Episode 8: AI for Everyone with Learn2AI

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Welcome back to Beyond Giving. I’m Zac, the nonprofit guy, and you are watching the Best non nonprofit podcast on the Boost Network sponsored by Nonprofits hq. This week we’ve got a really cool conversation centered around AI and helping people understand how to really maximize their usage on that, uh, on, on AI and their knowledge to kind of upskill.

And this nonprofit is called Learn to ai. We’ve got Mihir and Aryan with us, uh, to kind of share that. So let’s start by kind of learning about your guys’ background and what kind of led to this. Thank you so much, uh, Zac for having us. We have been knowing each other, but this is the first time that we are conversing like this.

But thank you so much for having us to begin with. Uh, I have the experience of around 14 plus years in the tech industry. Did my engineering have been a program like a developer to begin with in PHP Zen and that’s when Oh, Zen Zen. Oh, that’s an interesting place to take off. Absolutely. [00:01:00] It was, it was. So basically that’s how it started.

And then of course climbed up the ladder, uh, started the different roles of operations, uh, sales, business development. But then what I really enjoyed is basically starting up things from completely new environment. So that’s when I started living in Mexico, in uk. Yeah, Spain and being in the states for a while, but the idea is then how to set up something, which is very challenging, but very close to my heart and how to really set it up from ground.

That’s what gives me pleasure. But, uh, of course I’m being a big advocate of the industry. I mean, with technology, especially what’s happening around. Is what we have been known as machine learning. Now it’s called ai, like gen ai. The cool word is out. Yeah. And like it’s interesting ’cause like the subset of ML has really grown to encompass a bunch of different things.

Not just in terms of building software, but actually using software too. Absolutely. Like changes the way people use it, which is really cool. Now, you’ve always been somewhere around ai, [00:02:00] whether you’re using it to build for clients or using it for productivity. Yourself. Right. And so it does make sense that you’re kind of going in this like, uh, AI type, uh, direction.

Absolutely. And we’ll talk about it in a while. Uh, but the idea is that since we have been doing more like as a tech company, as a staffing company, as a solution company, then what about those who are not into like technology? What about those. Now considering we have those tools where with prompting you can do a lot of things.

You don’t need to be a nerd, you don’t need to be a geek. Absolutely. For writing a python code, for making things work. You don’t need to be technical to build a technical product. Absolutely. But then how people are ashamed, you know, people are afraid of, oh, what if I, and I’m talking about executives as well.

Yep. Or working on the large firms, but then they’re like, oh, I look like a fool if I just open up myself. That’s about me. So that’s, that’s what kind of led me to start something like learn to ai. Mm-hmm. And so you founded Learn to ai Yes. And then brought in ION as kind of a, a co-founder to help you kind of build out the organization.

Right. So, Aryan, tell me a little bit about [00:03:00] your background and how you managed to, uh, join this nonprofit with Mihir. Yeah. So my name is Aryan, and first of all, thank you for giving us opportunity. I’m going to be a high school senior. Okay. And, um, I would say I use AI more than your average team does. I use AI for quite literally everything, like organizing notes.

I mean, now even this, we even, um, do it for, uh, the Indian community outside as well. And so, um, with me here doing, uh, this urge, right, having, wanting to make this learn to AI thing possible, he kind of found me and then together we merged and made this happen. So how are you two connected? So you come from.

These large enterprises, um, you know, building, you wrote PHP, like all this stuff. You use a lot of ai. Um, how did you two actually connect? Where’d you connect and think, oh, this is something I wanna join? So we have someone in common through whom I came in contact with. Guardian. Okay. But the idea was that RNA is half of my h and the [00:04:00] the exciting thing is with the youth, the kind of passion that they bring up.

I’m like, Hey, I wish when I was young. I could have had that much of, you know, enthusiasm, right? I mean, the kind of potential and passion that they share. So when we, we spoke and I were like, Hey, learn to wear, this is what I’m doing. This is what I want to do. And like, Hey, can I team up? And a lot of people ask me this question, but when I kind of spent some more time with him kind of under understood and realized at this age, he’s already leading a lot of initiatives right on, uh, the Indian community level here in San Antonio.

And even in a school. Uh, so yeah, pretty. So like, tell me about, about some of those kind of like initiatives that you’re leading in the area and then I wanna kind of explore what your two roles are at the, the organization. Right. It’s very early stage. Right. So it’s pretty much everybody does everything, but what are your kind of like, areas of expertise that you bring to the org?

Yeah, so, um, I, so if you go to the Indian community, we hold, um, youth events in which we teach the youth about Hinduism and Indian culture [00:05:00] just to kind of, you know, preserve it. We hold many events here in downtown as well. One, a large one being, um, city. Okay. And we, uh, yeah, we have an entire parade. We have stage programs and a lot of that stuff, um, is.

