S5E19 Neuroagnostic Learning - Why One Size Fits One: Derek Crager

What if the best mentor you ever had lived in your ear, spoke your language, and waited while you tried step one? We sit down with Derek Crager, the builder behind Amazon’s highest-rated training programme and founder of Practical AI, to unpack how audio-first tools can transform learning for teams and students without adding more screens or stress.

Derek’s story begins with a late diagnosis of autism, ADHD, and dyslexia, and turns into a design principle: neuroagnostic, human-first learning. Instead of asking people to declare labels, Pocket Mentor listens, mirrors, and adapts in real time. Tap a button, ask a question, and get a clear path forward, plus a check for understanding. No video feeds, no LMS fatigue, just voice guidance that fits into movement, work, and life. Behind the scenes are tight guardrails, a single source of truth for company knowledge, and layered language models that catch hesitations and make space for interruption.

We explore why replacing humans with AI is a short-term win and a long-term loss, and how positioning AI as a mentor protects creativity, fuzzy logic, and the odd tangents where real breakthroughs happen. On the factory floor, that means diagnosing a VFD error safely and quickly. In classrooms, it extends one-to-one time so pupils can chase the why behind the lesson and arrive more engaged. For onboarding, it turns a maze of SOPs into a conversation that helps new hires feel competent and valued faster.

This is a practical blueprint for cognitive equity: one size fits one, with audio as the lowest-friction interface and trust built through better questions. If you care about faster training, safer operations, and learners who stay curious, you’ll find plenty to try tomorrow. Enjoyed the conversation? Follow the show, share it with a colleague, and leave a quick review to help others discover it.

Transcript

Stephen King 0:03

And hello everybody, and here we are on yet another episode of The Incongrant. Uh, we're getting close to the end of the season now, and I am joined again today by Arjun.

Arjun Radeesh 0:15

Hello. I feel like I'm Superman again.

Stephen King 0:20

And because we're close to the end of the season, Arjun is out of words. So that just shows how close we are.

Arjun Radeesh 0:26

As in, as in, I'm I'm I'm privileged to be the one to start the season. Um privileged to be the one to wrap up the season.

Stephen King 0:34

We just hang on together. That's what it is. Okay, uh Superman, uh Clark Kent. Uh Clark is Kentus. Uh tell us who did we speak to today?

Arjun Radeesh 0:45

So today we spoke to Derek Crager. He uh he basically uh created Amazon's highest-rated employee training program before launching his own venture called Practical AI.

Stephen King 1:02

He has this brilliant voice-based AI solution uh called Pocket Mentor, which is particularly helpful for those of us who are a little bit neurodiverse. So uh and we talked through all of those issues today. Um was there anything in particular that stood out to you?

Arjun Radeesh 1:20

No, definitely, even though the world says, oh, you gotta do everything in video and all those. Uh I felt a bit happy when he said, okay, there are still a bit of people who still would want to do things in the audio form.

Stephen King 1:34

Voice-based AI systems are very powerful, voice recognition and voice synthesis. Um, and this is this is a very powerful use of that. So if everybody's ready, we're ready to remote. And here we go.

Arjun Radeesh 1:49

Hello, and welcome to a brand new episode of Incongruent. So today we are joined by Derek Crager. So Derek built Amazon's highest-rated employee training program since launching practical AI to domestify artificial intelligence for every business, not just the Silicon Valley joints. Practical AI, Derek empowers individuals by teaching real-life applications of AI that drive profit, save time, and grow careers. It's a free community now that includes 6,500 neurodiverse, technically gifted professionals. They focus on making AI accessible, useful, and simple to apply. Derek's own journey with autism, ADHD, and dyslexia shaped how he sees AI and humanity. In his view, those two are identical in their unpredictable creativity and pattern-finding abilities. Derek is joining us to explain more on his approach that helps train skilled workers 80% faster with tools like Pocket Mentor, giving companies immediate and measurable cost savings. So, Derek, uh, welcome to Incongruent and how has it been going for you?

