AI Hustle: News on Open AI, ChatGPT, Midjourney, NVIDIA, Anthropic, Open Source LLMs: Insight Partners' Praveen Akkiraju on AI Shaping VC's Future

Welcome to the OpenAI podcast, the podcast that opens up the world of AI in a quick and

concise manner.

Tune in daily to hear the latest news and breakthroughs in the rapidly evolving world

of artificial intelligence.

If you've been following the podcast for a while, you'll know that over the last six

months I've been working on a stealth AI startup.

Of the hundreds of projects I've covered, this is the one that I believe has the greatest

potential.

So today I'm excited to announce AIBOX.

AIBOX is a no-code AI app building platform paired with the App Store for AI that lets

you monetize your AI tools.

The platform lets you build apps by linking together AI models like chatGPT, mid-journey

and 11Labs, eventually will integrate with software like Gmail, Trello and Salesforce

so you can use AI to automate every function in your organization.

To get notified when we launch and be one of the first to build on the platform, you

can join the wait list at AIBOX.AI, the link is in the show notes.

We are currently raising a seed round of funding.

If you're an investor that is focused on disruptive tech, I'd love to tell you more

about the platform.

You can reach out to me at jaden at AIBOX.AI, I'll leave that email in the show notes.

Welcome to the AIChat podcast.

I'm your host, Jaden Schaffer.

Today on the podcast, we have the pleasure of being joined by Praveen Aki Raju, who is

a managing director at Inside Partners based in San Francisco Bay Area.

He brings a product and operational lens to investing in passionate entrepreneurs who

seek to challenge the status quo in areas of automation, data plate platforms, DevOps

and infrastructure software.

So prior to Insight, Praveen actually served as a managing partner at the SoftBake Vision

Fund where he led the enterprise and SaaS investment practice.

And before that, he was CEO of Viptella Incorporated, a SaaS platform for enterprise edge and

also CEO of VCE, an enterprise cloud infrastructure company.

Welcome to the show today, Praveen.

Thank you, Jaden.

Pleasure to be here.

Super excited to have you on the show.

I wanted to kick this off.

I'm going to ask you a little bit about your background specifically.

I mean, I guess the first thing is, did you always know, you know, you were kind of interested

in tech and in this space and investing and whatnot?

Or is this something that you kind of discovered throughout your career and your journey?

Talked us a little bit about your journey to becoming where you're at now.

Yeah, indeed.

So I was fortunate to start my career at the advent of the internet age, if you will, the

early days of the internet.

And so at Cisco, where I started my career, we were a pioneering company that built the

internet infrastructure.

So I got to see sort of the entire economy that we take for granted today, built from

the bottoms up.

And as part of that journey, I got to play many different roles.

I was an engineering, I was a product manager.

And as I kind of got to run some of the larger businesses that both on the service provider

and the enterprise side, I ended up on the investment committee at Cisco, where, as you

know, Cisco, it was a pretty prolific sort of a choir of startups technology.

And so I got to sort of get a front row seat in the thought process of sort of how technology

gets built and just the whole sort of build versus buy, your large company, when do you

go acquire companies, how do startups actually deliver value?

And so it got me really intrigued into the startup ecosystem.

And so as my career progressed, and I transitioned out of Cisco, I ended up at Viptella, which

basically was a bottoms up startup where we were building a SaaS platform, it was like

a 40% team.

It was a phenomenal experience.

So I got to basically transition from sort of the large corporate environment to more

of a startup environment.

And I would say that was one of the hardest jobs that I ever did managing a small company

because it's a lot of fun, and it's also a high wire act in many ways.

And so I think that experience of kind of building businesses both within large companies

as well as a startup scaling the business, and eventually we did get acquired.

So gave me a pretty good perspective of how technology and products get built, deliver

and how to compete in markets and such like.

So when I kind of wrapped up at Viptella post our acquisition, one of the things that I

really wanted to do was to kind of take a step back and look at the broader ecosystem,

the broader picture of how technology was evolving.

This was in the 2017, 2018 timeframe.

And we were the cusp of AI, and at that time AI was really all about predictive AI and

computer vision and application of computer vision, things like autonomous vehicles and

such like.

So I was really intrigued to be able to kind of go spend time with founders and understand

that that's out of the equation better.

So that's kind of when I transitioned to the investing side at Softbank and then eventually

sort of ended up at inside where I've been here for the last three plus years, primarily

focusing on the areas that you talked about earlier.

Very, very interesting.

Yeah, and an incredible background.

