Jayanth “Jay” Madheswaran: So one of the law firms I was

talking to recently in Arizona, it's a PI firm. Typically, when

you get hit with a discovery request, you take, try to push

it off a little bit, or you take a week or two to respond. And

one of the things you can do with Eve is Eve actually has a

feature to go and comprehensively reply to a

discovery request, going over all the case files it already

has access to, and this gentleman just replied the same

day he got discovered class, and just boom, right back the same

day, and then just he received, like a question mark, question

mark, question mark back from defense. And it just kind of

like flips the script. And you know, those are like little bits

of tactics where the tactics are already starting to change based

on what AI gives you access to,

good morning, good afternoon, good evening,

whatever time this podcast finds you. Welcome to the 10 Golden

Rules of Internet Marketing for Law Firms. Podcast got a great

guest today, Jay Berkowitz is with Jay Madheswaran, and we're

going to learn all about his story, and we're going to learn

about how they just achieved a billion dollar valuation. Quick

commercial, as always, for 10 golden rules. Today, we're going

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to today's guest, because we have some really exciting news.

Jay, welcome to the 10 golden rules Internet Marketing for law

firms podcast.

Jayanth “Jay” Madheswaran: Thank you so much for having me on.

It's nice to meet a fellow Jay.

All right, good. Let's get to the big news here.

Tell us about the company. Tell us about how you achieved a

billion dollar round, and then we'll do your background after

we do the foreground.

Jayanth “Jay” Madheswaran: Absolutely happy to do it. And thank you

for the opportunity. So I'm Jay, you know, we recently, a few

days ago, announced launching and raising 100 $3 million

Series B at a billion dollar valuation for Eve. What Eve is,

an AI platform for plaintiff law, unlike chat GPT answering

questions on documents, we effectively go much deeper into

the workflows and do things with pure AI that used to take hours

upon hours of manual labor to do think in the personal injury

space, things like producing a really comprehensive medical

to the cave's life cycle, into demands and discovery requests,

responses, etc, all the way to resolution. And now we're also

layering in intake. And the reason why we've been able to, I

think, raise so much money is actually thanks to momentum.

Basically, I was in a conference a few weeks ago, and I asked the

crowd, out of 200 attorneys, you know, how many people have used

ai, 90% of them raise their hand, compared to the year

before, where maybe five people, you know, gently raise their

hand. Just the level of awareness people are seeing

towards AI is incredible, but what's missing Jay is them

figuring out how to implement it in their firm. And how do I get

adoption? Because, I mean, you don't want to spend all this

money on AI and not see value for your clients or yourself,

and that's the core problem we focused on solving, is, how do

you navigate this legal AI minefield and pick the right

provider and get actual results? And the reason why we were able

to raise a large round is lot of our customers are renewing,

we're growing and we're showing results.

So you got the tech and you got the results.

That's awesome, exactly. So tell us a little bit more about Eve,

like, what practice areas are you focused on?

Jayanth “Jay” Madheswaran: So, largely, again, plaintiff heavy

ones, so think personal injury, labor and employment. Those are

two immediate practice areas that we service today. We

started the company focused on labor and employment, and we

moved into personal injury last year. Great.

I guess now let's tell the story a little bit. You

were telling me some interesting stories. You were born in India

and came to America. So tell us your journey.

Jayanth “Jay” Madheswaran: Yes, it's one of, I think this is why

plaintiff law appeals to me so much. Is this my story has been

one of, like, the under resourced against the well

resourced for quite some time. And, you know, in India, I grew

up in the lower middle class with where we had to, like,

ration water and things like that, which, looking back, it

was actually, I remember it fondly. It was fun. But, you

know, if I had to do the do it today, I'd probably be very

stressed. But, you know. That leaves an impression on you,

right? So when I came to America, I worked really hard to

educate myself. And that really beautiful thing about America is

it's incredibly meritocratic, right? So if you do give value

to someone else, it's typically rewarded. And that led me into

kind of this journey of becoming a founder, where I did a pit

stop at Facebook early on, as one of their early engineers

focused on Facebook groups where we helped align people with

similar principles together. And then I was a the first

engineering hire for this company called rubric, where we

built really secure solutions to three letter agencies. How do

you protect the world's most secure data to becoming an

investor myself and then finally starting e with a team that I

respect and love to work with.

And how did you guys pick law as an area to

focus on?

Jayanth “Jay” Madheswaran: The really interesting thing is AI.