Derek Crager 3:11

Hey, uh, thank you so much. I've been looking forward to this all week. I'm excited to be here. Uh, point of clarification on the intro, just to uh for the listeners' sake, I have the for-profit side that you know works with enterprise work and has own products out there. And then on uh the nonprofit side, that's where uh our group comes together and we work together just to uh just to build and to talk, uh shop uh to build out. So uh those are two different entities, but the uh the North Star remains the same. That's uh empowering people with AI.

Arjun Radeesh 3:44

Amazing. So uh let me drive in straight into the questions. You built Amazon's highest rated training program before founding practical AI. What problem did you keep seeing in corporate learning that pushed you to strike out on your own?

Derek Crager 4:06

Well, I saw that uh corporate learning, they they they never removed anything. It was always add-on and add-on and add-on. Pretty soon you can just imagine a big stack of band-aids is is how traditional corporate environments work. So what I did, I uh and even at Amazon, the uh the organization that I was with, um I helped grow, I think, our our internal org from 35,000 to 70,000 people. So I trained about uh 35,000 of those within the first year.

Dereck Crager 4:35

And the spot-on piece that I saw was the old way of doing things was that 82 hours of video had to be watched and answered, you know, that like the old LMS and things that people no longer connected. And and everybody knew it was just uh, you know, a bad form of education.

Dereck Crager 4:55

So I I know when I see things like that, Arjun, is that I'll open 10 windows and I'll have 10 videos going at a time just so I can get through it. And I discovered that's how majority of our uh our students did the same thing. So my my training program came in there to replace that rote memory and actually honor the uh the unique ways that all of us learn. And it really comes down to being human first. That was the uh anchoring point and the foundation for our success.

Arjun Radeesh 5:27

Yeah, coming back to our conversation, I really did like that um phrase that he used using um AI for good, like AI for good and using AI for humanity. Um and uh and during the intro, I also kind of read that um you basically went through the stages of um stage stages of dyslexia, ADHD, autism. So I wonder, can you just walk us through uh a moment where your neurodivergence changed the solution that you built?

Late Diagnosis And Human-First Design

Derek Crager 6:03

It was a light bulb moment. I had started, I was about six months into uh my time at Amazon, and I was diagnosed, we call it late diagnosis at age 50 with uh autism, ADHD, and dyslexia. And I I gotta tell you, I I had some physical reaction. I cried off and on for two weeks, and it was more of a happy light bulb moment.

Dereck Crager 6:25

And I thought, oh, that's why people just didn't get me, you know, throughout my history. But looking back on all that, it allowed me to put everything in perspective that when I did succeed in the past, it was always when I had the right information at the right time and in the right amount.

Dereck Crager 6:41

So I uh I embraced my diagnosis, not so much as, hey, I'm different, I'm better than you, or uh, or I have superpowers. It was the fact that I honored the value that we are unique and uh and I integrated that into the training programs I built at Amazon. And it turned out to be that was the foundation right there.

Dereck Crager 7:01

Understanding, truly, understanding that we're all different and we need to learn in different ways. So, my the way it shaped my uh my training, my facilitation, my mentoring perspective is that let's build something and make sure that there's enough information out there so that everybody gets the information that they need when they need it and and and how they need it.

Dereck Crager 7:26

And I did that at Amazon. Amazon has, you know, AWS is one of the biggest companies in the world. So they had a lot of technology around them. And that's really how it shaped. I embraced that understanding of the difference so I could understand all the students that are there. And it made this connection that we are truly unique. It's no longer a one size fits all economy. We're truly at the point where it's one size fits one if you want the best response. And uh the technology that I built as after I left Amazon allows humans to actually learn one size fits one.

Stephen King 8:07

Um I'll try and jump in there. Um now one of the one of the unknown one of the insights that I am developing in my own uh Neurodivergence journey is perhaps that reason what one of the reasons that we don't use video is because I can't sit still to watch a video. And so it's my personal decision that we don't record it. And I have the podcast, and I whenever I'm listening to it, I'm just walking around the house or I'm doing whatever it is I'm doing. So I it's it's purely selfish that we're using podcasts. But what what is it that uh your solutions look like? You say that you're able to tailor it to different people. What do you find that people with ADHD or people with autism or people because it's a huge spectrum of uh which of different um conditions? Um what kinds of things does it look like? What do you do differently for people?