Hectic. And a lot like I, I lead some of it. I’m not saying like lead, lead, but I mean like I help in the planning of it. Um, in school I am, uh, the president. I hold a lot of officer, um, positions for a lot of clubs. So I feel like that’s helped with this speaking thing. A lot of this organizing and like, uh, making sure everything ends up in the department.

Okay, cool. And then, so what does a day-to-day look like at Learn ai? Like, what are you guys currently working on? What, what are you bringing to the table in terms of your expertise areas? What does that look like? I mean, mainly expansion, right? We wanna find different people of different backgrounds to show that it’s not only for.

For example, regulation people. Currently we are working with 4, 3, 4 Media, which is a large media company, but then we wanna make sure that, uh, youth, um, even executives, your average person, small to medium sized businesses, these guys all get [00:06:00] incorporated and we all find cohorts and, um, events for them.

Okay. Just to add on that, the idea is that I am primarily associated with the company with Kaha Staffing and we work like tech and non-tech, staffing, solutioning and everything. Then with the experience and especially living in San Antonio, and San Antonio has been very welcoming. People like you when I came to San Antonio were very generous.

You know, opening the doors, helping in terms of guiding, hey, what to whom you should meet ideally. So I guess over the years have built some good connections. Relations, I would say, with even working with startups to large enterprises, that’s where I see the gap with students. Mm-hmm. Executives, even small to medium businesses.

So. On a day-to-day basis, what we have been doing is earlier we started like building the cohorts, realizing where exactly what kind of cohorts we can build up to. Because considering people have their own work, their own things, their own businesses, but then they still want to learn. We want to educate them.

So we basically plan around that. Right now it’s happening, which is more about [00:07:00] we are already executing some of them. As Aryan said, we are already there is, as we speak, one cohort is going on at the moment, at the very moment. But, uh, the idea is, yeah, it, it brings Is this your first cohort for the org, or not really?

It’s, this is the third one. Okay. This is the third one. Uh, we have done it one for one of the schools and one for kind of a close group of the large executives as well. But then the idea is that gives us joy when we really see making that more interactive and, uh, people really do this and implement this in their daily life for making their own things productive, their own work productive.

So out of it, they’re like, Hey, you know what? We are able to do things in two hours, and now they have six more hours. Not to Netflix and chill, but the idea is you can do something, work on yourself or work on something else that you wish to do, or grab a beer and watch Netflix. Absolutely. Um, yeah, and that’s, that’s awesome.

So how long has Learn two AI kind of been around like, so in my thoughts and ideas and visions, it’s been over a year, but officially, formally, we have started [00:08:00] this over four months now. That’s exciting. That’s a really exciting time when you’re trying to, when you’re defining everything and like ironing out your mission, that sort of thing.

And so when, um, I know a little bit about the different programs that you offer, but can one of you kind of give us like an overview of the different, uh, types of things that you’re teaching, the different resources you provide? Like what does a journey through learn to AI look like? Yeah, so, um, a big one is prompt engineering.

So a lot of this stuff with AI starts with prompting. If you can prompt the AI and tell the AI what you want to do, how you want it to be, you can get the proper outcome. Mm-hmm. So prompt engineering is a really big one. We do, we do, um, AI youth clubs. We do. AI Pacific. Good. Incorporating like things like healthcare into AI as well?

Developers, like the executives, and we do a lot of, so these ones are the four weeks one. Mm-hmm. But we also have planned a few more. So for the executives one, which we did is like for 20 hours, it’s not for weeks. But then we have planned like more than 15 cohorts for now, which. Are about to get unfolded, but the idea is that [00:09:00] how about we can use the Gen AI for ui ux, for biz dev for some of the leaders, but specifically for hrs or for a particular tech scene.

The idea is not to just help them with putting a lot of technical things and build agents in this that, no, but there are tools there. Mm-hmm. The idea is that we want to show with just a 20 bucks of subscription with any of the LLMs. You can really build so many things. Sometimes we feel like, oh, you know what?

We cannot do a lot of things, but you can. Yep. So it’s just enabling them with that. And, and that’s such an interesting thing because like this idea of prompting AI has, has only been recently comparatively to technology, right? It’s only been recently a thing and so, but now it’s like common knowledge, right?

Yeah. Most people don’t understand how to actually construct a prompt or how to get the AI to, I say, think right the way they want it to. But yeah, all these different tools, like you don’t have to be technical to do technical things anymore. I, so I’m a recovering software engineer. Right. That was my, that was my entire career for my first job until we started my current company [00:10:00] and the.

I was so resistant to like paying these stupid subscription fees for these stupid ais, right? We built a lot of ai. I know what’s actually happening under the hood there, but I swear once I started paying for chat GPT, man, life just became so much easier. Absolutely. Uh, you know, I didn’t have to write these stupid emails anymore.