You know, what I'd be curious to know from you is, you know, how is your experience as

CEOs, both at Viptella and also VCE, right?

You said these are two of the hardest jobs you did running startups and whatnot, but

how is your experience as CEO kind of influenced your perspective on investing in AI startups?

Yeah, and that's a great question.

I think, you know, you realize when you're sort of running a company and, you know, running

a startup, it really, you know, there's so many variables that determine success, right?

It's not just the quality of the idea or the quality of the market that you're in.

You know, it's all of those combined with the team, combined with sort of, you know,

key decisions, how you make them, combined with kind of the investors you decide to work

with and how they help you.

And of course, you know, a slice of luck, right?

All of this kind of combines together to be able to make for success.

So when you sit on the investing side of the table, and, you know, from my perspective,

having sort of, you know, earned my scars in the back, if you will, made mistakes and

been, you know, been in the hot seat, you know, you get to sort of, you get a better

sense of understanding of, you know, what's really driving a founder, you know, when they

kind of step forward and start this company, right?

And I think you allow yourself to kind of, because you understand the variability here,

you're not looking for like one amazing thing that makes a decision on what is the company

that we want to invest in, or is the founder we want to invest in.

You also allow yourself to kind of, you know, let the founder kind of discover that journey.

So some of these pieces are not fully defined, right, in the early stage.

So, you know, because, you know, I've been down that path, like, you know, there'll be

certain aspects, certain decisions that are not clear until you get to a certain point

in time.

So it really kind of builds a much more holistic way of looking at, you know, an investment

opportunity and a founder.

And you know, once we make the investment as well, I think you obviously respect a founder's

journey, right?

And, you know, my journey will be different from, you know, a founder's journey that has

different points in time, different variables involved.

So you respect that.

And so you try to help where you can add the most value, right, as opposed to sort of trying

to replicate what you've done.

So I think there's a sense of sort of better, deeper understanding of the process of building

a company and what it takes for a company to be successful.

And also, you know, when things go sideways, as they do, like to start up, you know, you

have a better sense of like, look, you know, the sunrise tomorrow morning, it's not the

end of the world.

And, you know, I think you get a better sense of both helping the founder to that particular

situation as well as an investor, making sure that you're not, you know, panicking or you're

trying to put more pressure on a situation where they're already sort of working through

stuff, right?

Yeah, no, I think that's those are some really great insights.

And then I guess specifically kind of looking at those founders that you mentioned, right?

What are some of the key traits you look for in, you know, founders or entrepreneurs that

are kind of aiming to disrupt fields?

I know you kind of focus on like automation, data platforms, DevOps, infrastructure, software,

that kind of stuff.

So what are some of the key traits of founders and entrepreneurs that you're looking for?

Yeah, I mean, I think, you know, one of the only really the most important things is

the way that a founder tells the story.

And you know, the important thing that that in my mind sort of defines a key variable

of success for a startup is how deeply they understand the customer, right?

And why the whatever it is that they're building, right, really resonates with with with with

a customer and how the customer derives value.

So when I listen to a founder, listen carefully about sort of how they tell the story, you

know, if they're talking about like, you know, anecdotes of customers, right, problems

from a customer point of view, you know, and the customer is kind of weaved into every

aspect of their narrative that gives me a sense of, okay, here's a founder who obviously

has, you know, phenomenal technology background, right, or what have you.

But more than anything else, they fundamentally understand the customer, the problem and how

a customer will derive value from whatever it is that they're building.

You know, that's for a startup is really, as we talked about multiple different variables,

what are the key variables really is, you know, their ability to connect with customers

in a meaningful way and ensure that they are realistic about how a customer will derive

value from the product that they're building.

So understanding of that at a at a profound level is really sort of, from my perspective,

the most important thing that I look for.

Very cool.

I think that that's incredibly important.

I love your focus there on customers, because at the end of the day, you know, we all know

founders are people that have great ideas or vision for something, but the amount of

come to startups that have pivoted is obviously insane.

And if you don't have that product market fit, if you don't really understand the customer,

you know, you're kind of just building in the dark.

Something I would be curious to know is when you're looking at some of these frameworks

around, you know, venture capital and, and everything going on today, how do you see

the role of kind of venture capital evolving, especially in today's AI landscape where AI

is getting integrated into everything.

There's a lot of big shifts happening.

How do you see the kind of the role of venture capital evolving or maybe what are some of

the changes you think may come?

Yeah, I mean, I think I'm a late comer to the to the investing game, if you will, right?

