Most software engineers at major technology companies follow a familiar arc: deeper specialization, more complex systems, and increasingly narrow expertise. Arif Akram Mohammed went the other way.
After more than 15 years in software engineering—including six years at Apple—Mohammed stepped away from conventional career progression to explore a different question: How early can people truly understand artificial intelligence if it’s taught the right way?
His answer took an unconventional form. Mohammed created a card game called Hangry Dogs, complete with original characters and artwork. Those characters later became the foundation of a story-driven book, AI Made Human: Tales of Giethwick, which teaches core artificial intelligence concepts without formulas or code.
Released on Amazon in December 2025, the book is aimed at middle/high school students, non-technical professionals, and adults who feel shut out of AI conversations. Rather than teaching AI through equations or code, Mohammed uses storytelling to convey how these systems learn, adapt, and sometimes fail—guiding readers from foundational ideas to more advanced concepts along the way.
Why This Approach Matters Now
AI literacy has become a national concern. Students encounter AI-powered systems daily, yet most formal education introduces the topic only at the college or graduate level. Parents want to guide their children but many lack the technical background to do so. Meanwhile, non-technical employees across industries are expected to collaborate with AI-driven tools without understanding their mechanics.
Mohammed’s work addresses all three gaps at once. By reframing AI as a conceptual system rather than a mathematical discipline, AI Made Human lowers the barrier to entry without sacrificing intellectual rigor. Mohammed’s longer-term aim is to spark curiosity and confidence around AI and STEM before intimidation becomes a barrier.
“Accessibility and depth don’t have to be opposites,” Mohammed argues in his project materials. “If you understand the ideas, the math can come later.”
Testing the Idea Where It Counts
Before publication, Mohammed tested the manuscript with eighth-grade students at his former school in India. Their feedback—captured in a short video—showed comprehension of ideas typically introduced much later in academic pipelines.
Several independent Instagram reviewers have since picked up the book organically, signaling broader interest in non-traditional approaches to AI education.
The response highlights a broader shift: as AI becomes embedded in everyday decision-making, the demand is no longer just for engineers, but for informed citizens who understand what these systems can and cannot do.
Engineering Meets Storytelling
Mohammed holds a master’s degree in computer science and has spent his career building production software systems. Alongside that work, he developed a parallel creative practice—character design, game mechanics, children’s activity books, and educational storytelling.
The Hangry Dogs universe began as entertainment. Its evolution into an educational framework reflects Mohammed’s broader philosophy: narrative isn’t a distraction from learning, but one of its most powerful accelerators.
“Most engineers move deeper into specialization,” he says. “I’ve chosen to bridge engineering with storytelling—especially to make complex ideas accessible to younger and non-technical audiences.”
A Different Model for AI Education
Mohammed is not positioning AI Made Human as a replacement for formal curricula. Instead, it functions as a conceptual on-ramp—preparing readers to engage with technical material later, rather than avoiding it altogether.
For an independent author competing against established educational publishers, commercial outcomes remain uncertain. But the early signals—classroom validation, organic reviews, and growing interest in AI literacy—suggest the project taps into a real and under-addressed need.
As debates around AI regulation, workforce disruption, and education intensify, Mohammed’s work raises a timely question: What if understanding AI didn’t start with fear—or formulas—but with stories?
