EdTech Startup Showcase

Eric Makelky: Welcome.

This is Erik McKelky, your host today from Creskenova Labs.

I have joining me Christine Braun.

She's got one of the coolest titles.

I'm very envious.

She is the chief creative officer at Creskenova.

How are you, Christine?

Christine: I'm doing well.

Thank you so much.

Thanks for having me

Eric Makelky: Yeah.

first and foremost, I want to hear a little bit about your background and how did you end up being the chief creative officer?

Christine: Certainly.

I had-- So I'm a furniture designer by training, a master's in furniture design, and when my children were little, I recognized that one of my sons was very creative and noticed also that the things that he was interested in were robotics and things like that.

I couldn't find any classes for him.

Started creating my own company to bridge a technology gap that I saw widening within the school systems.

Did that for quite a few years, then went to the Nueva School, and the Nueva School is in the Silicon Valley.

It's in well, it's in Hillsborough, the one I was at, and I worked at the innovation lab at the Nueva School.

From Nueva, I went to Harvard University, where I became the director of the Makerspace at the School of Engineering and Applied Sciences.

My role was to break down the silos of Harvard and to really welcome everybody into a community at the, at the Makerspace.

And then while I was at the Makerspace, I taught a class for Crescando Global because I know Sarah and Katie from Nueva.

And while I did that, I started talking to the founders, Barbara and Yen, and they had explained to me that they were hoping to create an in-person
space, so I accept the pos- the position, and as soon as I started, we started looking for buildings in and around London to create Crescando Labs.

Eric Makelky: All right.

And, and you're finishing up your first year of having the brick-and-mortar Crescenova Labs program open

Christine: Yeah, so we bought the building in 2024, came out of construction August 2025, offered our first workshops this past October, and now are full swing into courses, workshops, and camps.

Yes.

Eric Makelky: Right.

Well, you know, for listeners out there that aren't in the London area or LABS wouldn't be a viable option at the moment, there's still a lot of great things happening in the LABS program, and I'm hoping
we can start today talking a little bit about the framework that you use w- with all of your programs and how that can apply to families and students everywhere, even if they're not attending LABS courses.

Christine: Excellent.

So the Crescenova Labs framework was built up over my years of teaching as a owner of a company and at a school for gifted students, and then at Harvard University.

What I found overall was that first and foremost, we need to teach students how to ask beautiful questions.

And I believe that parents can utilize this information, especially when, you know, your kid gets in the car at the end of the day.

Instead of asking something like, "Did you have a good day?" Like, that's a closed-ended question.

End of conversation.

Kid's either gonna say yes or no, and the conversation's dead.

But if you look at like the schedule that your child has, you know about their math, you know about the subjects, the projects that they're making, right?

Ask a more open-ended question.

And by asking that open-ended question, you're really giving your child the opportunity to answer, to really dive into what happened that day.

And of course, once you open that, that nut, so to speak, you know, the, the flow is gonna happen.

They're gonna tell you everything that happened throughout their day.

And the most exciting project, even if you say, "What was the most exciting thing that you learned today?" That in and of itself could be really critical for a child.

I have three boys, and that was one of my questions to my, my boys, was, "What did you learn today that was really exciting?" And that's how you drive that curiosity

Eric Makelky: Yeah.

And that can take some time as a parent.

If you've been asking them, you know, "How was school?" Or, "Was school good?" And then all of a sudden you say, "Tell me the most exciting thing that you learned about in math," your kid's gonna look at you like, "What's wrong, Mom?"

Christine: Exactly.

Yeah.

Yeah, yeah, yeah.

Maybe lead up to that one.

Eric Makelky: it can take a little practice.

And that's also a big contrast from, at least in the traditional education setting, you know, our approach has been get kids to answer questions.

But really what you're talking about, the first step in the Crescenova Labs framework is get them to ask good questions.

Christine: Exactly.

when we offer a course at Crescanova Labs, right, it's a broad course.

So we're working-- I can give you an example of microorganisms.