All the like, tedious stuff that I know don’t actually want to do. AI was able to head for me. So people can join one of your cohorts and learn like what’s, what’s the outcome? So they, they’ll understand some prompt engineering. Well, they understand. I know you guys just pitched at 1 million cups this morning, right?

That was a really cool pitch. I know one of the questions in the audience was something around the ethics of using ai, right? And that’s such a nuanced thing. So I do a lot of speaking about the ethics and the safety guardrails you have to add when you implement, uh, your own AI or integrate other AI products into your stack.

So, to give you kind of an example, one of our customers before we onboarded them would take all of their donor information, you know, the names, the addresses, the phone numbers, the amount that they donated. [00:11:00] I think it had like their last four of their payment method, you know, all of this. And they’d paste it into Chachi, BT and ask Chachi PT questions about that.

Right? So when you’re teaching, when you’re teaching people these, uh, way to interact with, uh, these different models. Are you baking in that kind of safety and ethics type of, uh, mentality into that curriculum? Or what does that look like at Learn to ai? That’s a good point, Zac, and that’s a very important point, which people are not realizing, I guess as, as small organizations, they don’t worry a lot considering Okay, how much information they’re sharing still they will have some sensitive information.

Right. And a lot of this will come with the experience of we. I personally, myself and with the companies that I would been involved with, but with implementing solutions for larger companies too. And we are like larger banks, larger insurance companies. So kind of having that understanding about how usually things operate when you scale up from small to medium to large company.

I probably have learned what not to do then more than you know, [00:12:00] which things absolutely to do and which things don’t work, basically. So kind of when we try to do these cohorts for onto ai. We kind of explain them what not to do. So one of the things, for example, for this executive club that we are trying to build is even for a medium to large enterprise company, what if you can build a wrapper around an LLM?

Mm-hmm. And basically either have an end mediaship installed in your own infrastructure or have a wrapper built. So basically it’s one way traffic. Yep. So you, your data doesn’t go out basically to any of these Ls. Then you put everything, still, not everything, but the idea is to put it. Another thing which we have seen so far is that when it comes to companies, right, not all employees care.

Yeah. The idea is that they might be like, Hey, you know what, so instead of fighting the system, what if you enable them saying, Hey, use ai, but don’t use that ai. Basically use the wrap to one ai, which we are offering you. You can name it anything. You know, you can say, Zac AI for nonprofit hq. The idea is use that ai.

So instead of you fighting the system. [00:13:00] Give them something to play with. Like, okay, automate, for example, if you are already in the Microsoft environment, copilot is there, but maybe somehow keep it restricted. Mm-hmm. So it’s just one way traffic. But setting guardrails is very important because you never know one fine day.

Some, someone might call you with all the information, blackmailing this, that, or absolutely fake data is value, right? Yeah. That’s where value in software is, is the data that they hold and the data they process. And so you have all these companies, you know when and when LLMs and your various different AI models started becoming super popular and super cheap and easy to integrate.

They were throwing everything at ai, right? If you had a chat, GPT, uh, API Key, then you were an AI company. And, and that was that. Uh, but most people didn’t consider the danger of the information they were putting into it. And like, uh, you know, we control our AI models, but we still don’t expose it to anything, anything sensitive, right?

We use RAG and a few other things to filter out and aggregate that data. So one of the things to add on is, well, when people start becoming dependent on something, [00:14:00] that’s where the scary thing is. I mean, that’s what we try to explain, use it. Kind of as a platform to step upon it and use and do your job.

Don’t be dependent. Like if the internet is down, I cannot access to check GPT or Gemini. Yep. True. My work is stuck. Well, if the internet is down, I’m probably not working that day anyway. But, um, but yeah, that’s a good point too. ’cause like you have to use AI where it makes sense to actually use ai. Where is it gonna add value?

Where is it gonna move you forward and not be like a barrier? Um, cost of change is hard for companies. It’s hard for just humans in general. Um. So tell me about like this current cohort that you’ve got running, uh, right now. What are they learning? What is a, what is the experience like in one of these, uh, these boot camps or these.

Absolutely. So what they’re called boot camps? What do you call ’em? We just cohorts, cohorts, cohorts far around. So, uh, this one was exclusively planned around. Uh, so what we do is we also customize our cohorts considering okay, if there is a business who wants their own employees or trainers to get trained mm-hmm.

[00:15:00] And to make an impact with whatever they are doing on day-to-day basis. So this was kind of planned around that. So we analyzed Okay. What kind of system they are using in terms of either a CRM. Or for daily communication for their marketing tools. And then we kind of build a cohort around it to just teach them and enable them.

Okay. How with the prompt engineering with the other agents that you can learn how to build with simple manners. But then this one is very fun because it’s a media company, full three, four media and Marcos is a great guy. And that’s how we got the liberty about, hey, you know what? Doing and playing around with stuff so.

