Using agents to build an agent company: Joao Moura

Summary

The speaker discusses the rapid growth and potential of AI agents, highlighting the impressive execution of 10 million agents in 30 days. He explains the autonomy and adaptability of these agents, which can make decisions and use tools in real-time. The talk covers the anatomy of AI agents, the complexities of building and orchestrating them, and the shift from traditional software development to agent-based automation. The speaker shares his journey as the CEO of Grayi, the creator of Crei, a production-ready library for multi-AI agent automations. He also announces new features like code execution for agents, training for consistent results, and a universal platform for third-party agents. The talk concludes with an offer for companies to try Crei Plus, an enterprise solution for deploying AI agents.

Takeaways

• 😲 Over 10 million AI agents have been executed in the last 30 days, showcasing the rapid growth and adoption of AI in automation.
• 🧠 AI agents are capable of making autonomous decisions and can be used to create complex automations without the need for traditional programming.
• 🚀 The speaker emphasizes the speed at which AI is being adopted and how it's outpacing many people's expectations.
• 🤖 AI agents can be created to perform specific tasks, like content creation or lead qualification, and can be organized into 'crews' for more complex operations.
• 💡 The speaker shares his personal journey of building a company, Grayi, which focuses on AI automation, starting from a personal need to automate his online presence.
• 🌟 The community around Grayi's product, Crei, is growing rapidly with over 16,000 stars on GitHub and an active Discord community.
• 🔧 Crei is described as a production-ready library for building and orchestrating multi-AI agent automations, indicating its robustness and reliability.
• 📈 The speaker highlights the success of using AI agents for marketing and lead qualification, resulting in significant increases in views and customer engagement.
• 🔗 Crei is positioned as a universal platform that can integrate with third-party agents, expanding its capabilities and use cases.
• 🆕 Upcoming features for Crei include code execution capabilities for agents and a training module to ensure consistent results over time.
• 📈 Crei Plus is introduced as an enterprise offering that allows for easy deployment of AI agents into production environments with robust features like autoscaling and private VPCs.

Q & A

How many AI agents were executed in the last 30 days according to the transcript?

10 million AI agents were executed in the last 30 days.

What is the significance of the number of AI agents executed as mentioned in the script?

The number signifies the rapid growth and adoption of AI agents in various applications, indicating a significant shift in the way automation and software development are approached.

What does the term 'agent' refer to in the context of the transcript?

In the context of the transcript, 'agent' refers to autonomous AI systems capable of making decisions and taking actions based on given options and circumstances, without the need for direct human intervention.

How do AI agents differ from traditional automation in terms of handling complexity as described in the script?

AI agents can adapt to circumstances and build automations in real-time without the need for pre-defined connections or 'dot-connecting' that traditional automation requires. This allows for more complex and dynamic automations.

What are the components that make up the 'anatomy' of an AI agent as discussed in the script?

The components include a central core, tasks, tools, a caching layer, a memory layer, training mechanisms, and guardrails to ensure the agent functions correctly and securely.

What is 'Crew' in the context of the transcript, and how does it relate to AI agents?

Crew, in this context, refers to a group of AI agents that work together, sharing caching and memory, to perform complex tasks. It represents a higher level of AI collaboration and automation.

What is CRE AI, and how does it fit into the narrative of the transcript?

CRE AI is a production-ready library for building and orchestrating multi-AI agent automations. It is central to the narrative as it is the tool used to execute and manage the high volume of AI agents mentioned.

How did the founder of Grayi start his journey with AI agents, as described in the script?

The founder started by building AI agents to automate the creation of LinkedIn posts, which led to the development of CRE AI as a tool to further automate various aspects of his professional life.

What is the significance of the number of GitHub stars and Discord community members mentioned in the script?

The number of GitHub stars and Discord community members signifies the growing interest and adoption of CRE AI and AI agent technology within the developer and broader tech community.

What new features or capabilities are announced in the script regarding CRE AI and AI agents?

New features announced include code execution capabilities for agents, a training feature for consistent results, universal platform support for third-party agents, and CRE Plus for enterprise deployment of AI agents.