And my whole first day of microorganisms, which is a two-hour studio class with students ages eight to 12 was to give them the
microscopes, give them the moss, which I'd been soaking for a week that I've collected around London and teach them how to make a slide.

And then from there, all I have to say is, you know, "What do you see, and what questions would you ask me?" And then the, this popcorn it.

I don't like a quiet classroom.

That's not how I educate.

I like it to be conversational.

I like it to be noisy.

And pretty soon the students are like, "I found something.

I don't know what it is." And then everybody runs and looks in it, right? And then they all start asking these questions and I say, "I'm not gonna answer these right now.

Let's write them down in our notebooks.

Let's record these questions.

Draw what you see, record your questions." And that's a really great way to have a really interesting class.

But for a parent, if I knew my child was in microorganisms, I might say, "What did you see today in that microscope? And what, what questions came up for you?"

Eric Makelky: Yeah.

Just getting that inquiry going, right?

Making sure they're curious and they're hungry, and that's when you see kids light up and get excited about what they're learning.

And then as a parent, you don't have to ask them what the most exciting thing was they learned.

They will tell you as soon as they get in the car

Christine: Exactly.

And especially if, you know, like there's room for that, right?

I mean, if you have three kids, you know, them all being like, "Oh my God, guess what I saw today? That's so exciting," you know?

You have to maybe level set and say, "Okay, each one of you is gonna tell me what was so exciting." But when you feel that excitement from your student, then you know that s- that they're growing in a different way, right?

Their growth mindset, their curiosity, and their creativity is growing along with them.

I always like to talk about this invisible backpack idea, and if you can picture that every child has an invisible backpack, and every time we teach them something, they're filling that backpack with the knowledge that we're giving them.

And for Crescando Labs, then what we want them to walk away with is the fact that they're-- they can drive their own curiosity, learn by doing, and growing confidence.

That's really what we want them to do.

So the framework is what they put in their invisible backpack.

So if I'm teaching them how to ask an open-ended question and how to ask a close-ended question and what the difference is and why there's that difference, they're filling their backpack with that.

So wherever they go in the future, they're still gonna be able to be like, "You know what? I think I need a little bit more information about that, and I'm not gonna be afraid to ask a question."

Eric Makelky: Yeah.

that's great.

And you and I were talking before we started recording today a little bit about first of all, I love the invisible backpack analogy because we all have one and that's a great way to look
at it as an educator is what am I putting in our students' backpacks that they can take with them and use especially after education when they're entering the workforce and becoming adults

and productive members of society.

But also let's talk a little bit about the AI role,

uh, comes alongside, because I know there's a lot of parents out there that, you know, AI is the front of mind for a lot of people, and there's
different views on AI's role, but especially when it comes to educating kids, there's just not a lot of resources or framework out there.

But this is something that you've been working on and the labs program has implemented.

So let's talk a little bit about the AI framework.

Christine: Yes, 100%.

I think that one of the things that we do at Chris Genova Labs is we look, you know, we're, we're constantly learning, and we're lifelong learners as we want our students to do, especially as we don't know what the jobs are gonna be in the future.

And when I listen a lot to speakers about AI, and I learn a lot about AI, I love to learn about AI, and I utilize it often, just so you know.

But what I realized in all of this is that there's not a process for educators to implement with students, and there's not a process for parents to truly understand what's happening with their student as it surrounds AI.

And what that's going to do is just like we had the growing technology gap, and I believe we still do, we're-- we have this growing AI gap.

And that's even more critical because there's gonna be the, those who have it and those who don't.

And what we wanna do instead of the polarizing the whole entire AI process, we wanna just create a bridge.

And I believe that, that this human to AI interaction does create a bridge.

And to go back to the framework for just a minute, we do inquiry and then into systems thinking, and systems thinking is really important because
we want the students to take on real world problems, but to look at every problem from a systems perspective, and that's the overall perspective.

Like, if you're looking at the solar system, right?

Or the environmental system we want them to understand that there's a community who upholds them.