We have, uh, been working with them to build agents. So in fact, soon in the next week, they’re gonna present their agents, which they have built, which can help to really elevate what the company wants to achieve mm-hmm. In the next two, three years. Instead of just building some shiny, fancy things, you know, so these cohorts that you’re, you’re creating, you’re, you’re creating a custom curriculum to help the company and their employees accomplish whatever it is they’re trying to [00:16:00] accomplish.

That’s kind of like the end goal that they have the skillset to do that now. And so, so like who you, do you, do you only provide this knowledge through these custom plans through companies? Or do you have like publicly opens who, who’s the target person you’re serving? So for now, what we are doing kind.

We like to preserve the meat of that cohort. Mm-hmm. But what we customize is basically, let’s say the output, which is relevant. So the agent that we might want to showcase or build or offer at the end could be relevant to you. Oh, okay. So you’re still teaching the foundations? Yes. The same principles. Yes.

The same lessons. That’s right. You’re just tailoring it to where at the end they have the output that they’re looking, so then it’s, it’s more useful. Mm-hmm. In terms of, okay, if I am, let’s say if you’re running a restaurant and I’m teaching you everything about, you know. How NASA operates and agents about that.

Maybe not relevant to you. You understood everything about AI at the end, but then the idea is if I give you some agents or if I teach you some tools, which can help you in terms of managing your daily restaurants or reservations [00:17:00] or based there, how to get more customers, the idea is at the end it should be around that.

So, uh, so far that’s how we have been operating, talking about what happens on our like kind of sessions and all. Uh, Aryan has been working very closely, so he’s the one who kind of designs works with our trainers to define Okay, in terms of how it should be, how it should be panned out, you know, how the flow should be is our producer.

Okay, so he’s running the show. So when you’re creating these, like how are you determining what is important to teach? What is more nice to have and like, how are you prioritizing that throughout your cohorts? That is a lot of, um, like basically what the company wants out of it, right? Again, like we, at the end goal, everyone kind of learns the same thing, but then what they get out of is different.

So, uh, based on what 4, 3, 4 Media wanted, we made a, you know, extensive curriculum and these. Interns are, um, they’re, they’re pretty knowledge themselves. So this wasn’t like your regular, uh, prompt engineering course. It was a lot more extensive and a lot more complex. And so working with the trainer, making [00:18:00] the content, um, you know, and all of that, it’s.

It’s a pretty tedious task, as in like sometimes, you know, it’s hard to, uh, construct everything. Mm-hmm. And so a regular day, basically we start off, um, with, uh, like a presentation or a small little activity, and then we try to keep it as hands on as possible. So we use, um, different things like Google Collab and all those things.

And we, uh, make sure that everyone is interactive and we make little group breakouts and we try to. Keep everyone engaged and not fall asleep mid, uh, class or session. So there are some of the collab files, like, uh, proper J files lab mm-hmm. Kind of setup virtual labs that we have created. So what happens is, uh, as Aaron said, you know, we don’t want people just falling asleep.

So the idea is it starts with something, they understand everything, but then it’s an interactive exercise of they also executing the prompts with the instructions that being shown, they’re learning, they’re implementing before the next session. They’re already excited to go home and try it out, you know, [00:19:00] on either their whatever.

That’s how, you know, you had a successful class, a successful course. Exactly. Absolutely. And when you, we start the next session, they’re like bombarding with the question like, Hey, you know what, why he is getting the response and why we are not getting the response. So that makes it feel also good. Yep.

That, yeah, absolutely. Yeah. And it’s cool, like when you can share a skill with somebody and they take that, they learn it, and then they know how to execute it, and they’re excited about utilizing that skill, that’s really cool. But now, so all of this takes, uh, dollars, right? It, it takes money to run an organization to keep things compliant.

It takes money to. Produce these different contents, all of this stuff, right? So how is Learn to AI funded, are you guys funded through public charity contributions, through grants? Like what does that look like for you? For now, we are bootstrap. For now we are, you know, self-funding ourselves. The idea is to really add some value by not just showing that we add value, but we wanna do some of these cohorts.

Definitely. And then the idea is that we definitely want to tap for some of the grants, some of the programs which are out there, which. You know, can support, uh, an [00:20:00] initiative like this, even some of the private institutions Yeah. Blog organizations as well that, uh, we are trying to work around to see, hey, you can support, basically you can be a part of doing something, which can be better.

But then of course, educational institutions is something that definitely AI literacy is something people need to know. Is that something that’s made it to. Now granted I have like opinions about like the school systems and education in the country, right? Um, but is, is AI literacy something that’s being incorporated into education, just generally speaking yet?