Outlines

00:00

🤖 AI Agents and Automation

The speaker begins by expressing excitement over the rapid development and execution of AI agents, particularly within the last 30 days. AI agents, such as those created by GPT, are capable of autonomous decision-making and can be used to create content. The speaker explains that traditional automation required pre-defined paths, but with AI agents, one can provide options and let the agents adapt in real-time. The speaker also touches on the complexity of building these agents, mentioning the need for caching, memory layers, training, and guard rails. The talk concludes with the speaker's personal journey, starting with his wife's suggestion to share his work online, leading to the creation of his company and the development of an AI agent library called 'crei'.

05:02

🚀 Scaling Business with AI Agents

The speaker shares his entrepreneurial journey, which began with automating his LinkedIn posts using AI agents. This success led him to automate more aspects of his life, resulting in the creation of 'crei'. He describes building various 'crews' of AI agents for different business functions, such as marketing, lead qualification, and code documentation. Each crew is composed of specialized agents that work together to achieve specific goals. The speaker highlights the exponential growth in views and engagement that resulted from using these AI crews. He also discusses the community and investor support that 'crei' has garnered, and announces new features like code execution for agents, training for consistent results, and the ability to integrate third-party agents.

10:03

🌟 Future of AI Agents and 'crei'

The speaker envisions a future where AI agents are ubiquitous and integral to business operations, comparing their potential impact to that of the internet. He emphasizes the importance of adopting AI agents early and experimenting with their capabilities. The speaker announces 'crei Plus', an enterprise offering that allows users to deploy AI crews as APIs with autoscaling and security features. He also mentions a course on 'crei' for those interested in learning more. Lastly, he introduces a service where a crew of agents can be created based on a company's needs, pushing the code to a GitHub repository and offering a quick start to utilizing AI agents in production.

Keywords

💡AI Agents

AI Agents, as discussed in the video, refer to autonomous software entities that can perform tasks, make decisions, and interact with other systems or agents. They are the core of the automations being built and are exemplified by tools like chatbots and content creators. In the script, the speaker mentions that these agents can be so advanced that they appear reasonable, capable of choosing between various options and operating autonomously, which is a significant shift from traditional automation.

💡Automation

Automation in the context of the video pertains to the process of creating systems that perform tasks automatically without human intervention. The speaker discusses how traditional automations have been linear and straightforward but can become complex when additional elements are introduced. AI Agents offer a new paradigm where automations can be more dynamic and responsive to changing circumstances, as they can adapt and make decisions in real-time.

💡CRE AI

CRE AI is a production-ready library mentioned in the script for building and orchestrating multi-AI agent automations. It is a tool that allows for the creation of complex automation workflows involving multiple AI agents. The speaker highlights that CRE AI is being used to execute a large number of agents, indicating its scalability and robustness in handling real-world automation tasks.

💡Orchestration

Orchestration, in the video, refers to the arrangement and coordination of multiple AI agents to work together in a seamless and efficient manner. It is about managing how these agents interact, share data, and execute tasks in a coordinated fashion. The speaker mentions the complexity that arises when agents need to communicate and work together, which is where orchestration tools like CRE AI come into play.

💡Caching Layer

A caching layer, as mentioned in the script, is a component of the AI agent systems that temporarily stores data to reduce the need to repeatedly fetch the same data from the primary source. This improves the performance and efficiency of the system. The speaker discusses the importance of considering caching when building AI agent systems, especially when agents need to share and access data quickly.

💡Memory Layer

The memory layer in AI agent systems is crucial for retaining information across different interactions and tasks. It allows agents to remember previous actions and decisions, which is essential for context-aware decision-making. The speaker points out that when building AI agents for production, one must consider the need for a memory layer to enable agents to function effectively over time.

💡Guard Rails

Guard rails in the context of AI agent systems are safety measures or constraints put in place to prevent the system from making incorrect or undesirable decisions. The speaker discusses the importance of adding guard rails to AI agents to ensure they operate within predefined boundaries and maintain a level of control and predictability.

