Vertical AI: The Next Big Startup Trend
Summary
TLDRThe transcript discusses the emergence of vertical AI startups focused on specific roles in society, such as AI for lawyers, doctors, and software engineers. These startups aim to enhance productivity by automating complex tasks. The conversation highlights the potential for AI to transform various professions, suggesting a future where individuals can leverage AI 'conductors' to manage virtual teams, leading to a significant increase in productivity and the possibility of millions of small companies run by solo entrepreneurs with AI assistance.
Takeaways
- 🚀 The emergence of vertical AI startups is focused on specific roles in society, building specialized applications for tasks like law, medicine, tax assistance, and customer support.
- 🤖 Large, general-purpose AI language models like OpenAI's GPT and Google's Gemini are trained on the open internet and can answer a wide range of questions, though not always accurately.
- 🔧 A startup named Cognition has debuted an AI software engineer tool called Devon, which has gone viral for its ability to fix bugs and build apps in real-time.
- 💬 Speculation suggests Devon may be built on GPT-4 from OpenAI, though this is unconfirmed. The tool is designed to enhance reasoning and long-term planning capabilities within existing language models.
- 📈 Benchmarks are being developed to test the performance of language models in coding, with Devon showing superior results compared to generic language models.
- 🌟 The progress in AI is rapid, with the potential to make complex jobs more accessible through command line interfaces, automating processes behind the scenes.
- 🔥 The increased efficiency of developers through AI tools like Devon could lead to a greater demand for human expertise to manage and refine AI-generated code.
- 🛠️ The shift from AI co-pilots assisting developers to AI taking the pilot role signifies a transition in how AI is integrated into the development process.
- 🌐 The evolution of AI is expected to lead to the creation of more solo entrepreneurs and smaller companies, leveraging AI to multiply productivity and reduce operational costs.
- 📊 The long-term impact of AI on job roles may not be about replacement but rather about 'leveling up', where humans work alongside AI to achieve higher productivity and innovation.
Q & A
What is the main difference between general-purpose AI language models and vertical AI startups?
-General-purpose AI language models like OpenAI's GPT and Google's Gemini are trained on the open internet and can answer a wide range of questions, while vertical AI startups focus on specific job titles or roles in society, building applications tailored to those specific functions.
How does the AI startup Harvey assist lawyers?
-Harvey is an AI specifically designed for lawyers, presumably to automate legal tasks, provide legal research assistance, or offer other law-related services that save time and improve efficiency.
What is the role of the AI notaker developed by the startup Bridge?
-Bridge's AI notaker is designed to assist doctors by taking notes during their work, potentially saving them hours each day by automating the documentation process.
How does the AI tax assistant, Tax GPT, function?
-Tax GPT is an AI tool that assists with tax-related tasks, likely automating tax preparation, calculations, and offering guidance on tax laws and regulations to streamline the tax process for users.
What is the primary function of the AI software engineer tool called Devon?
-Devon is an AI tool that mimics the role of a software engineer, capable of fixing bugs, fine-tuning AI models, and building applications end-to-end, thereby assisting or even replacing human engineers in certain coding tasks.
What is the speculated basis of the Devon AI tool?
-There is speculation that Devon was built on GPT-4 from OpenAI, although this has not been confirmed. The CEO has mentioned that Devon was created by tweaking reasoning and long-term planning capabilities in an existing large language model (LLM).
How does the performance of Devon compare to other major coding models?
-According to the data from coding benchmarks, Devon outperforms generic language models, indicating that it is more effective in coding tasks due to its specialized training and capabilities.
What is the potential impact of these role-based AI tools on the job market?
-These role-based AI tools are expected to make certain job functions more accessible and automate complex tasks, potentially increasing productivity and efficiency. However, they may also require human oversight, especially for tasks that the AI does not perform perfectly, leading to a need for human expertise and creativity.
How does the evolution of AI in coding compare to the evolution of the internet?
-The evolution of AI in coding is similar to the internet's impact on networking software. Just as the internet enabled new business models by moving traditional businesses online, AI is now enabling the creation of specialized AI tools that replace specific human roles, leading to a new era of productivity and innovation.
What is the potential future of startups and solo entrepreneurs with the advent of AI conductors?