We've actually been doing AI for even before llms. So when our

team got started, we were working on extracting very

bespoke information from contracts and bank statements

and, you know, these very highly variant doc types, computer

vision and OCR wasn't good. So we had actually created like

this, NLP based model. NLP stands for natural language

processing that's able to understand text and pull

information out. And many of our customers were, in fact, legal

tech and law firms. And what became clear for us, given we

were so ingrained in this technology, is we were

constantly dealing with this question around like, when is

accuracy good enough? When do you need people in the loop? And

how do you introduce people in the loop? When is it okay to be

pure AI and all of these little learnings led to an aha moment

for us in plaintiff law, where we saw the first for the first

time, a chance to kind of flip the script on defense, where,

historically, plaintiffs had need to be a lot more principled

with how they manage their time, because they you typically get

paid in contingencies and defense, especially insurance

companies, sometimes are able to fund quite the battle against

you and kind of drown you out. And there's an incentive

alignment where on the plaintiff side, you actually want to adopt

AI and be as efficient as possible, because ultimately,

you want to put your best attorney on every single thing

dealing with the client, right all the way from intake, if you

could, into sending out client comms, emails, maybe even case

manager work like that's what you would want, if you could.

But your labor constraint and with AI and what we were

building, our platform was able to actually customize and learn

from a firm and be able to go deeper in these workflows, and

that allowed a way to level the playing field and kind of flip

the script. And that, to me, for some reason, is, you know, both

mentally stimulating and emotionally very encouraging. So

that's what led us to go down this path.

Great. So try and make it really simple. I'm a PI

firm. I haven't really done much with AI. Maybe I'm just using

chat GPT. What's a simple step for a PI firm to get started

with AI?

Jayanth “Jay” Madheswaran: The easiest thing you can do is

adopt something like Eve and get started, most likely for pre

litigation work, that's where you see a lot of value right

away, because it happens pretty frequently, and there's a lot of

manual, repetitive tasks you are doing. So the good way to get

started is actually start with medical chronologies, right? So

you upload all the records, medical records you have, along

with any other office visit information, and Eve is able to

provide and categorize really comprehensive visit timelines.

It even highlights things you should be looking for, like bad

facts, and gives you a rough understanding of economic and

non economic damages that you can then seamlessly using Eve,

carry over into a demand letter, where you can get it to write

like you, like your best work, and repeat it without hopefully

any errors.

So basically, get through all the files really

quickly, get through all the data, come up with the best

positioning for your case, detailed medical chronology

demand letter done for you. Obviously, the lawyer wants to

oversee it, but it saves you a ton of time. And like you said,

it evens the playing field a little bit with the defense

firms.

Jayanth “Jay” Madheswaran: Yeah, and I have so many, like, fun

stories there in terms of clever ways in which our clients are

evening the playing field and kind of scaring defense in some

cases,

one of the give us a fun one?

Jayanth “Jay” Madheswaran: Yeah, absolutely. So one of the law

firms I was talking to recently in Arizona, it's a PI firm, you

know, typically when you get hit with a discovery quest, you

take, you know, try to push it off a little bit, or you take a

week or two to respond. And one of the things you could. Do with

Eve is Eve actually has a feature to go and

comprehensively reply to a discovery request going over all

the case files it already has access to. And this gentleman

just replied the same day he got a discovery request, and just

boom, right back the same day, and then just he received, like,

a question mark, question mark, question mark back from defense.

And it just kind of like flips the script. And, you know, those

are like little bits of tactics where the tactics are already

starting to change based on what AI gives you access to.

Yeah, a similar story. I got a request to write

an article for one of the major industry publications, and I'd

recently done a webinar on the topic. Actually, it was the

topic of AI search results. And so I took the transcript of the

webinar, which was done by AI, uploaded it into a GPT, gave it

a really good prompt, and I said, you know, reference the 10

golden rules blog, and reference Jay Berkowitz, his YouTube

channel, and write this article in the style of Jay Berkowitz,

and in make three salient points and do it in 800 words. And what

I got back was simply fantastic summary of my webinar. So it was

my work, it was my words, but it was written for me. I changed

maybe three or four words and sent it back immediately. In

about 45 they were that amazing. Wait. We picked the topic. We

gave you, we asked the article. We gave you about 20 days. You

did in about 20 minutes. That's the power of AI today. So that's

great. What's the scale and scope? How many firms today are

using Eve?

Jayanth “Jay” Madheswaran: We're close to about 500 firms today

using Eve. And again, one of the things we focus on is adoption.

You know, we're trying to get better and better at this, but

it's a combination of how the technology works, how easy it is

to use Eve actually suggests, based on what it sees in your

case data, what questions you should ask it. Even so, that's

one of the ways in which we encourage adoption and proper

usage. And including our many of our support team members are

actually ex attorneys themselves, or even practicing

once, in some cases. And we found that's pretty important.