💡LLM (Large Language Models)

LLMs, or Large Language Models, are AI models that are trained on vast amounts of text data and can generate human-like text. They are the foundation of many AI agents, enabling them to understand and generate language. The script mentions that these models are so advanced that they can almost look reasonable, highlighting their capability to handle complex language tasks.

💡Production-Ready Framework

A production-ready framework, as discussed in the video, is a software framework that is robust, scalable, and reliable enough to be used in a live production environment. The speaker claims that CRE AI is a production-ready framework, indicating that it has been tested and is capable of handling the demands of real-world applications, including the execution of millions of AI agents.

💡Code Execution

Code execution in the context of AI agents refers to the ability of these agents to write and execute code. The speaker announces a new feature that allows AI agents to build their own tools through code execution, which significantly expands their capabilities. This feature enables agents to automate not just tasks but also the creation of software components, showcasing the advanced level of automation possible with AI.

Highlights

10 million AI agents were executed in the last 30 days, showcasing the rapid growth of AI automation.

AI agents can make autonomous decisions and use tools in real-time, revolutionizing automation.

LLMs like ChatGPT are being used to create content, demonstrating their versatility.

Agents can adapt to circumstances without needing predefined connections, simplifying complex automations.

The anatomy of AI agents includes a core, tasks, and tools, with additional layers for production use.

Caching, memory, and guard rails are critical components when building agents for production.

Agents can communicate with each other, adding a layer of complexity to AI automation.

Crew AI is a production-ready library for building and orchestrating multi-AI agent automations.

Crew AI has been adopted by a community of over 16,000 on GitHub and 8,000 on Discord.

The founder's journey with AI automation started with automating LinkedIn posts.

Crew AI was developed to help the founder automate more aspects of his work.

Marketing crews were created to automate content creation and social media analysis.

Lead qualification crews were developed to analyze customer responses and CRM data.

Code documentation crews were built to automate the creation of technical documentation.

Crew AI is being used by various companies for diverse applications.

Investors like Darh CTO of HubSpot and Jack Outman vouch for Crew AI's capabilities.

Crew AI is working on code execution features to allow agents to build their own tools.

A new feature called 'Train Your Crew' will allow for consistent results from agents.

Crew AI is developing a universal platform to integrate third-party agents.

Crew Plus is an enterprise offering that allows for easy deployment of crews as APIs.

The first 50 companies to sign up get access to Crew Plus within 24 hours.

A crew that can build your crew is available, automating the creation of your first crew.

Transcripts

[Music]