You know, I've sort of transitioned to investing after a long career as an operator.

So my perspective, obviously, it would be from that, from that angle.

Yeah.

So, you know, I think the way, you know, we are right now in sort of a challenging economic

environment.

I've seen a couple of these cycles on the operating side, you know, when we went to the 2008 sort

of recession and the impact that had.

And so I think as a venture investor, you know, the journey starts when you actually

write the check, right?

The journey doesn't like, you know, you don't celebrate when you, when you get it, when

you invest in a company and it's phenomenal, you get, you're excited about the opportunity

to work for the founder.

But truly the journey starts at that point because, you know, the founder is looking at

you as a partner and somebody who's got a kind of, you know, obviously be there for

you to the, to the ups and downs, but more importantly, sort of, you know, as a contribute

to the effort, right?

Yeah.

You're not sitting on a board just kind of watching things and, you know, essentially

participating in a board meeting, but, you know, you are part of the team and you participate

as the founder wants you to participate, right?

So I think what that means for me, if we're going to break that down, you know, it's really

sort of each of us as investors bring our own point of view.

So I'm a product and a, and a engineering background.

So, you know, I, I, I can contribute to a conversation on product strategy, you know,

scaling teams, right?

These are things that I've done.

So what I tried to do with, with my founders is basically say, okay, here's sort of, here's

kind of where I'm coming from.

This is kind of my background, right?

Here's kind of what insight can offer to you, right?

And we have a pretty extensive set of resources that tap into it's part of the reason why

I actually joined inside as opposed to a couple of other opportunities that I was looking

at.

Okay.

And so then then you sort of, you know, build a relationship of trust with a founder where

they feel comfortable enough to come to you and say, like, hey, I need, I need help in,

in these particular spaces.

And, and so, you know, where's end of the spectrum, you're everything from, obviously,

you know, a capital provider to, you know, a product strategist to, you know, helping

them with hiring to, you know, being a therapist, just kind of walking through a difficult

situation, right?

Yeah.

You can play roles.

But, you know, the most important thing is that you have to first establish trust with

the founder in a way that they understand how you can help them.

And you're respectful of sort of how you engage with them, irrespective of what your background

is.

And, and I think that's, that's sort of the way I see, you know, my role, right, as a,

as an investor.

Yeah.

And I mean, I think it's funny you mentioned being a therapist so often, I think there's

a lot of different roles that venture capital, venture capitalists are playing today.

And of course, the reason for that is because there's a lot of challenges and startups.

Specifically what I'd love to ask you about is, you know, from your perspective and what

you're kind of seeing, maybe some of your portfolio companies or companies that are

coming across your desk, what are some of the most common challenges that AI startups

are having today?

You know, specifically for some of these AI startups and how do you think that they can

overcome these?

Yeah.

You know, I think the first thing I'll say is, you know, AI in startups, right, as part

of sort of products and technologies has been around for a while, right?

Yeah.

I mean, the AI revolution didn't start in whatever November 2022 and it was, you know, the engagement

and obviously it's caught the imagination of, you know, of the world at large.

So I think from my perspective, really, if I were to think about AI, AI is really a

tool, right?

And I go back to sort of first principles, which is, you know, how are you solving the

customer's problem and how is the customer deriving value?

And I think a lot of sort of the challenge with AI, right, or sort of the challenge,

but the challenge opportunity is really to understand deeply how AI can further help

a company engage with their customers in a meaningful way or deliver value to their

customers in a meaningful way, in a better way than the way they were doing in the past.

If those two don't check out, then there's no reason for you to be using AI, right?

So I think that's the important thing to understand.

AI in and of itself is not sort of, you know, it's a technology and so how you use it to

deliver value is kind of where the rubber meets the road.

So I think when we kind of look at startups in this particular domain, you know, I have

been in my portfolio, for example, an insights portfolio at large, a lot of companies that

have been leveraging AI, you know, for automation, for natural language processing, OCR, right,

computer vision, you know, predictive analytics, like all of these things which are essentially

a different generation of AI are already incorporated into the platform.

So the generative side of things, which is obviously the current sort of transition,

if you're current wave of AI, allows startups to essentially create a much better user interface,

much simpler user interface, you know, like using natural language to ask questions or

replacing custom dashboards with, you know, generative AI potentially creating, you know,

creating to presenting the information the way you want it.

So I think what we're trying to help our startups with is to really help them, you know, just

think through this process of, you know, how is the addition of AI or, you know, the enhancement

of the AI capability that you have on the platform, helping you differentiate yourself

in the market with the better product and better value proposition for customers.