There-- It's not one student working to solve a problem without anybody else.

There's a community.

So that systems thinking, we create this community that upholds our students.

Then we go into design thinking, and that's where AI interaction lives.

It lives within the design thinking cycle.

And the reason that it lives there is because once students go through inquiry into systems, and they understand how the systems works and they, they've identified the problem.

Without systems thinking, they could be solving the wrong problem.

Systems thinking definitely gives you an archetype, and then they can say, "Oh, this is the problem," and then they can solve for that problem.

Then they go into the design thinking, which design thinking is really like, how are you gonna do it, you know?

Now we know we've identified it and we've researched it because you've asked the questions, but how will you do it?

That's where we get into, you know, divergent and convergent thinking, blue sky thinking brainstorming if you will.

And then the AI comes in, and then the educator needs to say, "W- do I need to put AI into this project?" Sometimes yes and sometimes no.

It's really up to you.

Then we go, the AI interaction process starts with a question.

I mean, why wouldn't it?

It has to start with a question.

And for the students, very simply it's, "What am I trying to understand?" The educator has said, "This is what we're gonna do.

We're gonna use this AI tool." Actually, I don't wanna call it a tool.

"We're gonna use AI." And we start to, through this process, tell students that AI is a tapestry.

It's not a linear.

When you ask a question to AI, be it a generative AI or text-based AI, and you're trying to get an answer back for you, you're not hearing from one, one specific aspect of the world.

It's a tapestry.

Just like there are multiple people who fed this machine, because it is machine learning they have given it all of this information.

They-- So an AI doesn't specifically know what a human looks like because just because you put an image in, it's, it's deriving that.

It has never-- It's gonna see the world as a representation of what it was given.

As humans, we all have faults.

We all do, and that's where our biases come in.

So as the machine is learning, biases are being given because it's a human who's teaching it.

Our students need to know that because when they get feedback from an AI, it's a tapestry, it's a community that has built the AI, so that's a community giving the feedback, right?

So there's that.

The student has to understand what the AI is, then it has to ask the question, "What do I need to get from this AI?"

Then we go into frame.

Framing is really important.

Framing is how am I setting up my prompt so I get the information back that I need in order to move forward with my project?

Great.

In that prompt, you may get biases back.

You have your bias, right?

The person who's entering in this prompt has biases, right?

The person who created the AI that they're using, right, the multiple people, that has a biases.

So what we have to say to the students is, when you're setting this up, you need to look around the corner.

We need to identify what these biases are.

So framing is really important.

And again, open and close-ended questions here.

If you ask a close-ended question, you may not get the information that you need back.

You ask an open-ended question, right, you're gonna get more information back, and how do you be specific without closing that question?

Again, that's what this-- that's what the educator needs to work out.

So now we have question, do I need this?

And then what am I trying to get?

Frame, how am I setting up this prompt so I'm getting back what I need?

Then unpack.

Unpack is critical.

Unpack says you've gotten the information, whether it's an image that was generated for you, a research question that you asked and you got that information back.

Unpack is looking at the information that you have, what's here and what's missing?

Let's identify the problems and then go back and ask another question.

This is a great place to iterate.

Go back and ask another question.

And then after unpack is own.

We need to get the students to own the output, because once they take that and they add it to their project, they are saying, "I agree with this AI.

I agree with the output that has come out." And I have to say, like even when I'm working with my team or if I'm working with my students, I highly dislike when somebody says to me, "Well, the AI said this, so I'm using it." No.

That's-- Yes, the AI said that, right?

But did you unpack it?

Because now you have to own that.

Now it's yours to use, and how you use it matters.

Matters so much, right?

So after they own it, then you can go back to iterate.

What would I change next, right?

I got all of this information.

What else do I need to know to solve the problem?

And then we can go back through the rest of the design thinking process and into driving towards excellence

Eric Makelky: Yeah, I love that.

That was a great deep dive, Christine.

So in my experience, there's really two different mindsets with parents when it comes to AI, and you could probably extend this to educators.

