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Interviews from a multicultural perspective that question the way we understand America
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So I'll stop now
Shahid, thank you so much for being here with us today in Back in America. Tell me, is our education ready for ai?
It it is in certain areas, Stan, where people are understanding that this is not a tool for us to use as part of education, but it is a educator and it is a. Almost a co student. So is education ready for ai if they use it as part of their education itself, like the teachers have to be using AI to teach better at a hyper personalized level for languages, algorithms, et cetera.
That's one area. Then there's the other area of, is the school ready? To treat and teach students to use AI as a colleague, as a co-equal coder with them. And there the answer is no. So we don't quite know how to teach. People to use AI as a companion. And so what you'll see is people using AI for minimal kinds of stuff, but in the real world if we are hiring in a business world today, we don't hire one guy who knows 50 things.
We hire 50 people who know 500 things, and then we have to coordinate their work. And so we use AI to do that coordination. But education currently, of course, is woefully behind. Because it doesn't know how to do that any better than the business world does.
All right, and we're going to come back to that. So let me try to introduce you
so when I did some research, I learned that you were an award-winning fractional CTO and you are going to tell us what it is. And A-C-I-S-O, you've got hands-on approach to technology.
You've got over 35 years of experience of engineering. You've built secure compliance system for complex regulatory industries from medical device to digital health for the federal government among others. You blend deep technical skills with real grasp on how the market and the regulation shape innovation.
Yeah. Number one, as a fractional ct, my, my background is as a computer scientist, so I was trained to write code but as a fractional CTO, what I've spent the last couple of decades on is coming in, almost like parachuting as a special ops guy to come in and assist people who may already have a CTO as well, but they need a coach for that CTO or they might need a CTO.
'cause the CT OCTO is in transition. So the chief technology officer in product oriented companies is the, literally the chief technical person there who makes decisions, et cetera. Then I've also done work as a chief information security officer or A-C-I-S-O. That, of course, sounds exactly like what it is, which is that software needs to be secured, infrastructure needs to be secured.
Now, I like to say that I'm hands-on because a lot of CTOs that are at my skill level or experience level, I'm at 35 plus years now since I got my degree and I've been working on lots of different projects. A lot of those CTOs no longer code. And so I've, this is a pet. A peeve of mine is when a CTO.
Who is supposed to be a coder does not code. Today it's not right. Every, the tools are coming out fast and furiously, and if we're going to instruct. Younger people, whether it's from an educational perspective or a training perspective at work, you have to know something about what you're training them on in order to do that training. And so that's why I like to say that I'm hands-on.
Tell me what pulled you toward this kind of high stake engineering, working for highly regulated companies? Is there an attraction for you to these kind of industries, or
Yeah the principle attraction for guys like me is impact, right? We'd like to say I, I've worked on medical devices that I know save lives. For me, if at the end of a long day, like I'm an entrepreneur, I work long, long hours and long days. At the end of the day, I don't wanna say I did a fantastic job on, a new cartoon creation app.
Those are not bad. I use them for my grandchildren, but that's not for me. For me, I like to say I, when I finished the job, it helped somebody save a life, get a job done et cetera. So it's mostly about impact. And being, doing so in a heavily regulated industry allows me to use my special skillset, which is I'm one of those few engineers that can speak to humans.
As well as machines. And that's not common. And so in order to do all of this really highly technical work in regulated environments, you have to understand the law. So I'm part lawyer. I have to read the law, understand the regulations, know what compliance means, et cetera. And then I have to be an engineer.
But there are a lot of people that can do one or not the other and not the other vice versa. I the best of those amongst us now at this level of skills that we like to. Say that we have to understand a bigger world, and we have to understand that the code that we generate from AI has to live in the real world where you can accidentally spend more money, you can accidentally kill somebody, you can act, you can put this code into a a chip or a microchip.
That might be in an airplane that could fall out of the sky. It's really important. And so I just like to be working on important, impactful things. That's what, but that's why I would get up in the morning 'cause I'm I'm close to retirement age, but I don't see myself retiring anytime soon.
So you spoke about interpreting the code that comes from a machine and keeping your humanity. me back to a time where you were building something and you faced a bug. The system crashed and how it really impacted how you see human judgment versus mass machine logics.
Yeah, that's such a great question because it takes me back. Back in the early two thousands, late nineties I worked on a class three very large medical device in a blood bank. Blood banks are obviously you get one person gives blood. Say I could be the one donating blood. You could be the one receiving it 'cause you got into a car accident and you're at the hospital and you need the blood.