-The future may see millions of companies run by solo entrepreneurs with the help of AI conductors, agents, and bots. This would allow individuals to manage and scale their businesses with minimal human resources, leading to a significant increase in productivity and potentially a reduction in operational costs for companies.
How has the process of creating and launching a new product or service evolved over the years?
-The process has become significantly easier and more cost-effective over time. The advent of cloud services like AWS, developer tools, APIs, and app stores has abstracted away much of the infrastructure and distribution challenges, allowing solo developers and small teams to launch products with less capital and resources than ever before.
Outlines
🚀 Emergence of Vertical AI Startups
This paragraph discusses the rise of vertical AI startups that focus on specific roles or job titles in society, creating specialized applications. It highlights examples such as Harvey (AI for lawyers), a bridge (AI notaker for doctors), TaxGPT (AI tax assistant), and NCR (AI for customer support). The conversation emphasizes the potential of these startups to improve productivity and efficiency in various sectors. The recent launch of a tool named Devon by a startup called Cognition is mentioned, which has gone viral for its ability to fix bugs and build applications in real time. Speculations about Devon's development on GPT-4 from OpenAI are addressed, along with its performance on coding benchmarks compared to generic language models.
🌟 Role-Based AI and the Future of Development
The discussion in this paragraph revolves around the impact of role-based AI on the field of software development. It emphasizes the rapid progress in AI, shifting from co-piloting to taking the pilot's seat in coding tasks. The conversation explores the potential of AI to automate and scale up tasks traditionally performed by humans, such as lawyers and accountants. The idea of AI replacing specific human roles is contrasted with the notion of enhancing human capabilities through AI collaboration. The paragraph also touches on the challenges of working with existing code bases and the different approaches companies are taking to integrate AI into software development, such as GitHub's co-pilot and Source graft's Cody.
📈 The Impact on Startups and Entrepreneurship
This paragraph examines the broader implications of AI advancements on startups and entrepreneurship. It predicts a future where individuals can run companies with the assistance of AI conductors, agents, and bots, significantly reducing operational costs and enabling solo entrepreneurs to succeed. The conversation also reflects on the historical context of app development and the decreasing resources required to launch a startup. It acknowledges that while the barrier to entry has lowered, creating something profound still often requires a small team and financial investment.
Mindmap
Keywords
💡AI startups
💡Language models
💡Vertical AI
💡Specialization
💡Productivity
💡Code autonmy
💡Conductor
💡Agent-first approach
💡Context-first approach
💡Solo entrepreneur
💡Economic productivity
Highlights
Vertical AI startups are emerging, focusing on specific roles in society.
These startups are building apps around job titles, such as AI for lawyers or doctors.
Harvey is an AI for lawyers, Bridge is an AI notaker for doctors, and Tax GPT is an AI tax assistant.
NCR's AI is designed for customer support, and Brett Tor's startup is in this space.
Cognition's tool, Devon, is an AI software engineer that has gone viral on演示.
Devon is speculated to be built on GPT-4 from OpenAI, though not confirmed.
Devon's performance on coding benchmarks is significantly better than a generic language model.
The role-based vertical startups are powerful, as they make complex tasks more accessible.
These tools will automate processes, making developers more valued for their expertise.
The demos showcased AI's ability to find and remediate errors in code.
The evolution of AI in coding is moving from co-piloting to a more autonomous role.
The future may see AI 'conductors' coordinating teams of AI agents.
AI will not replace humans but will level them up, increasing productivity.
The economic productivity will rise as AI takes on specific human roles.
The future could see millions of companies run by individuals with AI assistance.
Solo entrepreneurs will benefit from AI agents, reducing the need for large teams and funding.
It's never been easier to start creating something as a solo developer.
For profound projects, a small team of developers and some funding will still be necessary.
The barrier to entry for launching an MVP has significantly decreased over time.
The trend shows that coding and app development are becoming increasingly accessible.