Derek Crager 9:04

Well, it's interesting you you know you mentioned the distractions that are there. And one of the things that I incorporated in our in-person learning, uh, you spoke of your uh your podcast uh being created during COVID-19 epidemic, as as far as your uh your original start. Uh, I actually traveled with Amazon training in person uh from 2020 all the way through uh 2024. And I traveled more during that time than I have before or since. And so we were actually uh connecting with people live. And in order to, because it's live, you can't cut video from live eyes.

Dereck Crager 9:44

So I actually would hand out, we call them fidget toys.

Dereck Crager 9:48

So when people are sitting there in their seat, and uh I would be holding one up right now if we had a camera on this podcast, but I've got a couple of them right on my desk, and that allows us to uh keep our fingers busy so our mind can stay focused.

Dereck Crager 10:02

So that's one example in the physical world. And if we're going to uh how do we achieve that in in the virtual world, how do we achieve that using AI? Um, the way I train the AI, the way we train AI here at practical AI is that we teach it like it's the trainer. You might have heard the term train the trainer. So anybody in training, talent development, facilitation, we talk about training the trainer. I want to teach you to teach as good as I teach. That's my goal.

Training The AI Like A Trainer

Dereck Crager 10:33

So we grab that same goal and we apply it when we're building out these AI proxies for our trainers. And we educate it and we we give all sides of the elephant, if you're familiar with that metaphor, you know, the six blind men and the different sides of the elephant. They all have different perspectives, right? You have the uh elephant uh that's that's facing forward, and

Derek Crager 10:58

and the gentleman in the back is holding on to the tail, and he says, Oh, well, uh, this blind man says, Oh, elephants are long and thin like a braided rope. And somebody next to him says, No, no, you are wrong, sir. Elephants are big and round like a tree trunk. And it's all a matter of perspective.

Dereck Crager 11:15

So a good trainer, a good facilitator will understand the differences in humans. And as the conversation progresses, and this is how we teach our AI to respond, we give it the capability to identify all these nuances, all these pattern recognitions. And then through the conversation, just like you and I are having conversations here today, uh, I learn a little bit more about you with every uh sentence that you give, and you learn a little bit more about me with every sentence and the word that I give.

Dereck Crager 11:47

We train the AI to do the same thing, to recognize patterns, to identify word choices, and then align, still gets the message across, but align with that individual on that one-on-one level. So uh the short answer would be we train just like we would train the trainer.

Stephen King 12:08

That requires a number of different AI services working together. Because you talked about being able to understand language. Um, you've be I'm assuming you're gonna have some kind of uh computer vision going on to detect eye, I'm assuming I'm just predicting uh eye contact because that's that's a big symptom. Uh do you have a list of which services and which platforms that you're you're using for your tool?

Derek Crager 12:39

Well, just for clarity here, we are a audio interface only. So just like your podcast, uh yeah, we're not looking to uh ingest video data. Um our our solution is somebody's walking around, they have a need, they hit the magic button in their ear and they say, Hey, Pocket Mentor, you know, talk me through this.

Dereck Crager 12:59

There's five steps. I'm kind of fuzzy on the third step. Can you talk me through it? And so this is when uh Pocket Mentor will respond with the steps in order and he'll say, Are you okay with that? Do you understand that? Do you want me to break it down, you know, explain it like I'm five type of thing.

Dereck Crager 13:16

So it's the same type of mentoring that you would get through a telephone call or an audio-only podcast.

Dereck Crager 13:22

So we are not taking in uh video, which uh makes things the barrier to entry. Uh we zero out the barrier to entry because we're leveraging uh a telephone just like you would, or a digital telephone like a VoIP call, uh just like any human would.

Dereck Crager 13:39

Now, the technologies that we use on the backside, you know, we have the knowledge domain that we uh put guardrails in that uh allows the LLMs to access only the correct information rather than going out on the internet and just grabbing any answer that could be a solution. We relegate it to just the answers that uh that align with that organization's goals. Um we have uh some layering of LLMs.