Or are we still like way behind on that? We are still behind, um, AI literacy. I think a lot of schools don’t. Prioritize it, not mainly ’cause it’s newer and, um, people again, like can use it for the wrong way. So then I think schools are sort of leaning back on like that, uh, unethical way to use it. Yeah, I mean, you can use, you can use anything unethically, you can use it anything wrong.

Right? But then if it’s, like, if a school promotes it, then it’s like, oh, the school let me use, its so I can use it. And then you kind of have that. But one thing that I have seen is, [00:21:00] uh, I have been meeting few people. I mean, this morning in 1 million cups, I met a high school professor where what’s happening, I guess it, it starts from top to bottom, right?

So if you wanna bring a change, but who’s gonna bring the change? Yep. So you need to educate your staff, or let’s say the professors and everyone like being aware about what’s happening so then they can pass it on. I’m not saying just enabling one right kind of thing about ai. Okay. Now we are gonna learn about ai.

It cannot, unless it’s coming and it’s being supported from top to bottom saying, Hey, you know what, we are there. This is how we are gonna do it. Let’s not do it the usual way. Like let’s say I build a presentation. I don’t want you to build a presentation PowerPoint, use one of the tools, for example.

Absolutely. Or make me a short film using VO three, or SOA or whatnot. But idea is. That all these should be motivations, kids are gonna use it anyhow. Mm-hmm. Yep. And so that probably leaves though like a pretty large gap in skill from what you get, um, going through school and then where you land [00:22:00] once you get in the working world or, or whatever.

And I think that’s probably why AI literacy is super important because all of our tools are kind of based on that, right? And so you need to know how to use it safely and ethically, but also productively to get the output that you’re looking for. What are some of the biggest challenges, uh, you two have seen since starting learn to ai and where, where does your organization struggle or need the most like attention?

What I have seen so far is, first thing is people not opting for help when they really need help. So it’s, it becomes at points critical. Like we have to explain people like, Hey, you know what? Upscaling is important for you to know it’s important. And there is a fear of people thinking, Hey, ai. Or this is gonna replace my jobs and that, but the idea is it’s not gonna replace your job.

Maybe someone who knows how to do all these things, how to use those tools might replace your job. That’s very much possible, and that’s such a good point. You know, the, the, this idea that AI will replace our jobs or like we’ve, we’ve had these things before, right? Exactly. [00:23:00] New computer stuff from new tools or new technology.

Oh, we don’t want that. It’s gonna replace our jobs. And then it becomes just a part we’ve had to pivot on what our jobs are look like or what we think about as work. This entire time. So why is AI anything different than the last, you know? Right. A few times we did that. Um, but that’s very true. I mean, if you are a carpenter, right, and you go to work and you don’t have a saw, uh, but there’s a guy that has a saw, they they’re probably gonna get the job.

Exactly right. Exactly. Yeah. It’s as simple as that. I mean, anything, if you’re not brushing yourself up for making sure you are competitive in the market, that’s what it helps, because it’s obvious, right? If you are doing the same thing, which takes four hours. Someone is using something which you can also use and do it in two hours, that also works.

Yeah. And I was telling Aryan this morning, like what I’m seeing, the trend is like it is still not there because people are, many people are there who are not yet familiar with gen ai. Yeah. Are not really aware about prompting, but then people, there are people who are already moving to a gentech world and by the time these people will [00:24:00] catch up about what prompting and everything is, there will be companies and people who are already.

Yep, ahead. The idea, what we want to do is, hey, right now is the time. Educate yourself and we are there to help. You know, we are there to support because in future it’s gonna happen. Like, you know, people, everyone will have AI bots talking, making calls, and, uh, oh wait. On the other hand, AI bots responding.

So two AI bots talking, and maybe down the road five years, uh, we might have humans in demand who can talk. So it’s always the circle, which is gonna happen. How you can stay ahead in the game. That’s the most important thing. Yeah, definitely. You’ve been talking about, and I wanna dive into, you said you use AI tools for almost everything, so I wanna kind of dive into that.

But before we go there, um, you, you’ve mentioned a lot, a few things like, you know, LLMs, gen, AI versus ai. Can you like, explain to our audience what the difference between those, those different types of AI are? Absolutely. I mean, the main ones, uh, which, you know, kind of machine learning is being called generative ai, right?

It’s more of, uh, reactive. [00:25:00] So basically you ask something, you get a response, but at the end, this responses are. Based upon the data being fed. So these companies have spent billions, you know, uh, feeding documents, movies, series and everything, but it’s still dependent on all the data and they’re still learning.

All of us are the users. Now, technically we are the better testers training the models, which is fine as far as we are getting our work done, but it’s still reactive. So with artificial intelligence, of course, the risk and other sites are there. But let’s look at the positives of. Within the guardrails, whatever things we can do.