Transcripts
vertical AI startups are starting to
Make Some Noise we all know about large
language models we've talked about them
here if you listen to this program you
know about open AI Google's Gemini
previously known as Bard anthropic
Claude all this stuff their general
purpose they've been trained on the open
internet as we were just discussing so
they can answer questions about almost
anything and yeah sometimes it's correct
sometimes they're incorrect but it's
showing promise there is another school
of thought here that's emerging in
startups iCal AI these companies are
kind of taking a job title a role in
society and they are building vertical
apps Harvey is AI for lawyers a bridge
is doing an AI notaker for doctors saves
them hours a day according to them tax
GPT is an AI tax assistant NCR is AI for
customer support that's Brett tor's new
startup this week a startup called
cognition debut a tool called Devon
they're calling it an AI software
engineer the demo went viral on X uh you
probably seen them all over the place
and in the news if you watch it you can
see Devon fixing bugs in real time fine
tuning an AI model building apps end to
endend and people are speculating Devon
was built on GPT 4 from open AI That's
not
confirmed but according to the CEO Devon
was built by tweaking reasoning and
long-term planning into an existing llm
here's how it ranks against other major
models on coding benchmarks they're
building all these bench marks to test
each language model and as you can see
it's according to this chart and
according to their data doing much
better than just a generic language
model kind of makes sense jamat did you
see these demos this week I think I saw
you on the group chat talking about it
and what was your take on these
role-based vertical startups oh I think
this is so powerful I mean it's
incredible because we're measuring this
progress in like what week over week
feels like
yeah I think the point that you should
take away is that
the most of these very difficult in
impenetrable job types for the average
person if this if you said to them hey
become a developer that's like a
complicated Journey
right it's just going to be now
like a command line interface where you
just kind of describe in English what
you want to do and all of this stuff
will just happen behind the scenes and
it'll be totally automated so that'll
grow the number of people that can use
these tools at the same time it'll make
the developers I think even more valued
because you're going to need people in
the guts of these models and in the code
that it generates because it's not
always going to work perfectly there's
always going to be some kind of
hallucination some stuff is not going to
compile now the demos that they did
though were incredible they were able to
find errors they were able to remediate
errors in
code I mean I just I think it's really
really special you've been on co-pilots
for the past year talking about that
this is slightly different we're moving
from hey here's a co-pilot somebody
helping a developer to hey here's a
developer working and now they have a
supervisor so what do you think of these
sort of role-based agents and how
quickly we went from year one
co-piloting to okay now they're the
pilot and we're sitting in the co-pilot
seat watching them fly the plane yeah
well look F first of all everyone's
working on autonomous coding or working
towards that this is like one of the
core most obvious use cases of llms
because code is text and it can also be
run through a compiler to debug it so
you can also get to in theory you can
get to high levels of accuracy yet
although in the example that you gave
Jason this new product was only at 133%
so there's still a long way to go but
the potential is clearly there so a lot
of companies are working on some
variation of this
idea Devin is I guess you could call it
an agent first approach and I think
that's very cool for generating new
software projects but where I think this
gets much trickier and is much more
difficult is when you're working in
existing code bases and just to talk my
own book for a second we're an investor
in a company called Source graft they
have a product called Cody and their
whole approach is context first as
opposed to agent first it's all about
getting getting the co-pilot to work
inside of existing code bases so
different companies are coming at this
from different approaches GitHub
co-pilot I think is kind of more like
Cody where it's all about making an
existing code base more useful whereas
Devon again is starting with I think net
new code bases but that's going to demo
really well and so that's what you're
seeing is like these really cool Demos
in any event the larger picture here is
that we are going to get better at
better at coding auton ly I guess you
could say and I don't know if it gets
ever gets to 100% where you don't need
coders anymore but it's going to make
coders much more productive over time
you're going to get this huge multiplier
effect on the ability to write code and
that's really exciting for a bunch of
obvious reasons free we've been tracking
this Evolution from you know Gmail guess
the next word guess the next phrase
guess the next sentence to co-pilots now
we have these role-based agent-based
solutions that startups are pursuing
what's next if we follow this thread
what would the next Evolution here B
well the big push has been for this
notion of AGI to replace a
human and I think what we're seeing
is software that replaces a specific
human doing a specific thing like being
a lawyer being an accountant being an
art director if you think about the
internet when the internet which was
like networking software and the
capabilities that arose from the
connection of all these computers during