Dereck Crager 14:05

So yeah, we we listen to the pauses, we listen to the hesitations, we make sure that we allow the speaker to interrupt and uh the the AI when it's talking. So everything is uh audible and we just layer this in, just like uh we would teach a trainer to understand that uh uh if there's a long pause or some hesitation, um, and some things that, like you mentioned, you know, if we see somebody's eyes go wonky and you know, we we can see visually that they don't get it. So in place of that, there's simple cues.

Dereck Crager 14:42

We'll just have the uh AI after every delivery, just ask a confirming question, you know, and and that's where we get through we're using AI to think with the human instead of thinking for the human. It's not just spitting out an answer like you do with the keyboard with ChatGPT. It's truly connecting with that person in a way that, uh, hey Stephen, you know, those are the five steps. You know, here's step one. Would you like me to walk you through it? Or I tell you what, when you finish step one, you tell me how it is, and then we'll review that together. And that's what we're doing here. It's just reassertion.

Neuroagnostic Support And Mirroring

Stephen King 15:17

So, final question before I ask you to go back into the schedule that we have. Um, do people need to have an official diagnosis? And does that diagnosis need to be fed into the machine earlier? Or does the machine infer and just tries to be as helpful as possible based on the responses to prompts that it's been given?

Derek Crager 15:40

Well, that's a uh great question. And what we do, we actually uh uh step back a step and and address everybody. I uh I coined a term, I don't know if it'll hang around for more than a decade or two or even a day or two, but I turned the uh coined the term neuroagnostic.

Dereck Crager 15:56

So our program, our product actually speaks without any special acknowledgement of um diagnosis. Because even in a diagnosis, uh if if we just take the a top-level autistic, me being autistic and someone else being autistic, well, we can't paint ourselves with the same label. Uh, who is it uh uh, you know, once you label me, you negate me type of thing.

Dereck Crager 16:27

So we're still unique, even those of us that have a diagnosis. And so it's not just about conforming our tool to address ADHD or uh autism, or you know, there's hundreds of unique diagnoses that are out there that that are separate and then there's still overlap. So what we do, we step back from the problem and we don't look at issues, we look at the human and we just ask the question what does this human need to uh to understand the uh the conversation as we progress?

Dereck Crager 17:03

And and as I well, I guess as I explained earlier, it's just a one-on-one step. I'll learn something about you, Stephen, with every question, with every statement. And it doesn't matter if you're autistic or not, you still are going to begin displaying a pattern, and I will just mirror, and that's a psychological thing, right? Mirroring technique we talk about on how to get people to align. Uh so at the basic level, we're actually uh introducing mirroring technique to align with that individual caller.

Arjun Radeesh 17:39

Um so your community is 6,500-plus, neurodiverse, technically gifted professionals. What have they taught you about you uh taught you about how AI should behave if we really care about cognitive equity?

Derek Crager 18:01

Well, I uh I think the biggest takeaway is that uh you know, we look at everything with face value, you know, with a grain of salt to throw in those aphorisms of old. And it's the fact that uh with the right questions, uh you'll get the right answers.

Better Questions, Better Answers

Dereck Crager 18:16

And if we if we step away before AI

Derek Crager 18:19

even came about, uh we we look at um autistic individuals, if you ask them a question or when asked a question, they'll respond based on their understanding of the words. No context, just the words, and those answers will come out you know, weird to to the you know, quote unquote normal people that are out there. And now we introduce AI and ChatGPT.

Dereck Crager 18:46

And it was just, what was it, uh two or three years ago they started talking about this new career path, be a prompt engineer, right? Because if you phrase the question the right way, you're gonna get the right answers. And autistics around the world rejoiced. We said, Oh, yeah, great. Humanity's gonna finally learn how to talk to us because we're the same way. If you phrase the question the right way, we're gonna give you the right answer. If there's context or innuendo in there, well, we're just at face value.

Dereck Crager 19:16

These words have uh have specific meaning. And if you're gonna change that meaning through your own intonation, your own context, you have to explain that as well. So this, I think this is a great alignment point and uh and a huge win for the neurodiverse community, is that all of humanity is learning how to be better questioned um architects.