Because again, you know, one thing I keep repeating

internally in the company and externally is like it really is

a merger of people, process and technology. You have to get all

of the three components working well together, otherwise you

just don't see the results you want.

I asked you for a simple tip of how someone could

get started. Maybe give us that medium to advanced tip, how are

some of the most more sophisticated applications

working? Some firms have been using the technology now for

some time.

Jayanth “Jay” Madheswaran: It goes into, you know, kind of

this prompt fine tuning that you mentioned before, Jay, that you

use did for your AI search blog post, but Eve has a similar

feature, where you can actually train Eve to respond like your

best work every single time. So what you do is, effectively, you

drag and drop a few of your exemplary demands. Let's say

that you wrote you're super proud of into Eve, and it

creates something called a blueprint. And now for every new

case going forward, it actually applies the same letterhead,

same formatting, same reasoning that you use to kind of come up

with those points, and it does all of that for you

automatically. So the first draft that you end up with ends

up being significantly higher quality. And of course, you get

all the hallucination prevention features you would expect, like

it cites, it references the information, as well as does a

bunch of things to ensure it's not hallucinating. And

ultimately, like what you end up doing is you start thinking

about your business in a different way. You start

thinking about your business, and these are the bespoke

workflows I can upload into Eve and turn into a software

component. And then what do I do with my staff, and how do I

improve how they review it and how thoughtful they are in

implementing it? So kind of getting that motion going is a

bit advanced, but it pays huge dividends if you do it right.

I love it. Let's talk a little bit about the

raising of money and the seed rounds. The headline of this

webinar is going to be something about raising your seed round

and dollar valuation. I'm speaking for my marketing folks,

because we haven't written it yet. Of course, tell us a little

bit about the founders journey and how you achieve different

tranches and raise some money in this most recent raise, maybe

with an eye to your friend who you mentioned is just doing a

startup this week, or firms that are going through that first and

second round of raise, absolutely.

Jayanth “Jay” Madheswaran: I mean, fundraising is never,

never easy, but we've been fortunate. A lot of our founding

members come from places like Facebook, Google, Microsoft,

rubric, and I had the privilege of working with my co founders,

Matt and David, at rubric, and these are some of the smartest

people I think you'll ever meet. You know they ran really, really

large teams and initiatives at their respective companies, and

without them. And what we've built so far would be very

difficult, but the way these things go, you know, it starts

with a dream, and you show, hey, the dream is turning into

reality, and that's how you raise money. So the dream

initially was around, we had this idea that we actually could

drastically change plaintiff law when everyone else was focused

on defense, right? Historically, that's at least for legal tech,

that's where the money used to be, and most plaintiff firms are

much smaller and also much they don't pay much, relatively

speaking, and that's a really difficult thing to solve as a

legal tech company. However, we took a bet that this software is

so valuable that it actually changes how plaintiff law firms

will operate, and it'll turn them into AI native firms first,

even before defense firms can so that was a bet we took and we

showed that it worked, right. So that the hard part to solve for

us during the seed round, I think we raised about 14 million

or so in the seat Series A round the hard part there was

effectively showing that AI can actually do it right. So the

problem with technology and AI is it doesn't matter if it's 90%

accurate, if what you really needed was 95% accurate,

suddenly the whole software doesn't work. So let's say you

go into Eve and you ask a question, and it only gives you

the right answer 20% time. No one's going to use it right so

solving that piece was what took a lot of our time in the seed

stage. So we ended up iterating constantly, and you have to be

careful, we can't really use the data for training, so we had to

be quite clever and thoughtful about how we made the software

such that it's actually able to answer all the complicated

questions across the case life cycle for any type of case

within labor and employment or personal injury, which turns

out, is a lot, right? So you have moving vehicle accidents.

Is labor and employment. You dive deeper into different

causes of actions that all result in different types of

work. And getting all of that right was it felt like a death

by a million cuts. But eventually we came up with some

clever ways of simplifying it and implementing a software. And

we were actually the very first provider to do this entire thing

end to end with AI when everyone else was shipping it overseas to

get you back, a demand letter, met Quran or something along

those lines. And once that happened, we raised our Series A

from Andreessen Horowitz, which is one of the well known firms

in the Valley, and I guess now the world raising a lot of

money. And they kind of saw the vision, because lot of our early

customers were using it every day, and they were starting to

see signs of, hey, we're actually taking on, you know, 2x

the case capacity of the same staff. This just didn't think it

could happen. And Andreessen took a bet that, Hey, this looks

promising, and funded us really well, like they gave us $47

million and did that quickly. That was in January this year,

and then we just continued building. And what we really

focused on is eventually what plaintiff lawyers want, is they

want a tool that is cheap goes deeper into their workflows and

keeps innovating and launching new features to go and deliver

as much as they can for their clients in the shortest amount

of time, right? That's really at the end of the day, is what you

care about. What does cheap mean? What's the

starting cost for Eve, for a PI firm or a defense firm? And then

is it per person? And how does the pricing scale? Yeah.