So it's a super. Critical thing that blood be taken properly, it'd be tracked properly, it'd be tested properly, et cetera. So I worked on, this a blood banking software. And there were multiple times over years where we saw bugs, but we didn't understand what would happen if we didn't fix it.
A lot of times you're working in a business app you got a bug, and the wrong color shows up on the screen. If nobody tells the developer that, no. When that bug occurs. Somebody's not gonna get their blood or they might get the wrong blood type, right? You're supposed to get O negative, but you got a po a B positive, that's death, right?
That's not a, it's not a small thing that happens there. So having worked in these environments where I understand. The bug when it could impact a life, that's where your humanity comes in, right? That's where you, that's where you spend the extra 40 hours that weekend trying to get through and making sure that this code can get out the next Monday.
And that's really where, because I've lived through that like I've worked on probably a dozen or so medical devices and I know the code that I wrote. Had bugs that probably accidentally harmed people and that stays with you. Like I, I can actually remember two or three cases. I can't talk about them publicly where Yes it did.
And we know that people were harmed. Now nobody would arrest me or sue me 'cause it was a team, right? Medical devices do harm all the time, just like planes do fall out of the sky when things go wrong. But that's when you, your humanity comes in, is you see that the every decision that you make. If AI is gonna generate the code for you, and a human doesn't watch the AI doesn't care whether it's being used to save a child's life or draw a cartoon figure.
It just, it's just generating code. But you and I know that one requires a high amount of reliability, a high amount of safety checks, et cetera, versus the other. That's where we have to come in and recognize that it doesn't matter how much AI comes in, if the target of the software that we are building is other human beings, you need us in the middle to verify that AI doesn't harm the other human being.
So you talk about AI and when did you realize that AI was not just another tool, but something that would change? The way we learn, the way we work, the way we code. When was that?
Yeah. Some of us worked with AI very early on. So as we know in late 2022 is when Chachi PDT was released. But that version of Chachi PT. Was available in open communities a couple of years, a few years earlier. When we used to use that before chat, GPT came out, you had to wire a bunch of stuff.
Like you had to write a lot of code, you had to write a lot of prompts and put those in and then wire it all up. And so that never gave us the impact that this could have. But when Chachi PT came out, that exact software. With a direct interface, like a human to human, like you and I are talking right now.
The very first time that I realized it is it was about probably the second or third month when chat GPT was out.
I'd already been using it for a while, like I signed up for it, literally the weekend it came out. Now so I'd been using it for code and other things for a while, so I knew what it could do. But the one really cool thing that I ended up doing is so I have family members that have chronic conditions like diabetes and cancer et cetera.
So when I started asking it. By giving a little bit of context for family members who needed medical advice. Even with knowing the same thing, that's when the light bulb went off, is that I'm getting real information that a real doctor would give me, that I can make actionable.
That's how I know that it's now a colleague. That's not a tool that I use. Just like I have friends who are doctors. When I have before ache pt I have oncologist friends, I have cardiologist, friends. Whenever I had a problem, I called my cardiology colleague, my oncology colleague, and said, and they would help out. They would brainstorm. They would discuss and say, did you try this paper? Did you read that paper? In the essence now, the 90% that I do now back, the first time I realized this is do it all there.
Now take that output. And then bring in the human colleague after that and things get even better because the humans can now take obvious stuff and make it unobvious. Or the humans can say, oh, wow, I never thought about that. You know what? I just saw a patient two days ago where we did do this. We didn't even think about it.
Let me go back and do it with that patient as well. Or extending that. So it became crystal clear that the AI is your colleague, it's your friend, it's a worker, a
How did you feel at the time when you when that light bulb came on, how did it make you feel?
At first I was like, no way. I said this can't be right. It has to be fluke. So sometimes when you see a generative ai, because I know the technology about generative AI enough to be able to say I know it's gonna generate English 'cause that's what it's been trained on, et cetera, et cetera.
But when it put together the words in the order that it did. That is not just what it was trained to do, because there's more of reinforcement learning, more training that happens on top of that, which means that there's a bank of humans at OpenAI, at Claude, et cetera, that we know tens of thousands that are reading and rewriting and updating these prompts.
And but what it made me feel is, does this obviate me? Meaning, am I no longer necessary, like the doctor is no longer necessary?
Then of course in a few days you find out no, of course not. 'cause it's incomplete, it doesn't know how to prompt itself. It doesn't know how to execute on the things. It doesn't know how to be empathetic and talk to one patient versus the other if you don't set the prompts properly. So that's when I knew, oh, I'm not going anywhere.
There's plenty of opportunity.