Arjun Radeesh 19:42

Wow, that's a very interesting take. Um You've said AI and humans are identical in their unpredictable creativity and patent finding. Can you unpack that and what that means for how we work with AI rather than against it?

Creativity, Tangents, And Thinking With AI

Derek Crager 20:03

It's an extension of uh that uh last answer. It's uh it's that uh we tend to go down rabbit holes, you know. Let's let's go off on this tangent. Let's how does this associate? And and you know, tangent upon tangent upon tangent or layer upon layer. I think there's a uh a term over here, you know, talking about uh an indigenous tribe that is talking about uh you know, God said the earth is built on the back of a turtle.

Dereck Crager 20:29

And when asked the question, you know, well, what's underneath the turtle? And they go, well, another turtle. And then, well, what's underneath that turtle? And the response is, well, it's it's turtles all the way down. And uh it's uh it's it's we get we can get um sidetracked or so focused that uh that there's terms out there, you know, we can't see the forest for the trees, uh, we're too in the weeds.

Dereck Crager 20:56

And you know, that's what happens as well. Sometimes those journeys end up as a dead end, but other times those journeys take us to places that uh that we've never been before, and the result is something new. And and that's the path we can take when we communicate with AI is because it allows us to think with AI and expand our process.

Dereck Crager 21:18

So it's more than just a journaling effort, it's a true back and forth thinking with us to allow that creativity to blossom.

AI As Mentor Vs Replacement

Arjun Radeesh 21:31

Uh okay, um, so um where where do you draw that line between AI as a productivity tool and AI as a mentor? And how would you stop companies from using AI mentors as an excuse to underinvest in people?

Derek Crager 21:53

Oh, great question. And I write about that in my book. It's uh coming out uh by the end of the year. It's human first AI. And that's where we need to draw the line. Is there going to be AI, and we're polarized at this moment, at least in the business community. Uh we're going to use AI to replace humans, which is great, right? ROI for the first two or three years. It makes our books look better and the bean counters are happy. But in the long term, we lose that creativity that we just spoke about a moment ago.

Dereck Crager 22:22

And so that's the fork in the road that we're at. And it's important we choose the right path.

Dereck Crager 22:28

Using AI as a mentor really enhances and it gets the best of both worlds. It takes uh the human category, that that creativity, that's where our value is. Creativity, fuzzy logic, seeing things that other people don't because each of us have a unique experience up to that point in life we're at today, all of us do. And then taking that information and then we bond it, we pair it with AI to document that new technology, to research it and align it and digest it so it can be later shared with our entire workforce.

Dereck Crager 23:05

Uh, and I'm speaking, you know, at the enterprise level here. So when somebody discovers something new, it's typically a human that does that. A human has to be in the loop at some point. So when we pair AI as a mentor with the human, we get them to think better, allow them to come up with those creative solutions while still looking and empowering their fuzzy, fuzzy logic to see things that AI would. Because AI in a box is exactly that. It's programmed to do something specifically within boundaries. And if we look at that first scenario where we replace humans, uh, we don't want to replace humans uh for the fact that the negative aspect is when that company hits two or three years down the road and they're no longer being recognized for these creative developments, they're no longer making these strides of creativity that humans input because it's just an AI in the box.

Dereck Crager 23:58

And an AI in the box is just going to be like Henry Ford's first assembly line. It's gonna continue running until the grease wears out and then it breaks down, or civilization around has advanced so far that that original machine no longer applies. And and that's a big uh difference right there. As far as um, you know, the backstop you ask, how do we keep companies from using AI mentors as an excuse to underinvest in people?

Dereck Crager 24:25

Um I I truly believe that just from a pragmatic sense, once they start using AI to augment people, they uh their ROI will be immediate and so profound that they're not even gonna look elsewhere. Um, even if they had that negative intent uh to begin with.