Jayanth “Jay” Madheswaran: So typically it is a price per

case. That's how we charge it. I've been in trouble for

mentioning this before. If you ever change, it causes us

problems. So maybe it will refrain from saying it, but it's

usually a few $100 per case depending on various factors,

and that certainly makes sense from what

I know about how they price their cases and the expenses

that go into it. That's right, I know I've had this conversation

with probably a dozen people on this podcast, from

transcriptionists to different softwares to investigators and

folks who work on the cases. Couple 100 bucks for the AI is

nothing relative.

Jayanth “Jay” Madheswaran: That's right. I mean, if you you know,

a lot of people don't do this, but you know, typically, when

you start growing your firm, you start getting into it. But a lot

of firms, when you actually break down the costs related to

servicing a case on a per case basis, you end up finding that

something like 30% goes towards marketing, and potentially even

50% goes towards the actually servicing the case. And then you

have miscellaneous expenses, which adds up, and you're

actually your profit margins are relatively thinner than they

need to be. And what the hope of AI is that you're able to

basically trade the the labor costs for software costs over

time, and in exchange, you can use the additional labor that's

been freed up to actually take on more cases. That'd be the

that'd be the transition, right? So I kind of see. Actually,

interestingly, Jay, I do think, like, more money is going to go

towards marketing. Interestingly, if, when AI

starts really getting good, right? Like, think the average

attorney is able to handle 100 cases per month, I think we were

going to probably see more money flowing towards marketing, and

that becoming one of the central areas in which you differentiate

yourself against other firms for sure,

if, if you're a very smooth AI operation, and

the time and the cost to run those cases goes down, you want

to get more of the cases, but only so big. So that's where

notion comes about, right?

Jayanth “Jay” Madheswaran: It's true. But what, what is really

fascinating is our law firms are choosing to different things

with that added time. So for example, like some end up

becoming significantly operationalized for, let's say,

subset of cases, right, like MBAs or dog bites or what have

you, you get really specialized for those cases, and you're able

to handle so much because you're focused on it. Alternatively,

some others are using the fact that, because once you start

working with Eve, Eve starts learning the entire case life

cycle, and starts learning your history of cases, so you can

actually start qualifying, let's say, more cases for litigation,

because you're able to do kind of that heavy work of litigation

much more efficiently now, and that's a very different

approach, but they're seeing much higher settlement checks

when they they don't settle in pre lit.

Yeah, I don't know if you and I were having

this conversation or someone else, and there's you mentioned

this earlier, the defense firms have had AI and have had

sophisticated computational ability for some time, and now

they have a pretty good snapshot of each firm's capabilities and

how often they go to court and how often they litigate, and so

the defense firms are making a snapshot of the valuation of the

case based on the likelihood of the firm's ability to make their

case. So this software, again, levels the playing field, like

you talked about, but it's like aI versus AI. What do you know

about that defense side software?

Jayanth “Jay” Madheswaran: Defense side software is large. I mean,

it's split across the board, right? That are also trying to

figure out what to do. You see some players like Harvey helping

out defense firms where they'd be helping with synthesis of

information, kind of like chat, GPT, but for law, yeah, that's

kind of, that's the most common one we've seen so far. But the

challenge there is that workflows are so diverse, and

their business model is so different. You know, if you're a

defense firm, you care about retaining one client over a long

period of time, and kind of increasing the value of your

billables over time, and that leads to very different product

building and what they care about. So I think that's where

kind of the products differentiate. But I think you

should probably also expect they're also going to adopt AI

solutions pretty soon, mostly driven by, I think, US and

plaintiff workflows, right? Let's say the amount of volume

of work suddenly explodes by 5x for them to respond back,

they're going to have to look at solutions.

That's great. You mentioned it briefly a minute

ago, talking about new product development. So how do you guys

create your list? How do you figure out what to develop next,

and then tell us a little bit about the intake product, your

newest product, absolutely.

Jayanth “Jay” Madheswaran: So, you know, the way we develop is,

again, we're architecture first. So what we care about is

combining, again, broken record, people, technology, process, all

together, and the product helps as much as possible with that.