I want to come back to education. So we see today that a lot of companies are letting AI do the grunt work of, debugging boilerplate, all that kind of stuff. What does it mean for young freshly out of school student looking for an entry job?
Yeah, it's gonna be tougher and tougher for those entry level positions, but not in the obvious way. Like the obvious way is that companies are not looking for the junior guy. They want the mid or senior who can help operate ai. That's the obvious part. The unobvious part is that the juniors don't know enough to be able to, in their mind, the ones who are hiring this way, the juniors don't know enough in order to drive the AI faster in their environment.
Said another way. The juniors and if you look at it from the high level, if you're really good at what you do, the AI makes you a hundred times better. If you're bad at what you do, like of course all younger people are gonna be bad at coding 'cause they don't have enough expertise. And you gotta build that expertise.
But if you're bad at coding, you're a hundred times worse. It doesn't mean if you're bad at coding, you get good because you have ai. The first thing you have to realize as a young person is. You don't know shit, right? You don't know what you don't know, what you don't know. You don't know how little you do know.
And so you pretend that you do know and you put that prompt in, and then you get stuff out, right? Code is going to come out the other end. You just don't know whether it's good or bad. That's why. So if I'm a leader who has the opportunity to hire five seniors and five mid-levels versus five, entry level just for my own sanity so that I don't have to check the work of those younger people to cr who are grown to create slop. I need to hire the mid or upper end. That is, that, that's the normal case. Even without ai, that was the case. If I had a choice, I would go get a senior. I often did not have a choice, so I needed 10 people.
I knew I could only get two seniors. I could get three mid-levels and five juniors. So like I knew I needed 10 people. So this is what you, and if you're being educated today and you're coming outta college, you need to recognize, in the old days, I might have needed ten five juniors. I had to take you because I had no other choice.
Now if I have two seniors and one mid, I may not need the rest of them. Mentally speaking, I may decide that and say, I don't need the rest of them. It's not quite true. But that's what I'm going to think. And so what do I do? I just let my seniors continue and my mid-levels continue. Now what I don't realize is if I don't build my juniors now, how are they gonna become that mid, when my senior leaves, the mids gonna go up to become a senior, but I've got this whole era area which is gonna be completely empty.
If I'm an idiot, as a senior executive, I will stop hiring junior people only if I'm an idiot. If I'm not an idiot. I have to get those juniors to be able to shadow the seniors in the midst, just like in the old days. And so this is what the education establishment, compsci education.
IT education, they have to be teaching the juniors and the fresh guys that are coming outta college. To be so useful with ai that would be silly not to use you in combination with the seniors and the mids. And senior executives are and senior people like me are making mistake right now.
We're gonna pay for it in two years, or five years, or 10 years, where we're not building that community of juniors to be able to take care of the to become a mid, which then becomes a senior.
Is it what you. You call the adapter, someone who guide ai?
So you could think of them as context engineers. Really the, you don't really need to guide the AI per se. In general, what you're saying is correct, but the guiding of the AI really is telling it the background of what it needs to know so that it can generate what you're asking it to generate.
So if you go to chat GPT in a fresh account today. And you say, write me a function that can sort a linked list and that's all you say. You don't say anything else. You just give that, it will most likely pick Python ' cause it's a popular language and it will do so in a way that is fairly advanced. 'cause it'll use traditional link list algorithms and you'll get a function.
Now you were supposed to tell it that this is to be an Assembler or Pascal or C or ADA or whatever. You didn't give it that background, which is what was lacking, right? You didn't give it the context. Now, in the modern era, I would rather get a junior guy who understands context engineering, and then I could give him or her the extended language specific things that I need rather than a mid-level who has the skills but cannot prompt an ai.
As an example. If you are a designer, HTML, CSS, et cetera, you have, you're fresh outta college. You don't know all the advanced ways of doing that. But boy, do you know how to use lovable? Lovable is a it's a popular design tool as we all know. So if lovable and you don't have super high level skills in HTML or CS.
You're still more valuable as a junior guy who knows lovable that can take my words or my prompts, put it into the tool and get something out that I can then give down the stream to someone else rather than a senior guy who's been writing HTML and Cs s his or her life for years, but doesn't even know lovable exists.
Now you have to ask yourself, which one do you want? Do you want the junior guy who knows Lovable exists? Not only that, but they can drive lovable better than everybody else. Or do you want the senior guy who doesn't know lovable exists? I'm taking the junior one any day of the weekend, twice on Sunday for sure.