Use Cases In Industry And Schools

Stephen King 24:44

I'm gonna try and uh tap on the questions we've got here because from what you're what you're saying, it's it reminds me of a LinkedIn post I saw today, where in the teaching environment, and I know you're in adult uh training, but in the teaching environment, there is a complaint that the AI is is not being implemented uh and is only lipstick on a robot. It is very, very skin deep. Um, and that's because the leadership teams are just too scared to really see the potential of transforming their businesses and they just don't see the disruption, they don't see the reason why they should, uh, and they don't want to explore they would they want to give it the time to explore what they what the potential is um what would be the use cases or the initial use cases that you would recommend to a mid-site business, because more schools and education facilities are mid-sized businesses, but doesn't have to be education. What would you say you know you really should be exploring these transformational futures and opportunities? What would be the use cases that you you you you foresee that anyone might be able to uh benefit from?

Derek Crager 25:57

Well, business and enterprise use case are uh our impetus here, that's what started our company was uh the frontline workers in manufacturing industry. And that's the uh operators that have uh have to that require a certain amount of skill set. And their skills and knowledge, it's really separate things.

Dereck Crager 26:14

And we expect it that it's that's one of the same, but it's not. So we empower the frontline workers to do what they do best, and then in that moment of need or hesitation, ah, wait a minute, can you just confirm you know the data point? And it gives it and they can continue running operations without time with uh skilled trades fixing something, they tap the earpiece and they say, Hey, I've got a um a uh uh VFD variable frequency drive here running this 480 volt uh motor and it's got this error.

Dereck Crager 26:47

Can you talk me through diagnosis and repair? And so that's a that's another part on the business side. Now, if we jump to schools, schools um, I'm talking the K through 12 variety, and I have experience as a student, I also have experience as a parent, and I have experience as a substitute teacher within the system. So I've seen both uh the school systems from inside and outside. I see a smile in there a little bit. Have you substituted uh yourself? Have you tried that on?

Stephen King 27:18

It's in it's in the pipeline, but I've seen I I can imagine from what you're experiencing.

Derek Crager 27:24

Well, it's uh it's a neat thing, especially to come in as a uh, you know, the adult learner side and then see everything that the K through 12 uh goes through. And the one constant that we see here is that K through 12 teachers work 12 plus hours a day. It's huge. And we see that uh the time that teachers spend with students keeps growing smaller.

Dereck Crager 27:49

U m, and how do we address that? Uh, we have the teacher to student ratio that is always important. Uh, my favorite ratio uh number is one-on-one. And that's what we do with Pocket Mentor. It's that scalable proxy for the teacher, for the supervisor, for the manager, for the trainer, for the facilitator, you know, for yourself.

Dereck Crager 28:11

It's that that scalable one-on-one to deliver that knowledge 24-7 to anybody that needs it. Now, the limitation in K through 12, you know, if you have 20, 25 students in a classroom, and some uh here in the States are even greater, you know, 30 plus. Um, but when you have that many and you only have uh, let's say 40 minutes in a class, and with 20 students, that means there's two minutes that a teacher can deliver one-on-one with that student. And you've been in class, you've seen this happen.

Dereck Crager 28:43

It's rare, it's probably impossible that the teacher is going to spend an equal amount of time with every student. And what ends up is that there's always the students that are involved and raising their hand, and the majority of the time gets spent with them, and their minds get developed because their questions are answered. Now, you know, the uh the students in the back of the class, they're not getting their questions answered.

Redesigning Onboarding One Size Fits One

Dereck Crager 29:06

So they go home, they're not connected, their curiosity that they

Derek Crager 29:10

might have had on day one wanes as the school year goes. So we're actually experimenting here with K through 12 solution that um it empowers the teachers to teach, to do what they do best. And then on the back end, it uh allows each one of the students in their own time to continue that conversation with the teacher.

Dereck Crager 29:31

Let's just say we download that uh the teacher's brain. And in this instance, we download the teacher's brain, but what we're really doing, we're downloading, you know, science for seventh grade or math for eighth grade, a topic, history, social studies. We download all that and then we put it in a box and we give a phone number and a push button for students to call in. And instead of talking to Mrs. Johnson, they're talking to Mrs. Johnson AI. And it's like Hey, you know, I we're in chapter three and we're talking about um, you know, how hydrogen peroxide and and I don't know, whatever react.