But the way it's architected, you know, we work closely with

anthropic open AI to come up with their architecture. It's

done in a way that is always going to benefit from new

advancements from Ai, right? So even if AGI comes we're still

going to be the best way to use AGI for plaintiff law, and that

was very important to us. But a really useful side effect of

that architecture is really, really quick innovation of

literally anything AI that comes out. So as a result, I'm sure

many of your viewers probably have seen or heard about these

voice AIS starting to come out, right? So now AI is actually

able to listen to you and talk back to you. If you have chat.

GPT, you can click this little voice button and you know,

she'll talk to you, or he, depends on you can set you can

change the gender if you'd like. And lot of our law firms were

actually asking for that, because one of the difficulties

is now that Eve is helping accelerate pre lit and

litigation workflows. They actually want to take on more

clients, so now that's starting to become bottleneck. And I'm

sure you know, one of the toughest thing that everyone has

seen is you never want to miss a $10 million case. You know, the

time, you'll realize some other settlement happened for $10

million that actually came through your intake and you

passed it or didn't respond quickly enough. It hurts, right?

I think also hurts them, because they're getting. Uh, seed to

much slower, and that's something we can solve because

that's largely blocked by Labor training and improvements. So

what our Eve intake does is it has multiple different

components working together, right? They're aiming to not

really replace the intake team. We want to make them better so

he was able to integrate with existing telephony providers

like zoom, Ring Central, etc, to automatically categorize and

almost like light up missed opportunities, right? And that

then helps you coach and come up with different SOPs to handle

intake. And even more cool, at least for me, is the same SOP

documents you create in a Word file, or what have you, you

could actually upload right to Eve, and that configures the

voice agent for you. And now the voice agent is not like the IVRS

we're used to, where it's like, you know, press one to continue,

yada yada yada. It's actually a dynamic one that understands and

follows more complex directions you want to give it. So, for

example, you know, if a customer ever, or client, rather, ever

mentions like a headache, maybe you dive a bit deeper into TBI

related questions. And those are things that's hard to train.

Exactly those are, those are like hard to train staff to do,

and Eve, because it's built on the same intelligence that we've

kind of built it for prelim litigation for, it's able to

bring that intelligence into the call center.

I mentioned the simple GPT product project I did

for myself. And one of the things I skipped was the key

step to writing a great prompt is giving the AI a role. And so

I said, when I wrote that prompt to write an article for myself,

I said, you're one of the world's top business writers,

and you write for magazines and website blogs, and you give the

GPT a role, and you specify the tone and the style and the

expertise you want it to bring to the project, I imagine you

had to make Eve an attorney. How did you read in legal

intelligence? And just another side note, I understand GPT four

was in the 90th percentile of passing the bar. So I don't know

where it got all that intelligence, but maybe you can

tell us, and maybe you can tell us, did you send Eve to law

school?

Jayanth “Jay” Madheswaran: We basically did. I think that the

challenging part is technology has gotten to the point where

it's not a simple put data in, get some data out, type of

challenges anymore, because what we care about, again, is

shortening the time end to end for something like a demand or a

METRON. You know, it's not just important the first draft is

good, but you want to get to the last draft as quickly as

possible. And this is where at least I have trouble using

generalized AI tools, right? Like chat GPT. I also use it for

blog creation and sometimes writing LinkedIn posts, sorry,

and it's always the last bit that takes a lot of time, and

then I'm stuck wondering, should I even have used this to begin

with? I just written this myself, and that's the same

challenge people have trying to use it when you actually know

what you're doing. You know, in a topic you know a lot about is

getting to actually be a system. So to make that happen, we had

have this attorney like reasoning in different steps,

right? So, for example, like in a demand, you have to know when

is the right time to go crawl a medical record, and when is it

right time to double, double down and look for other related

things. Again, we mentioned TBI before, but let's say you see

something with TBI, you actually want to pull that up and

highlight, hey, this could be something that we missed to

check for, and we may want to talk to client to go get some

additional testing done. And those are things where we have

to go train very specific things for right? So it's not just

that. It's a AI attorney in terms of what it knows, but the

workflows and knowing how to do the work is something no one

knows, right? Like, at least chat GPT doesn't have that

information, and that's really more of what we're tweaking on

is, how do we keep track of, how do you do the work, right? And

we train on that per firm. And then Eve actually starts getting

better and doing that work. And it manifests itself in really

cool ways, like that advanced feature I mentioned to you,

where you can drag and drop your top demands, and it just starts

thinking like you, in terms of how you wrote that.

What's the plan for all of this? I see

interspersed Venn diagrams where all of the case management

software are building some AI capability at the back end.