And that brings me to a natural question about the skills, right? So being curious, being innovative is what we talked about, using those new tools and. But what are the human skills? You talk about empathy earlier on and I believe that properly trained AI can be extremely empathetic. So what are the skills you are looking for as a CTO when you look at those kids fresh on the market?
Three main things. Thing one is when you deal with ai, how much do you use AI to help you with ai? Now, this sounds very weird and very meta, but the best prompters in the world like myself. When I work with ai, the very first questions I ask when I teach a context or need a task done is, what do you need from me in order to do your job?
Give me the prompts that you would have me give to you. So you have to literally sit there for minutes or hours and just coordinating with the AI to figure out. Do you understand me? And do I understand you? Because when you give me the prompt, I understand it more. So if you're, if you've got, like I have 35 years of programming experience, you could give me almost any problem.
And with a little bit of books, obviously we're all old and we're gonna have to go back to reference books and things like that. I would be able to write your function, write your code, et cetera. But what I wouldn't be able to do is if I hadn't already done, six, seven years of this work already, I wouldn't know how to organize my thoughts and provide the context to an ai.
So that's thing one. If you can understand and tell your hiring manager or the guy interviewing you and say, look, I don't know everything. I know what Marissa Meyer said at at Google a long time ago. It's not what you know, it's what you can find out now. It is not what you know, not what you can find out, but what you can prompt through context.
So if you extend that and you say thing one is, can you talk to the computer better than the guy, than the next guy that they're trying to hire? If the answer is yes, prove it. Write the articles, show your prompts explain how you do things. Go on to GitHub. Put project after project. Get everything that you know that you're doing with AI public, because that's how you're gonna be able to prove to me that you know what you're doing.
So that's thing one. Thing two then is do you have the basic skills? If I said give me a circular link list. Versus a unidirectional link list. Give me a a a directed graph versus an undirected graph. If you're going to, if you're gonna say, oh, I know how to tell AI what to do, and you don't know the difference between a directed graph and an undirected graph it doesn't really matter how well you communicate in English 'cause you don't have that skillset.
Kids coming out today. They not only have to have the basics, but they've got to be stronger in those basics than ever because the AI is going to generate code in the way that you ask it to. So if you tell it to create type safe code, it creates type safe code. If you say, give me unsafe code, it gives you unsafe code, so you have to know what to ask for, and so the first problem is.
Can you communicate what you're communicating well to a machine, which is not the same as communicating to humans. It is different and we know that, but two, if you say you know how to communicate to the machine, but you don't have the basic skills in computer science and understanding the algorithms versus you know when to use one versus another.
If you can't do that, you're not very useful. The first skill is not very useful in the second, but the third. If you couldn't even do number two, but you could do number three. I'll let it slide, which is, look, I'm really good at what I do. I'm not great at the algorithms and things like that, but I understand how to talk to humans to get requirements input, understand what are their expectations, and I will use that to coordinate and work with a mid-level engineer to fill in with AI so that the two of us, a junior plus mid.
Where the mid knows more about the computer science part, but the junior knows how to talk to other humans, if you can fill that gap, then all three of those things, if you can gimme two of those three, starting with the first one is a must, right? But the other two I'm willing to negotiate on depending on how good you are.
With the tooling. Now the world is hard for younger people and it's always hard for young people. It's like when I was young, it wasn't like the world was easy, but at least I was only competing with other human beings, right? Today, kids are not only just competing with other human beings, they're competing with the AI colleagues and the mids and seniors who are 5, 10, 15, 25 times more productive than they were just five years ago.
I love you said you had grandkids. As a parent of student, what would be your fears when it comes to AI and your hope?
Yeah. My biggest fears are that people our age and those that are in the job market today, we don't understand the benefits of AI and how operating it as an additional colleague is more valuable than trying to replace the humans that we have. That's my biggest fear. And of course it's understandable that, this stuff is two or three years old.
It's not like we've lived with it for decades. So the fear is when you think it can do too much, it is going to harm your environment. Like you won't build the human skills that are necessary to operate complex machinery, complex equipment, et cetera. But. If you say that, okay, I'm treating it as a colleague that every new hire that I have deserves a proper twin of their ai, well-trained, designed to work with the person that comes in, that's okay.
Now my hope is that, so I have a couple of granddaughters. One is six other is two, turning three this in November. Now, the biggest hope that I have is it their teachers can do what I do when they come over, I often play with them with ai. So instead of playing a traditional Donkey Kong game or just on their Nintendo switch or whatever, they do that, of course they watch TV and they play with that.