But I'm gonna give you one, and I want you to tell me what your pitch would be to this type of parent.

If I'm the type of parent that is fearful of AI and I haven't exposed my kid to it, I haven't talked to them about it, I don't want them using it, I don't want it a part of their educational experience, what would you tell me?

Christine: Well, I mean, first and foremost, it is part of their education experience.

Schools are utilizing it, you know?

When parents sign their waivers at the beginning of the year, AI's in there.

I hate to say it, but it is.

So first it's being used.

You might wanna talk to your school,

Eric Makelky: That's a good first step

Christine: so that's first step, right?

But the other thing is, back to that invisible backpack, parents can help, right?

And when you learn this process, it gives you power.

When you have power and understanding about AI, how AI is used and how it's used within your specific family, you're gonna relax.

We all know that with knowledge comes power.

I mean, that's, you know, everybody says that.

but it's truly the fact here.

If you understand how an AI is built, it takes the mystery out of it.

And then once you understand how it's built and you understand how your student utilizes it, that's really a key.

How are they using it?

It's not going to, it's not out there to, like, change, you know, like, their perspective on life or anything like that.

You really need to say, "You need to take this, unpack it, and own it." And if the parents are using the same vocabulary at home as
the educators are using in the classroom, that's really filling that student's invisible backpack to have a better future, right?

That growth mindset of saying, "I can come in contact with any AI, generative, anything, and I know how to use it. And I know how, even better, to ask a question using the same language that the system developed it to have," right?

Prompt engineering constructing you know, like garbage in, garbage out, right?

That's a really big one, and that comes really big into unpack.

You know, if you put a bad question in, you're gonna get bad information out.

So let's unpack that.

Parents use that same language, it's, it's going to deescalate, and it's going to give parents the power to work with the students and the schools.

Eric Makelky: Yeah.

And I think a lot of parents just have a hard time wrapping their, their minds around that because this wasn't something they had to learn or deal with, especially as they were being educated.

And it, it can be pretty scary.

So it's a, it's a normal reaction for parents to be fearful and not wanna expose their kids to it.

What about the opposite, Christine?

What if I'm a parent who knows that AI is important, I know that my s- my student's gonna be using it in school, and eventually, you know, in the workforce it's gonna be a
skill, and I've just been giving them the iPad saying, "Have at it, figure it out." You've talked a little bit about this, but what would your message be to that type of parent?

Christine: So for that type of parent, I would say you really need to understand, like you n- you need to help your student frame the question that they're asking because the information is biased.

And if you just hand your child an iPad without them understanding that this is an entire community that they're speaking to, and it's an entire
community that has built this system with these biases in place, that they may be truly believing that what the AI is saying is truth, right?

Concrete, absolute truth.

They can just believe this like they're talking to their parent.

That's not, that's not how this works.

That's not what an AI is.

An AI is, you know, like if you went into like a, a, a football stadium or like a concert, and you started just asking questions, and everybody's giving you the answer, then it all comes with these biases.

And if you teach the child that, you know, don't trust this, then you're, you're really filling that backpack for that child.

You're giving them the ability to think critically, right?

We want students to think critically, and if you say to them, "You need to unpack this information that you got, and you need to own that information," then they're going to be really flexing that critical thinking muscle, and it's of the utmost importance

Eric Makelky: Yeah.

And I really love my favorite part that you've brought up so far is the ownership, because I hear that a lot with adults and students.

It's, you know, "Well, the AI said," or, "The AI told me." And it's like, well, did you really analyze it?

Did you really evaluate it?

Whether it was supporting your hypothesis or not at the end of the day, it's a tool, but it shouldn't be blindly taken at face value every time you get an output from it.

Christine: 100%.

100%. There, there is this idea when you're unpacking where it, I talk about counter-framing, right?

And counter-framing is looking at it creatively and critically that output that you're getting, right?

Can I look at this from a completely different perspective?

That's really interesting.

That's an interesting question to ask.