We're big fans of case status and Hona, who do customer

service, and they have some AI built into that step where once.

A case is in your case management software, they give

you proactive communications that go out to the consumer and

tell them what's happening with their case. Then you all are at

the front end of managing the case and giving the attorneys

tons of capability and the medical chronologies and the

demand letters. And now you're getting into intake. And then

there's intake or intake software at the front end. And

so I see all these Venn diagrams sort of merging. Is that what's

going to happen, like someone is going to be the best across the

board at some point, very soon,

Jayanth “Jay” Madheswaran: again, putting my VC hat on right. So

this is a question we had to answer for many industries. The

question that you're asking is like, does best of breed win, or

does an all in one platform win? And the answer is never clear

historically, in all basically verticals, it flips back and

forth. You know, sometimes you end up going best of breed, and

then sometimes you end up going converged. My anticipation of

how this goes is we're focused on one thing, and one thing very

clearly, which is, how do we serve a client as quickly as

possible, right, and get the highest settlement possible? And

the only things we care about are the workflows, so that

actual work you'd be doing when people are pulled in, how do we

make that as effective as possible? And that requires a

decent amount of focus and building right, at least for us,

so far it has, and from what we can tell, it's going to involve

that way. And so that's that's ultimately what we're focused

on. So with intake, we kind of view the rest as side effects,

like, if you want to partner with other softwares, and we do

that handles, let's say, the telephony part of intake really

well, or they handle one part of insight really well that we

don't necessarily think is critical for shortening the

client to close a case, then we don't do it. We focus on what we

do best, which is the AI components. So that's how we're

viewing it. I expect it to evolve, though, like what I'm

probably envisioning is I think that law firms will buy one AI

software and potentially a CRM, depending on which workflows and

data management tools they need, and then I think everything else

will become kind of bespoke, right? Meaning you'll want to

solve a very specific problem, like if you have a specific

problem with client communications, honor and K

status are great, right? And you want to look into them. And if

you want to solve a very in the future, let's say, break down

the future, you have one very specific type of deposition you

want to do. It's possible you go and buy an agent just for that

one day. I don't think we're quite there yet. And there is

benefit to having something in one platform, like, for example,

Eve is able to learn from your past cases, which makes all the

workflows better. So there's some benefit there, but I think

we're gonna have to evolve with the industry here.

Yeah, it's not dissimilar for us at a digital

agency, and I think it goes to the buyer's mindset. Some people

are going to look for the best all in one solution. Some people

are going to look for the best solution in each of the

verticals. So some people come to us because we can build a

great website, beautiful, high converting website. We manage

SEO, social media, do a lot great video pay per click, local

service. Ads, very strong across the board, and people like to

have a one stop shop. And then some people come to us and they

say, you know, can you just manage our pay per click? Or can

you guys help us with just SEO? Because I have vendors for the

other things. And their mindset is they're they're shopping for

the best in each vertical. Yeah, exactly. Maybe it's more up to

the buyers in the future. You briefly mentioned AGI, which is

basically the All Knowing all team intelligent AI, right?

Where it's more, more intelligent than humans. Talk a

little bit, please, about AGI, and what you see for the future

of AGI and the future for our industry? Absolutely.

Jayanth “Jay” Madheswaran: So there's actually a conversation

I had a few days ago with some open AI employees, right? And

basically the definition of AGI is that no one actually really

knows what AGI means. So it's turning into a spectrum now,

right before the term was thrown around to me in something like a

god, like creature that knows everything, can do everything.

That's what I think people tried to imply. It was what we're

heading into now, is more of a it gets better at this one other

thing next year, and this one other thing the year after that

seems to be the path we're on right now, where it starts

getting these capabilities, and it just so happens people use

it. I mean, if you think about even today, what tools like

chat, GPT, Gemini, these things can do. It's ridiculous, right?

Like it can do a lot, and we're just taking it for granted. And

in fact, we get annoyed with it when it doesn't get exactly what

we're thinking, right? And it hasn't really changed the world

in the way I think you would at least from the. Marketing, the

way they kind of talk about it, you would expect it to, and

that's because, again, again, I repeat this. But like

technology, people process, you know, all of that has to combine

and work together, and that's going to take time. The other

thing is, as we approach let's say AGI, I think the world will

change around it, and it's not going to be all instantaneous.

So for example, let's say next year, AI reaches superhuman

levels of intelligence in material science or something,

and then it starts inventing a new product every year. Then the

whole world will kind of change a little bit to accommodate for

that capability, and we're all going to adapt, but eventually,

like, I'm of the opinion that I think we have a purpose and we

have a reason to exist. And, you know, worst case scenario, we

can turn off the AI, so I think we'll find a reason to survive.