Yep. And being reactive, how much it can solve. But if you are, let’s say, a PhD holder, and if I’m asking you like, Hey, which are the best restaurants of San Antonio? You’ll only answer with that. But if I can utilize your knowledge Absolutely. To ask you something, which only you can answer. Now I don’t have to find a Zac who is a PhD holder.

No, you just, it [00:26:00] has the data. Ask the right questions. Ask in the right manner. And that’s why prompt engineering is so important and, and probably like a core focus of your programs. Yep. Because that’s also gonna be different depending on what model you’re using. Right. The parameters that we’re used to train that model.

’cause then that generative ai, like you’re saying, it responds, but it can only respond with the data that it has that it knows. We’re in those parameters. So if you kind of understand, you don’t even necessarily need to understand how it was trained or where it was trained, but how you can craft the ideal response exactly.

To get you the furthest, uh, through that. And by the time we go to the age world, just wanted to add up what we also are showing at the end, let’s say with this cohort where we know that the crowd is already with technical, they understand about Python and everything. We are helping them to build agents so then they can build their own agent systems.

The idea is instead of being reactive, you can make something which is proactive. So instead of it coming back to you saying, oh, Zac, here’s your email, no. Already figured out what needs to be done and you can build an agent. So we have been helping companies for building an agent for, let’s say, creating content.

So [00:27:00] it creates the content, it posts the content on a regular basis on TikTok or on LinkedIn or Instagram. Similarly for biz dev, it can scrape data from all those tools, let’s say whatever zoomin info polo that you might be using from there, create the emails, do things. There are ways you don’t need to be a developer.

That’s what I tell people. Like, Hey, absolutely you need to open up though. You need to come to our cohorts and say, Hey, we want to do it. Your second question, uh, right now we are focusing on doing with businesses like B2B, but we can, we are happy to open up a cohort where, let’s say a bunch of people shows up.

Let’s say at least a minimum, seven to eight people. And then if they all say, Hey, we want to focus from the list of cohorts that you have, we all want to do this. We’re definitely open to start a cohort for them too. Yeah, see there’s probably a lot of like, just on that note, and we can kind of circle back on that another time here, but there’s probably a lot of potential for opportunities or collaborations between our company and learn to AI to serve the nonprofit world through [00:28:00] Absolutely.

Like a cohort focused on. AI for Good or something like that, right? There could be a lot of cool collaborations in there. So, Aryan, you use ai, you said in just about everything, right? Right. So like, like what are some examples? Where are your most productive uses of ai, even for 1 million cups today? Um, a lot of the things were made by ai, I mean the content obviously we drafted, but stuff like the side slide templates, um, the VO three videos, something simple as just saying, you know, the videos or like any images, they were all AI generated.

What it really does is, like earlier mentioned, it just, um, saves time. Something that would take longer, right, with thinking and, uh, you know, planning the colors and making it just look proper and professional would be done quickly by ai. And, and that’s such a cool point because like all, all of the tedious, cropped crap that goes around your job or the things that you do, right?

You don’t necessarily need to do that. You can let a tool, an AI tool, do it, like your colors on your slides, your layout, that sort of thing, and you focus on [00:29:00] the part that actually matters, the part that’s actually moving you forward, which is the actual presentation, the content, right? He’s the one who’s managing, uh, the LinkedIn for lead to ai, okay?

And all the posts where you are seeing and hearing. The audio of a real person talking and everything, it’s all edge. That’s what he has been using to make it sound like a real podcast or a real voiceover. Yep. What’s the difference between. You’ve, you’ve talked a lot about age agentic ai. Right? A lot of people confuse AI agents versus AI’s assistance.

Right. And so can you kind of walk through like the difference of that and why your program focuses on more the age agentic AI versus the assistant ai? Yeah. Yeah. The idea is that, uh, we, again, depending on if someone for our app dev and other cohorts which are technical, that’s where we focus this upon Uhhuh.

Initially, let’s say for ui UX one or the prompt engineering one, we try to keep it basic. That’s when the Ai, ai assistant Oh, so that’s, that’s part of that very much. That customization for the cohort? Yeah. Yeah. Okay. But when, uh, we bring in rag and lang chain and, you know, all the other elements, that’s when, if it’s super technical for the building agent [00:30:00] route, or taking the agent route about opening up in Python and then bringing or merging the APIs from, let’s say open AI or something else and integrating those.

So both, but depending on, we don’t want to bombard someone who is not, you know, in there. That’s the very reason why people are afraid. ’cause they feel this is overly complex. Yep. But no, I guess there are steps and people will have their liking and choice. They might like, Hey, you know what, I don’t want to do it now.

Even if many of the websites are being built drag and drop, how many of them you are seeing people are, there are people who still paying. For a developer to do it right, which is insane to me. Hmm. So there are different kind of people, different kind of people might need different kind of assistance and that’s okay.