And if you do that, if you look at it from a completely different perspective, the output that you got, then when you own it, you have two
perspectives, and then that student has to analyze it to come t- and say, "This is what I think based on these two very different perspectives."

Eric Makelky: Yeah.

That reminds me when I was a social studies teacher and we had to teach debate.

I would let kids pick their topic and pick their side and do their research, and then two or three days before the debate, I would flip them to the opposite side.

And that was kind of my goal is like, I know you're really pro this or anti that, but now I need you to make an intelligent argument based on the facts for the opposite side of, of what you think.

And I, and I think that's a important skill to have, especially with AI.

One of my favorite things to do is you know, if it's something that I've formulated myself, I'll put it into an AI model and say, "T- tell me what I'm missing.

Tell me-- Shoot holes in, in, in my theory." Or if I take an output from one AI, put it in a different model and say, you know, "Evaluate this, analyze this, and, and tell me what I'm missing."

And that's a fun skill

Christine: Yeah, 100% I do that as well.

I have three.

I'll go, I'll go into three of them.

I'll have Chat, Perplexity, Claude, you know, I can use all of them.

And I have my favorites, and I have reasons why they're my favorites.

And then I'll also say, "Show me the research." Right?

Because we know adults know that AI hallucinates, and it's, you know, it's like your, your nicest people pleaser right?

Is what an AI is.

It's like, "I'm gonna tell you this because this is what you wanna hear." No, it's not what I wanna hear.

I wanna understand the research.

I wanna understand, again, the bias, and I wanna understand where you're getting this from so I can research it.

I wanna know.

And if you a- if I, I usually do two or three, just like you, I, I pit them against one another.

What am I missing?

Where did you get this information?

Because then I need to own it.

And to your point, if you, if you have like a debate team, and they're all like you have to critically think from the other side's perspective, that's exactly what we need to do as adults.

And when we teach that to our students, imagine how amazing they are going to be when they become adults

Eric Makelky: Yeah.

that's great.

So if listeners have more questions especially about your framework or the human AI interaction piece, w- where would you point them?

What are some good resources to learn more, Christine?

Christine: Okay, reach out to me.

I'll tell you all about it.

No

Eric Makelky: You just had a great post on LinkedIn, so start by following Christine on LinkedIn

Christine: Probably on LinkedIn.

That's where you can find the article.

You'll find the article on the website as well.

And you know, message me, but I mean, if you're really interested, I can put-- I'll put a bunch of books of where, where I'm coming from onto the website as well, and that's inquiry.

"The More Beautiful Question," amazing book, right?

That really hones in on inquiry.

Systems thinking, and there's so many great books on systems thinking.

I'll put my favorites up there.

And then design thinking, of course, there's a lot out there, design thinking.

And then the human-AI interaction, why I chose these steps, and these are for educators and parents to teach to children, right?

It's not like we're ha- gonna hand this and say, "Okay, child, go figure it out." That's not what this is.

This is a teaching tool.

And then drive towards excellence.

There's, there's a book about driving towards excellence.

And the reason that we drive towards excellence at Labs is because when you're doing the design thinking process, it's rarely taught when to get off the prototyping reel.

Students will iterate forever if you let them, right?

I mean, if you think about it, if they're driving their own curiosity in AI, they're owning all of this information, they're coming up with new questions, they could, they could go around that prototyping wheel forever.

But we, we are saying, especially for like perfectionists, you know, we have those perfectionist students, we wanna tell them, "This is
good enough for now. Drive it towards excellence. Make it as good as you can possibly make it, then we'll answer that question again."

Eric Makelky: Yeah, I love that.

Well, it's been a lot of fun jumping into the, the framework at, at the Labs program, and I'm excited for our next episode.

We're gonna dive in a little deeper on experiential learning and flexible thinking, Christine.

Yeah.

Great.

Well, thank you.

thanks for joining us today and, and sharing more about the framework at Crescando Labs

Christine: You're welcome.

This has been wonderful.

Thank you so much