Dereck Crager 30:10

Can you tell me what if we mix it with this? What if we mix it with that? What if we mix it with something else?

Dereck Crager 30:15

And the neat thing about curiosity is that it will continue forever if there's an available amount of time. You know, work expands to the time allotted. So if we can expand that time that the students have with the topic um at hand, then they can uh satiate their curiosity, ask all the questions. And now when they return to school that next day, they're so much more engaged that they understand the why.

Dereck Crager 30:44

I think Simon Sinek talks about the why of something. So many students don't understand the why. They're just told to do, well, you do A and B and C, and they ask why, and they say, because I said so or because the textbook said so. With Pocket Mentor on the back end, they can actually dial up their textbook and not get answers, but they can actually have a valid conversation to say what if. And that's what we're given here. That's that's the value, and that's how I see a AI mostly uh you know growing in the K through 12 infrastructure is to augment that one-on-one time that teachers don't have today.

Stephen King 31:21

Brilliant. So we've got one last question here. Uh, and it's if you could redesign workplace training from scratch for neurodiverse talent, uh, which is baked in from day one, what would it look like? What would the ecosystem look like? What would we have in there?

Derek Crager 31:40

Well, it's uh it's what we've done already. It's uh taking that neuroagnostic view and addressing this one size fits one mentality. And it allows the companies, the enterprises that we work with, to take their SOPs, to take their knowledge base, to take their vision and their mission statement and put it all in a box and look at that box as a single source of truth. So we don't have multiple versions that are out there that confuse the employee base.

Dereck Crager 32:12

Uh it's a way for let's say a new hire comes in and they uh they have time with their manager, they have time with their peers. So once again, that time is limited. So they just hit the magic button on their earpiece and they say, Hey, I'm here on day one. And how does the the uh company vision statement apply to my role as product manager? Okay, can you tell me about my role as product manager? What do other product managers do here at Amazon?

Dereck Crager 32:42

Um, it's this conversation again to uh to lean on the uh story that I told with the K through 12 where the student is asking questions. Um, it allows us to uh it allows the user, the employee to ask as many questions as they want while they're working. So it's not time away. And it allows them to satiate the curiosity and to create some one-on-one soundboarding. Well, hey, uh, you know, Pocket Mentor, if I was going to do this in my role, you know, how would I best uh perform? Or where should my starting point be?

Dereck Crager 33:17

Or can you can you tell me the uh all the uh other product managers that are in my building? And that that's it's having information when you need it. It and it doesn't matter if if we have a label that's neuronormative or neurodiverse, it's the fact that all of us as humans need knowledge, no matter how our brain works.

Dereck Crager 33:40

And if we can gain that knowledge through a simple tap of a button and asking a question, and then expand that knowledge through practical use of interacting with that knowledge base in a human capacity, well then that allows us to onboard much quicker, allows us to understand our role. And the biggest part is employees. Employees want to feel validated, they want to produce something, they want to be productive.

Dereck Crager 34:08

I think that uh the last uh survey I saw that um that the reason people work for a specific company, that uh the money itself is in third or fourth place, and it's really about feeling validated and productive. And that's what we give them with Pocket Mentor. It's that solution right in your pocket that that makes sure that none of us are ever alone.

Stephen King 34:29

Gives you independence, gives you agency, gives you control. That's amazing. Well, thank you very much. That's really inspirational. Uh Arjun, would you like to close us down?

Closing Thanks And Listener CTA

Arjun Radeesh 34:38

Uh sure. Uh once again, thank you so much, Derek, for joining us and giving a bit of insights on Pocket Mentor and how Pocket Mentor is creating that sort of impact uh within the Neurodiverse community. And um and and and and good luck with all the new um wenches you guys are going to explore into and to all the listeners out there. Thank you for tuning on once again to the Incongruent Podcast. Uh, please do like, share, and follow us on your favorite podcast platforms. And yeah, until next time, this is the entire crew from Incongruent signing off. Goodbye.

Editor 35:16

Last edited December 31, 2025.