And I think that really comes down to that AI is a tool.

It's not, you know, sort of an end in itself, right?

Yeah.

I love that.

I think that's some really good insights into that.

Something I would be curious, you know, of course, you mentioned this AI revolution,

it didn't just start recently, this has been ongoing for a long time, but it does seem

to be accelerating.

And maybe it's just we're more aware of what's, you know, the acceleration, but it seems

everyone being interested in it.

Now everyone's, you know, all the companies are kind of focused on building on it.

Something I'd ask is, you know, as AI continues to grow, what are some areas of opportunity

that you're the most excited about for the next, you know, kind of wave of these AI or

startups and kind of the field?

Yeah.

Yeah, and you're right.

I think, you know, clearly this sort of generation of AI connects with the end user in a much

more profound way.

Now, let's say a predictive analytics, you know, engine that's kind of doing risk predictions

or failure predictions, you know, that's not quite visible, not, you know, something that

you as a consumer or even a knowledge worker can engage with, right?

The fact that the degenerative side, the natural language interfaces it enables is profound.

So I can see like three areas where, you know, this generation of AI is going to be, you

know, significantly sort of transformative, you know, think about sort of the best product

market fit today for a generative AI product, it's the coding co-pilots, right?

Yeah.

You know, those are, you know, for a experienced programmer and it's not for the novice, right?

It truly is game changing in terms of your productivity.

And so we've, you know, we've heard from a lot of CIOs that as these coding co-pilots

get deployed, they're seeing, you know, anywhere from 20 to 30 percent productivity improvements

in their amongst their engineers.

So that's a clear use case, it delivers value, it delivers in a significantly better experience

for developers and it's been rolled out at scale in a lot of companies, right?

So I think that that's almost the most optimal product market fit that you have today for

a generative AI product.

The other area obviously isn't in the space of kind of, you know, copy generation, right?

So, you know, you just saw a writer, one of our companies, by the way, raised a big ground

last week.

Yes.

I did a podcast on that.

Very exciting.

Yeah.

I mean, and it's because they can deliver immediate value, right?

You know, productivity for marketing professionals as well as the function as a whole.

So that's another clear area where output is being generated and AI is helping accelerate

that process, right?

With a human in the loop, right?

Making things much more efficient, much more faster, much more accurate, right?

So that's another area.

The third area, I think, is really sort of where we're still in the exploratory stage,

but we see a lot of sort of efforts in the space is really about data extraction summarization,

right?

Because this is another superpower of generative AI.

So you know, you can think about like examples where, you know, if you're doing research

on the new drug, being able to kind of study drug interactions, right?

You might have this content spread out in multiple different research papers or document,

you know, or publications of different drug providers, be able to synthesize all of that

and help a human researcher accelerate their process of figuring out, right, in a good

amount of detail these interactions and where they need to focus their research on.

So this whole sort of data extraction and summarization as kind of a part of a business

process.

Is another area where we see, I think, a lot of experimentation happening across different

verticals.

You know, it could be pharmaceuticals, it could be automobile, right?

Could be, you know, just even data synthesis, things like named entity extraction, I think

is going to be, you know, pretty significant, right?

And then the other area is automation, automation of workflows.

And you know, you've had sort of a generation of, you know, business process automation out

there for a while, RPA companies, you know, that have been out there for a while.

I think generative AI is transformational in this space.

And primarily because I think you had a lot of these like no-code, low-code ways of approaching

automation.

Yeah.

Which could potentially, and sell sort of TVD being worked out, right, replaced by a natural

language interface.

So, you know, the sort of utopia of this kind of technology is that you can describe an

automation, you as a knowledge worker might say, hey, you know, scrape my LinkedIn for

everyone with a founder title, you know, sort them by, put them into a Google doc, sort

them by geography, or by, you know, area like AI, and send that list to my teammates in

a Slack, right?

And you might just write that in natural language, and you know, you should be able to basically

build that automation and have it executed, right?

Yes.

So.

So I think that's the, you know, that's a transformational way where we see like, I mean, I gave you

a knowledge worker example, but there are much more complex workflows in the enterprise

that could potentially be transformed.

So those are some of the areas, I mean, there's a lot more, but you know, this is where I see

a lot of very interesting things happening.

Yeah.

Absolutely love that.

I totally agree with you.

So I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

I think that's the best way to do it.

Machine-generated transcript that may contain inaccuracies.