So that’s where we are open to like, Hey, it doesn’t matter. You don’t need to be shy, you know, come up. It’s okay. Someone might pick it up easily by reading a document, but no, you need, let’s say two session, three sessions to understand. That’s fine, but you get it now. And then, so I guess I do wanna expand a little bit.

You had mentioned a [00:31:00] little bit earlier in what you just said made me think of this on, um, an executive focused cohort, uh, where you’re, I assume are teaching executives how to make decisions on evaluations and set those guardrails for AI usage in their companies, that sort of thing. Um, what’s interesting is, so, you know, I grew up in tech.

That’s what I did. Uh, we build AI like training, deployment, specialization, all of that. I know tools like Rept and was it lovable? And like all these other tools can produce amazing stuff for us really quickly, but I also don’t want to deal with it. Right? Yeah. So for example, I know I could put together a website pretty, pretty okay.

Pretty quickly and get that deployed to our infrastructure done. But we just hired a marketing agency to rebuild our website, right? And so like. What does it look like when you’re talking to these executives? What are the areas where they’re kind of focused on and, and where is the, the real work happening?

’cause it’s likely not around AI itself in those sessions, right? Absolutely. So we have been working with some of the large institutions and I say we, uh, with [00:32:00] my experience with luxury and everything, with solutioning. We have been implementing this from last three, four years already. Yeah. So what one of the example to give you one of the largest banks in the San Antonio, you probably know already which one I’m talking about.

Mm-hmm. So that’s where, um, we kind of implemented a solution. So what happens is with ServiceNow Snowflake areas, which are these BPM tools. Yep. As I said, with when you’re small, it’s easy to pivot and do all these things, but when you’re large. In order for you to change something or implement something, there is a big risk or big fear from the management.

Like, oh, you know what, let’s not do it. But that’s when you have to explain them, Hey, about what this brings in. So for example, there’s one solution called Solve, which we Okay. Brought in, which is a tool agnostic tool, uh, AI basically. So what happens is it can plug into your different, different enterprise level systems and then.

From a UML diagram, let’s say it can write you the use, use, uh, use cases or user stories, which a BA or two needs to be [00:33:00] done for, let’s say two weeks, right? It’s gonna be like in four hours. Now a BA needs to send 20 hours to doing it, but then the idea is how to do it. So there is a way of doing it in development, staging, production, how you roll it out step by step.

Also, it can help you cut down the budgets, right? ’cause at the end, for big companies, it’s all about budgeting, about, hey, how much approval you have got. Now, if you have half a million to spend in this quarter or in this year, if you’re able to do this in like a hundred thousand, you have 14,000 left. Yep.

Where you can invest it, you know? So the idea is you can really do a lot of things, especially when the tools, when they’re not talking with each other. With enterprises, what I have seen is all these enterprise tools have their own ais as well. Yep. But it’s two ways. That’s the worst part that everything goes out.

So that’s why no one wants to use it. Everyone wants to guardrail that, and that’s when you can build a wrapper solution and build a solution on top of it to make it work. So the idea. When, uh, [00:34:00] with them, with the leaders, this is what we kind of explain, teach them, show them the demos, how to do it. But that sessions, those sessions are different, right?

Compared to what we teach to startups and small to medium businesses. And so how does a company bring learn to AI in to help, you know, teach AI processes, help understand their processes? How do they do that? And what does it cost? Like how, how do you guys, do you charge for the curriculum? Do you charge for the time?

What does that look like? So, pretty good question, Zac. And that’s where I guess people need to be aware about it. So any of the companies, even their startups or small to medium business or large enterprises. They can bring in if they’re aware or they want to bring in, but they’re afraid in terms of bringing in AI or how to do it.

Yep. So what we usually do is either they can choose one of our cohorts, which we have like including the 15 and the plus, the ones that we have, 20. They have like from 20 to choose from considering their areas if they don’t want to spill the beans, you know about which ones our team can [00:35:00] utilize for making their work more productive.

That’s one. Second thing could be about if. Like what we are doing with the existing cohorts. That’s like, okay, we can be open, we can ask you, or Okay, you want help? You came to me and we are talking now tell me which are the tool system that you are using and we considering we are the experts, we can guide you in terms of, okay, what do it in this manner.

Maybe you are trying to buy HubSpot or this spot or that spot, but that tool comes up with their own complexity and you know Yep, absolutely. You, you don’t even know how to use that. So the idea is how. Really, whatever you have, try to build upon around it. In terms of costing, we are nonprofit, so honestly we try to do it at the best possible manner.

We wanna keep it at no cost to people. Mm-hmm. But at the end, with corporations and companies and government institutions, I guess we can do it even on cost to cost basis. Just to cover up the cost of our. Trainers and all the materials that we have been using. Well, yeah. And, and that’s actually a good model, like to fund your, [00:36:00] like individual cohorts or your, your public cohorts, right?