10 million

62,000

922 over 10 million and a half that's

how many agents got executed with crei

in the last 30 days

yeah and this is crazy I'm so impressed

by this because this is real it's real

and it's moving way fast than most of

people think and I assume most of you

here know what AI agents are but I'm

going to catch you up if you don't real

quick so llms we all know them chat GPT

turns out great to create content and

they're so good that they almost look

their reasonable they can choose between

left and right and up and down and all

the other options and if you get them to

chat themselves or to a copy of them

guess what you can leave the room you

have an agent basically it can take its

own decisions it can use the tools it

can be autonomous so if you didn't know

what agent was there you do now you

might be asking great now what what's up

to me well we have been building

automations as Engineers for decades and

usually starts pretty straightforward

it's like hey I want to go from A to B

but then what happens when you add C and

and then you get D and this things can

get complex pretty quick and that's how

legacies and headaches are born but uh

turns out that with agents you don't

necessarily need to do that you don't

need to connect the dots you give it the

options and the Agents can adapt to the

circumstances that they are met and they

can do that in real time so that allows

them to build automations that were

never possible before that you couldn't

do it and when you think about the

anatomy of these agents and what they

look like they might look pretty simple

at first you might say like well you

have a na Lim in the center and you have

task and you have tools but once they

start to building these things in

production for real you quickly realize

that you got to think about well I need

a caching layer I need a memory layer I

need to train them I need to find a way

to add guard rails and so much more that

goes into that and then now you're going

to like them to talk to each other and

that adds another complexity layer and

then when they're in a crew you want to

still think about the caching but now

shared and the memory and now it's

shared there's so much that goes into

this and then you can go one extra level

and get multiple Crews to talk to each

other how that goes to say that the way

that we have been building software is

changing a lot if you think about the

way that we used to do it's very strong

time all the software that we have view

is very strong time you start with

knowing exactly the inputs that are

coming in it's a form it's an integer

it's a string you know what's happening

you're summing it up you're multiplying

and then you have have a very strong

output to the point that you can write

basically any tests because the behavior

is always the same but with AI agents

and any AI apps for what it's worth

everything is fuzzy uh you don't know

what's coming in yes it's a string but

can be a CSV can be a rasp can be a

random joke and then these models are

basically black box and you don't

necessarily know what's coming out of it

and you know what I love it so this is

happening now

and I'm being serious every single day a

100,000 crews are

executed and I'm talking like every

day and I mean I have been talking a lot

about cre Ai and uh creai is a a

production ready library to build and

orchestrate multi- AI agents automations

and we'll talk more about that in a

second and um I don't know exactly what

like uh is the like the book that

definition of a production ready

framework but I'm pretty sure that

involves running more than 10 million

agents every month so uh I I like to

claim that and the fact that we have

been beaing this means that we get a lot

of exposure to a lot of use cases what

are people building out there how

they're using this and it's so good

before I move along really show our fans

real quick who has tried crei raise your

hands I like this but we're gonna have

even higher number

so I'm joal my name is kind of hard to

pronounce I go by Joe sometimes nice to

meet you I'm the CEO and founder of

grayi and the way that I build this

company has been a very interesting

Journey everything start back in Brazil

I'm a long way from home and everything

started with my wife I'm very blessed to

have a very smart wife and I have been

working clear bit for many years before

starting crei and my wife told me you

know what you're buing a lot of

interesting stuff with like llms you

should be sharing more about it online

but I suck at writing LinkedIn posts so

as a good engineer I was like Hey I'm

going to write some agents to do that

for me it turns out it

work I got so many views everyone's

going into my LinkedIn and I was soed I

was like you know what I want to

automate my life away I don't want to do

anything anymore I want to just relax

well for my surprise it doesn't turn out

that way uh and I start to building cre

I because I want to use the same thing

to build more and more agents the

problem was all that happened in my

anniversary so you can see that I was

having a lot of fun but at the same

point my wife doesn't like me to spend

too much time in the computer when we're

in the holidays uh but little did she

know that I was working super early and

I was hacking away and I was buing PRI

and things start to cook off and we

start to getting bugs like rabbit hole

reports hallucinations two erors I'm not

going to lie things got a little crazy

for a hot second there for us but turns

out with that also cre a gate community

over 16,000 stars in GitHub uh a Discord

Community with over 8,000 people and

then someone created a Reddit I didn't

know but we have a Reddit and that's

amazing and then not too long after that

Engineers start to like reach out and

then companies start to reach out and

I'm talking about hundreds of thousands

of people and I'm like all right we need

to scale this up but then how we do it

how do we scale a company in such a

competitive market guess what the answer

was in front of me all along we need

agents and so did I bu some them agents

so let me tell you how I start I was

like hey let's start simple this is a

company what do we need we need

marketing so I build a marketing crew I

was like I'm going to build first a

content creator specialist a social

media analyst a senior content writer

and a chief content officer bring them

out together together this is my