Yeah, it's

interesting that I think there's a lot of fear

out there about AI, and I think I was listening to the Google

CEO on an interview talking about AI, and the interviewer

asked, What's the future for AI at Google, or what's coming up

in the next year? And he said, well, the beauty of AI is it

allows us to do projects quicker and less expensively. We're

development, and so now we can do about 10% more projects. And

I think that's the optimistic view. Is that AI will free up

humans to do even more amazing things by getting rid of the

easiest, simplest tasks, and perhaps some of those simplest

jobs, and the one thing I worry about is the training jobs,

right? Like the young person of digital agency isn't as

required, the young developers that you all would have employed

in the past aren't required, and the young attorneys and

paralegals won't be as important. Yeah.

Jayanth “Jay” Madheswaran: I mean, I think this is something

that is temporary, because eventually what you want to do

is figure out what people are really good at and utilize that

with AI to increase productivity. And right now

we're just in a phase where I think we haven't figured out

exactly what we're good at and what AI is good at. Yeah. So I

anticipate, I anticipate that will change pretty quickly, and

we're seeing some of that actually already. You know, even

for us, we've only hired senior engineers across the board for

very many similar reasons to what you mentioned. And we're

seeing the new generation that's grown up with pure AI, which

exists now. You know, I think I even had a phone growing up for

a long time. They are thinking about problems in a very

different way, and it's causing some really incredible new

changes, right? And I think we're just entering that phase,

and I think we haven't, you know, I think we'll be fine.

It's my optimistic, optimistic look on life.

Talked about digital natives and the way the

generation comes to projects, but now you're saying, AI

digital native coders would just envision the solution so much

further ahead than I possibly could. So anyways, thank you for

sharing this fascinating journey. I'll just get to the

final questions. We've done this on this podcast for probably

close to 15 years, and we ask the sort of short one liners,

and this will be a great question and answer for someone

every week. So what apps or techniques do you use for

personal productivity?

Jayanth “Jay” Madheswaran: I tend to use Gemini deep research

or deep research, in any one of these providers, quite a bit.

For example, even before this interview, deep research found

everything about you, Jay and the 10 golden hurdles, and

helped me prepare you know, for this podcast,

what's the most interesting thing it shared?

Jayanth “Jay” Madheswaran: I think basically it talked about

you advertising for things like Coca Cola, which I didn't know

about, that's really cool, and talked about your philosophy

behind the 10 golden rules, and found some things about you, and

also like how you'd like to interview people. So it actually

did a pretty thorough job. I thought,

yeah, and it saved you from going to my

LinkedIn, where it would have said that I was a former

director of marketing for Coca Cola and listening to all my

podcast interviews on our YouTube channel, etc, exactly.

It just so deep research. So what kind of prompt did you

write in Gemini deep research?

Jayanth “Jay” Madheswaran: So Gemini deep research works a

little bit differently, to open AI where you can actually tweak

the plans it comes up with, yeah, so what I typically do is

like, you know, just, hey, I'm having this meeting coming up,

very casual, like meeting coming up with Jay. And, you know, he

runs 10 golden rules. Help me prepare for it. And it comes up

with a plan, and I just go edit the plan of, no, I mean, this

is, you know, it, I think it hooked on your marketing

services. Or so and help them improve the podcast, I'm like,

no, no, that's not what I want. Do this instead. Do this

instead. Fantastic.

I love it. Do you have a personal wellness and

fitness routine?

Jayanth “Jay” Madheswaran: Yes, my wife and I actually wake up

at five, 530 every morning, and we have a gym that we built in

the house, great. And we work out with a trainer from Croatia,

of all things. And you know that is, that is, I think, been the

biggest change. Because, like, you know my, I'm sure you know

this too, I have a kid, and as soon as he wakes up, the day

goes to becomes all around him. Exactly we get, we get at least

an hour of alone time working out before that happens, which

is very, I think, makes me happy.

I heard a line recently, the heaviest thing

that you have to lift in the gym is the door to get yourself

inside.

Jayanth “Jay” Madheswaran: All that problem

right here at home that that's

Jayanth “Jay” Madheswaran: and the same thing with the trainer.

The trainer just calls and you know, you can't It's rude to

hang up, so you pick it up and you have nothing better to do

than work out.

You have to let him in. Right? Exactly. That's

awesome. What do you recommend as your best business books?