But when they spend time with me, we are on ai. So each session might be, Hey let's invent a game together and let's play it together with AI or, and when they're coloring. They're not coloring Disney characters. They're coloring pictures. Like I, I will I'll load up pictures, create coloring books, stories, et cetera, with their parents, with their grandparents, with their siblings, with their cousins.
So the stuff that they do is still hyper creative, but it's personalized to them. So the 2-year-old stories that the AI works with me. Are great for a 2-year-old. The 6-year-old, the games that we play, it escalates the game because it knows the request and response. Now, I am a parent, I'm a grandparent.
I love my grandkids. Of course I'm gonna spend all that time with them but if you see this, the power of this. So what I'm really excited about is could teachers recognize. Within the next, months, years, however long it takes that each student in their class can have a personalized teacher that can operate at their speed, at their level, at whatever pace that they want to go to.
And that the teacher in the classroom, whether it's in a, for a 6-year-old or an 18-year-old, doesn't really matter that the teacher in the classroom is a proctor or an organizer or an orchestrator. Of all the other teachers that every single student has in their environment. Now I can, I'm just imagining the level of intelligence that the students could have if each one of them had a bank of personalized teachers teaching them math at, science biology, et cetera, at their level, at the pace that they wanna go to, instead of being bored out of their mind and going.
Into different places in their head because they're just bored, because they're really good at biology, but their biology teacher's too behind. They're really good at math, but they're too behind, right? You see this, that, that part. So that's got me really excited.
So we are getting almost at the end of this interview, and we've got parents, we've got teacher listening to us today. If you have one thing you would like to leave parents and teacher with, what would it be?
Yeah, just think about the AI as a personal. Third parent, for example. So parents good parents will spend time with their children, right? And they'll spend time doing homework, et cetera, et cetera. When you are busy as a parent, often you're not able to do the things that the kid needs attention on.
But the AI knows where it needs attention, right? Because you can actually give it the prompts and say my kid got this homework. I don't have time to do it with them. Could you help with it? It'll do it for IT teachers, the one thing you can start doing is start to see which students could be the ones that are your voice to ai.
And like in my case, when I spend time with my 6-year-old. She, as soon as she saw me chatting with the ai, she started giving it prompts. She said, she's, it. In her mind, it didn't even occur to her that this was, an amazing piece of technology that she didn't have when she was born. It's like she started talking to it as if it was always with her in her entire life, and she's oh, ask it to do this.
Oh, this is a better idea. Let's do this. This is a 6-year-old. Now imagine what an 8-year-old or a 14 or an 18-year-old could do. If we trusted them. And so teachers today are scared of ai just like everybody else is in many different circumstances. But what I would recommend for teachers and parents to do is adopt it.
But you sit there with ai, do not leave your, do not leave your kids with their AI on their own. Like in our case, when our kids were young. We only had computers in a central area where we could see them. So do that. Let them use ai, but be there with them. But don't be afraid of it.
And don't say there are universities out there that are preventing kids from using AI to turn in their homework. It's the dumbest thing in the world. How are you going to be able to teach them that it's a companion or a colleague when you say you can't talk to this, massively useful technology, so don't be afraid of it.
Work with your kids in class and outside whenever you can in an interactive way, so you can see are I building their prompting skills or am I accidentally making them dumber? Because they're not gonna look at anything on their own. They're not improving their prompting skills. They're not saying, I learned this in my environment.
Let me put it in Instead, they're just waiting for information to come out. That is a horrible situation that we have to try to prevent.
Thank you so much. So this podcast is called Back in America, and in the podcast we looked at what makes America, we look at the culture or. The identities and the values. And if you are familiar with the podcast, I always end with one question, which is, what is America to you?
To me, America is so I've been here since I was four years old. So I started elementary school here. The number one thing America is to me is opportunity. Opportunity. Opportunity, in this era so having seen lots of other countries, 'cause I've been flying around for my entire life what we see is that even today, lots of other countries have caught up in many other areas, but they haven't exactly caught up with.
The amount, just the sheer amount of opportunity available to do anything that you want to do. And now with ai it's easier in one way, 'cause you could do whatever you wanted to do, but it's the tyranny of choice. You can literally now do whatever you want to do. And there's a, a, an old scientific American paper.
If you don't know what I'm talking about. But in 2004 there's a paper that came out called The Tyranny of Choice, how Having choice like we do in America. Is wonderful at the surface level, but when you have a lot of choice, your life is actually much harder than when you don't have any choices at all.
So read that paper, understand it's about opportunity, and start selecting your 📍 opportunities wisely.
Thank you so much for your time today. It was a pleasure to speak with you.
Yeah I had fun. Thanks. We'll do it again. I. 📍