marketing crew I'm going to shoveling

rough ideas that kind of suck and I want

to get something great so they're going

to check acts and check LinkedIn and

what other people were talking about

this they're going to search internet

and learn more about the topic they're

going to look at my previous experience

and they're going to give me an

incredible draft and then I started

posting it out and again guess what it

worked we got 10x more views in 16 days

60 freaking days and I was loving it but

with that came a problem I was like well

I need to move on I I need to like now

serve these people how do I qualify them

well I need to go the next level I did a

simple crew I'm going to step up the

ladder I'm going to do the next step the

higher impact but L lower risk so this

is what I did I did a lead qualification

crew so I was right I'm going to bring

up a lead analyst expert I'm going to

bring an industry researcher specialist

in a strategic planner I'm going to wrap

them together into a lead qualification

crew I'm going to shoveling my lead

responses and I want them to analyze the

answers I want them to compare them with

my CRM data I want them to research the

industry and give me like a score use

cases talking points so I can jump in a

meeting right away guess what it

worked the problem is it worked too

out I end up

doing 15 plus customer calls in 2 weeks

it was crazy you know what I don't

regret it I love it so this is what

happened I start to expand more let's

build more crews we have marketing we

have lead qualification let's do code

documentation so if you try crew all

those docks we didn't write it agents do

it for us and I was like I want to do

more and start to do email and do more

and more and it works so to the point

that these are some of the companies

they're now building with crew they're

using crew and it's insane to me and hey

if you don't like these companies you

don't believe that well believe some of

our investors darh CTO of hubs spot or

Jack outman I mean they can vouch for us

we're doing pretty well and what about

the future like where is this thing

going well as an llm model I can't I'm

kidding so

actually Jenn is not getting back in the

bottle this is going to be huge bigger

than the internet we all knew it like

this this is not going back people are

not going to stop using Agents from one

day to the other

well this is my advice for you be

adopter don't wait for other use cases

start simple expend to low risk and high

impact that's what we did but hey I'm

not going to finish here in Cai we are

known because we sheep them fast so I'm

going to make some announcements of some

of the stuff that we are working that

I'm super excited about first thing your

agents need tools right so why don't you

let them build their own tools so we are

working with code execution what means

that in the new version all you got to

do is create an instance of automated

coder command line code

executor come on you're not buying this

I'm not Auto Jam or whatever other

framework are using we're crew AI all

you got to do it's one flag allow code

execution that works your agents can

code now you don't got to worry about

this another thing that we are working

on you know how you do when you hire a

new employee you train them why not do

that with her crew so you can get

consistent results over time well

there's a new feature train your crew

it's a new CLI you can run that and you

can give instructions to it and that's

going to become baked into the memory of

your agents to the point they're going

to give you consistent results every

time moving forward but we're not

stopping that as well there's more you

know what I like to think about us as we

don't see agent callers we want all the

agents so bring them all we're a

universal platform bring any third part

agent you know your Yama index agent

your link sh agent your autogen agent I

mean I don't know why you would do

anything else because you got a crew but

hey come on you can bring them into the

party and they're going to have all the

crew AI agents features the shared

memory the same tools you're going to be

able to use all them if you and then

again the best thing about all this you

can try it today we just shipped the

version before I come in the stage if

you want to try it right before this

call or later in today you can give it a

try it's a new version it's live and if

you again that is not exciting enough

maybe you want to hear from another of

our investors and they

so you can and check it out we put

together a 2hour course on how to learn

about crew aai and all you got to do is

go to learn.

crew.com

and final thing I promise I'm know that

be right at time bear with

me this conference has been one the best

conference I have been who here agrees

with

that right there's one thing though I

heard a lot of like teing a lot of like

coming Sue type of Dees and I don't know

about you but I'm a little sick of

that so why don't we actually start to

bring some like agents into

production so I want to talk about cre

plus it's an Enterprise offering what

some of those companies that I showed

you were are using it and with cre plus

now you build your Crews the way that

they're running your terminal but you

basically can select them push them to

GitHub in three minutes they become an

API and I'm talking about a real API I'm

talking about about autoscaling

protected by a barer token with a

private VPC everything that you need to

run those things in production and then

you can also like one click away export

that into a react component and now you

basically have a UI that you can demo

and you can customize any any way that

you want so you can basically connect

your agents like in a few minutes to

anything and there is more for the first

50 companies that signed up using this

link we're going to give you access to

crei Plus in less than 24 hours and I

also have one extra thing you don't even

have to build your first crew turns out

I pull an out either I have a crew that

can build your

crew you heard me right based on your

email and your company name alone this

crew is going to run is going to create

your crew push into a GitHub repository

and that can be the first crew that you

Deploy on CI plus so hey why don't we

leave at that it's starting to become a

little like uh ugly for the other guys

so hey thank you so much I catch you in

the confence

[Music]