will rewrite the contract to be more aligned with their positions. But that's going to change. The kind of softwares that we as humans are so accustomed to using, I personally think is going to, you know, that platform is going to be radicalized with agents. And so you're going to have agents talking to each other during most of the negotiations on your behalf and somehow, as an end user and the human, the way that you're interpreting and analyzing the outputs might not be in a contract form, might not be through email, might be in a totally different format. I don't know what that format is before you ask, because if I did, we would be very much pushing it today. But that I think that will take time because again, lawyers are creatures of habit. So I don't think that's going to happen tomorrow, but I do think that that's on the horizon. And for Luminance, I like to think that we've done a very good job with legal. You know, we've grown very, very fast in the space. And what a lot of our customers are now coming to us to ask for is there are so many use cases that sit adjacent to legal compliance, procurement, hr. And we're building these modules to help empower those teams and to start helping essentially automate the work that legal might do that sits alongside compliance, alongside risk, alongside finance, whatever.
- [34:21]
Danny Fortson
It might be creating, like an outsourced legal workforce or insourced Insource.
- [34:27]
Eleanor Lightbody
Exactly. AI kind of brains that are specialized for different departments.
- [34:32]
Danny Fortson
So that was Eleanor Lightbody of Luminance. And I guess the thing that it left me thinking about is, you know, my job, a lot of my friends jobs, how much of their work could be done, could be easily automated because we all think we're special snowflakes and that, no, no, no, no, I'm very creative, or what I do cannot be replicated. But I think what we're finding is a lot of these things can be. And that is at once, as I said, totally terrifying because the obvious follow on, and I think a lot of what companies are doing is like, yay, we can just get rid of humans. But as we saw with Klarna, they got rid of a bunch of people, but then they brought a bunch of people back because people actually wanted to talk to humans in certain contexts. So I think it's really a question of, like, if you can extract 20, 30, 50% efficiency today from what you were doing two, three, five years ago. The question is, what do you do with that extra time, that extra money, that extra resource? Does that mean you simply need less people? Or will these technologies, because they free people up to do something over here, then they can do new stuff over there. And I do think, and maybe this is kind of I'm fooling myself, but I am optimistic that AI will overall be a job generator. But I think we're in the phase of the cycle where the Tide is going out. It's taking jobs right now, but I do think it'll create new ones. That's my hope anyway. Otherwise, you know, God help us all. Anyway, next week Katie Prescott is back, so please do tune in. And until then, take it easy and we'll talk very soon. Bye bye.
- [36:23]
Times Tech Podcast Announcer
Today's episode of the Times Tech Podcast was sponsored by Adobe Acrobat Studio.
- [36:28]
Danny Fortson
Acrobat Studio is about more than just the PDF.
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Times Tech Podcast Announcer
It's a collaborative workspace designed to make working with colleagues across teams and time zones faster and easier.
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Danny Fortson
One of the features is PDF Spaces, which brings PDFs, Microsoft 365 files and websites together in shared spaces.
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Times Tech Podcast Announcer
It helps centralize notes and draft documents so you can see the full picture of a project all on a secure platform.
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Danny Fortson
There's also an AI Assistant which can summarize information, pull out key insights and help you understand what's in your files without reading everything manually, which helps if
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Times Tech Podcast Announcer
you're dealing with a lot of information but are short on time.
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Danny Fortson
And with integration with Adobe Express, you can turn documents into presentations or branded content without switching tools.
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Times Tech Podcast Announcer
So it's not about creating more paperwork, it's about making your paperwork work harder.
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Danny Fortson
Check out Adobe Acrobat Studio and its new features now.
- [37:24]
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Danny Fortson
it isn't just about the tech, it's a new way of thinking and it's empowering your people to create value in new ways. This is where PwC helps you shape AI to fit your business, delivering real value, working with you, combining strategy, industry insight and deep tech expertise to help you innovate with impact, empower your people and accelerate growth.
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Times Tech Podcast Announcer
PwC knows how your business works so you can put AI to work for your business. Discover more@pwc.co.uk.