Because companies have dollars that are often budgeted for, uh, professional development or upskilling or wherever, wherever you wanna put that. Right? And so that could be a good model to charge a little bit over what. Is cost to produce the content and the cohorts Right. For the, the organization and use that to fund all of your other initiatives and stuff, so, right.

That’s pretty cool. The, the mo main mission we have is to make San Antonio the most AI iterate city by 2030. Yeah. By 2030. We want to be a part of that. You know, not that you, you got four and a half years, years. I know. So we don’t wanna say, Hey, you know what? We talked about this, maybe with this evolution our name should be there somewhere.

Yeah. Zac and Mihir and Ian were there. Absolutely, definitely. Okay, cool. And then, so in terms of upcoming things, what’s happening, like what’s the next thing for Learn two ai? Do you have any upcoming events or fundraisers or anything that, uh, you wanna share? So one of the big events that we are having is basically kind of a [00:37:00] demo day for our existing cohort, because that’s where we have given like.

The real projects for them to build and showcase. So that’s happening next week. But other than that, we are lining up. There are a few things behind the curtain at the moment because they’re not locked yet. Right. But we’re trying to work out with some of the universities and also some of the good private institutions to start doing some of the cohorts as well.

So those will be live soon. Hopefully. The idea is to make it rolling. Mm-hmm. In a way so that at least we can have four cohorts ongoing in a month. Okay. Different, different places, different cohorts, different kind of around Texas, around just San Antonio, like around to begin with, around Texas. Okay, nice.

I mean, that’s still a really big area, right? Um, okay. Awesome. And then so how can the community kind of get involved? What do you need from the community? Do you need volunteers? Do you need people to recommend learn to ai? Like what do you need from the community? So two things. One is definitely volunteers to help and support to guide.

Uh, second [00:38:00] thing is we definitely want some trainers too. ’cause we are trying to be, you know, bring in and making it by ourselves. But definitely we will be open to hearing and getting more people who want to really make an impact there. And join us as a either trainer for our different cohorts, which we have planned and designed so that we can do this and we can help multiple people at the same time.

And also people to show up. That’s the whole thing. Like we are doing this at a knock knock house to you guys. Come and make an impact in your business and don’t be hesitant. That’s where people usually have seen is, you know what, it’s new. And how would I look if I now go to Zac and say, oh, Zac, how does this thing work?

It’s okay. You can be open. That’s fine. And there are companies who are reaching out to me and the CEO is saying, Hey, you know what? Uh, can I get this training first and then I can do this for my peers? And I get it, but I’m glad that at least he showed up to me. You know? Yeah, that’s okay. Whatever way it works.

But, uh, yeah, the [00:39:00] idea is to come in together. So where can you learn more about learn to ai, how to get involved, how to make contributions. So right now, uh, we have our LinkedIn page app since we started like four months ago. Is that learn to ai.org? Yes, that’s right. But then the idea is the website is still under wraps.

Mm-hmm. It’s Bill we are building up because we also have in planning to do the feature of podcasting and, you know, donation and other things too. Well then I’ve got a question for you, Mihir. Yes. Okay. Your website is still under development. You know how to use these tools to build it. Why didn’t you just vibe code this thing in a weekend?

So we did, we did. In fact, we had the first version live and uh, we had some changes and we wanted to bring in, so there was some change around the board. So we are trying to also form a board around it. Yep. And the idea is that when we go live, we make it. But now since it’s taking some time, what we are thinking is the same route of saying, Hey, coming soon at the end.

Yep. Put a banner, you know? Yep. Something around that. Okay, awesome. [00:40:00] And yeah, that’s pretty cool. So like making AI literacy is becoming more and more important and it’s really cool to see organizations like yours. Are making it a priority and helping people understand why it should be a priority for them.

So, um, yeah. Awesome. Thank you so much for joining me on the show today, guys. This was an amazing conversation. Um, that’s another episode of Beyond Giving the best nonprofit podcast on the Boost Network sponsored by Nonprofits hq. You can learn more about Learn to Ai, Mihir, and Aryan on that lawn. Learn to ai.org.

I have a question, Zac, for you. What’s up? What are you willing to contribute for Learn to ai? What do you need? So like. One of the things that, that we always do, it’s a hard requirement for, uh, anybody that’s involved in nonprofits hq, which is our company, is volunteerism, volunteering for different organizations, whether they’re customers of ours or not.

Um, I sit on various boards, very well connected in the tech community, like, what do you need? That’s what I’m willing to do. Thank you so much. So we’ll definitely be [00:41:00] talking about it. Absolutely, dude. Absolutely. But thanks for having us, Zac. Really appreciate it.