Jayanth “Jay” Madheswaran: Ooh, I kind of have an unconventional

answer, which is, these aren't actually business books, but

Nassim Taleb, he's like a mathematician. He's written

probably famous books like Black Swan. There's one that I like in

particular, called anti fragile, and it's really meant more from

a market perspective, like, how does a market become less

fragile? But I found a lot of those principles are actually

applicable to how you run your life in a way in which it's not

fragile, right? So what happens? You know, most people, if you

don't get the next paycheck, you don't know what to do with your

life, and kind of rethinking your life and structuring it in

a way where, like he says, anti fragile, I found to make a

pretty big impact. And I think probably what pushed me on the

entrepreneurial journey.

Love it. What blogs, podcasts or YouTubes Do

you subscribe to? And when something hits your feed, you

stop everything else and listen to

Jayanth “Jay” Madheswaran: it's a good question. You know, for

longest time, I used to like this podcast called The Founders

podcast, where it was like it goes to the biographies of old

founders and spends a bit more time thinking about that thought

process, which I enjoy more so than the history. So that was,

that was one for a long time, I think more recently, just given

how quickly AI is moving, there is one called AI daily brief,

which is, unfortunately, today become quite ads heavy, but it

basically captures all the latest developments in AI on a

daily basis. And there's a lot happening these days. Yeah,

exactly. And it gives me a chance to kind of catch up on my

community work.

Yeah, the founders approach, like a lot of

people say, read biographies, which, yes, I try and

intersperse with business books and AI books. I

Jayanth “Jay” Madheswaran: think the right of a lifetime is a

really good one for the audience, the Disney the Disney

one great.

What is your NFL or sports team?

Jayanth “Jay” Madheswaran: You know, I have a bad answer here,

which is, I don't actually watch any sports. Back when I was

really into tennis, I love watching anything with fetter or

Nadal. But unfortunately, those Troy retired. Now I haven't

exactly, hey, well, look Alcaraz center, when

you when you're ready to find some time for tennis, it looks

like it's going to be the next great. Oh, is that right? Some

of those matches. Oh, yeah, yeah, just watch the Wimbledon

final. It was fantastic.

Jayanth “Jay” Madheswaran: Okay, I'll load up the highlights.

Yeah, and the French Open. US opens, these

guys have won, I think, eight of the last eight major bombs

between the two of them. So last two questions, what's a great

introduction for you? Who should we send Eve's way?

Jayanth “Jay” Madheswaran: Yeah, absolutely. The best way to

reach us is at our website. So it's e v e dot legal. And you

know, we have we're growing pretty rapidly. If you want to

join us as well, if you're into building a next generation of

plane to flop, please apply. We're looking for all sorts of

people, and I would be encouraged if you guys just

tested it out, like we have a free demo and pilot. And

typically, even if you don't end up purchasing, you'll know what

to do, hopefully to speed up your day. And at minimum, I

would love to kind of give that to you.

Fantastic. And where can people get in touch

with you?

Jayanth “Jay” Madheswaran: So I'm found on LinkedIn with my

very difficult to spell last name, Jay Madheswaran. And you

can also follow Eve legal at LinkedIn as well. And we're our

Twitter presence isn't great. We're trying to get better at

it. And if you have any things you want to add, just message us

somewhere, and we'll get back to

you. Hey, here's my marketing tip that makes all

that easy, and that is just produce one piece of content,

like every week, or, in your you guys case, every day. And the

one of the best things to do is just answer a question. Do? So

okay, if you just like to take questions that you're getting

from customers or even better prospects, answer one great idea

day, and then what we do for our clients is we cascade that. So

you're probably not gonna have time, but you could have, like,

maybe when you're marketing people just answer that question

and run around to the different texts and get, get the answer.

And if you do it on video, it's great. You put it on on YouTube

and all the socials, and then we call it cascading, like a river

cascades over waterfall and creates many waterfalls and many

rivers, little streams, that one answer becomes the first piece

of content on YouTube or wherever, and then it's just

super easy for your marketing folks to cascade it everywhere

else. That at least gives you a baseline presence on Twitter and

Tiktok and Insta and everywhere else. And all of a sudden you've

just got really helpful, valuable content as a baseline.

And obviously, if you can do really smart social on top of

that's great,

Jay, you're giving me all sorts of ideas. I'm going to put this

into action right away. Actually, this is great.

Jayanth “Jay” Madheswaran: It's my TED talk that I just haven't

done yet. You should do it. That's That's fantastic. Yeah,

yeah, I'm amazed, because I've

been talking about it for 10 years. But

nobody else has done the TED talk so But Jay, thank you so

much. This was great. And everyone you know, check out

Eve, and if you haven't dipped your toe in the AI waters,

you're overdue.

Jayanth “Jay” Madheswaran: Thank you so much. Well, thank you so

much.