the internet era The Innovation was
everyone tried to create a business
model which was how do you take an
existing vertical business and put it on
the internet I think what we're seeing
in this era is everyone's taking a
vertical human and creating a vertical
version of a human um in the AI era and
so um I think like the the success will
probably acrew to one company that
replaces one set of core human services
like being a lawyer being an
accountant you know being an artist in
whatever way and that that ends up being
the specific vertical tool that people
will use to automate and scale up their
ability to do that task in an automated
way because I think that there's like a
great deal
of capability that emerges in the fine
tuning and the unique data that certain
people may have to make that one tool
better than the rest and therefore
everyone will end up using this one
lawyer service or this one Accounting
Service or what have you so I definitely
think that's kind of what we're seeing
yeah I think it's pretty obvious where
this is going you got co-pilots
assisting a developer or a lawyer then
the next or a writer then they got the
next phase okay you've got a peer so
you're doing peer programming or
somebody's kind of working alongside you
you're checking their work hey maybe
they're even checking your work seeing
if you have bugs where this is going to
be next year is there's going to be a
conductor there's going to be somebody
who has a role or a piece of software
has a role where you say hey you're a
CEO of a company you're a Founder a
product manager here's your lawyer
here's your accountant here's your
developers here's your designer and now
you will coordinate those five people
now imagine how that changes startups
when you as an individual have a
conductor working with you and says you
know what I don't know if I agree with
this legal advice that's coming in in
relation to the tax advice and maybe we
should not even add this feature to the
program let's talk to the product
manager the agent product manager about
taking that feature out so we don't have
these Downstream legal issues and we
don't even have to file taxes in this
you know area it's going to get really
interesting next year when they have a
conductor the other way it may go Jason
is you have a lawyer that has 50
Associates working for them through the
AI so you don't replace the lawyer you
don't replace the software engineer the
software engineer levels up and now the
software Eng has 50 Engineers available
50 agents running doing tasks for them
you do still you do still need humans
with domain expertise and creativity to
Think Through architecture to Think
Through process and to make sure that
the AI agents are doing their job so I
think what it creates as extraordinary
leverage for people and organizations
which is why generally economic
productivity goes up people don't lose
jobs they level up in this phase the the
Opex of companies will probably be cut
in
half at the limit
I think Jason is
actually absolutely right I think you
find that there'll be millions of
companies with one person and then a
whole layer of software and conductors
and agents and Bots that's the future
yeah so you won't have these engineering
people that person should be running
their own company and so you'll just
have millions and millions and millions
and maybe billions of companies and I
think that that's really exciting not
all of them will work many of them will
fail and a few of them will be
ginormous and it'll be up to the person
who can navigate and be a conductor as
you said you know yeah be really
interesting the solo entrepreneur
movement of the last couple years there
were all these kind of like independent
hackers building one item like Phil
Kaplan did with um drro kid he just had
like two or three people working on that
got very big you know I was telling you
guys about that slopes app I showed you
I I I reached out to the founder of that
I was like hey tell me about the
business like it's enough of a business
to support one person or two people like
there will be a lot of these apps or
Services one
conductor and you know it makes what
half million a year 3 million a year
whatever it's enough to support one two
three people working on it but
previously you know you be going to the
Venture Community like oh what did it
take a modern app company Sachs to kind
of build an Android in a an IOS app just
you know five 10 years ago if we were
funding one 10 years ago what would the
footprint look like for you know a
consumer app company if you're going to
go all the way back to like the late 9
90s during the era I remember that with
PayPal just to launch really what was an
MVP we had I'd say a dozen developers
and it was pretty expensive and we had
to set up our own Colo there was all
this infrastructure that all got
abstracted away with AWS then you move
to the mobile er uh and the app stores
provide there there's just a lot more
developer tools more apis yeah well as
well as distribution but it's just it's
far easier to code these apps so things
have gotten easier and easier that's the
trend if that's the point you're trying
to make it's certainly never been easier
to get started in creating something if
you're a solo developer yeah that being
said I think that depending on what
you're trying to do it's still usually
the case that if you're trying to do
something interesting and profound
you're going to need a small team of
developers and a couple million bucks to
get you started yeah it used to be Ru of
themb I think 12 people for an app
company got two working on each platform
a couple designers couple
testing and uh design ux you get to 10
12 people to to run a modern one
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