Panelists reframed AI's role as a tool that handles mundane tasks so people can focus on human-centered work like relationship building, creativity, and critical thinking

Key skills for AI-driven future are adaptability, curiosity, critical thinking, creativity, and domain expertise—not just technical coding skills

Black users training AI systems reduces bias since models are currently trained primarily on European and American data where Black experiences represent only 13% max

Jonathon emphasized AI should click and type for you but never think for you—students must use it to deepen learning, not shortcut it

Maya Angelou network rolling out Microsoft co-pilot to all teachers on December 12th with custom frameworks to assess student AI use through prompt quality and iteration count

Free learning resources available including Khan Academy, Google AI courses, Deep Learning.ai, and local libraries with computer access

HBV announced Black Futures leadership program launching February 2nd through March 30th, 2026 for grades 6-10 with 36 spots available

Iraya explained AI is reshaping businesses by automating administrative tasks like expenses, freeing people to focus on high-level and person-to-person work

Jonathon noted ChatGPT turned 3 years old yesterday and emphasized we're still early in adoption—not many can credibly call themselves experts given how fast the tech evolves

Jonathon encouraged using AI not just for speed but to go deeper and expose yourself to perspectives you wouldn't have considered

Makiri highlighted that AI will eventually be ingrained in all workflows like electricity, but context, culture, and community will always remain human

Makiri positioned AI as opportunity to become more human by spending more time on pedagogy and relationship building versus mundane tasks

Makiri emphasized AI takes over mundane tasks allowing people to get to more human-centered work and in-person communication

Makiri stressed his teachers use AI for planning and idea generation so they can focus on pedagogy and relationship building

Iraya explained AI refines ideas but humans generate them—AI doesn't replace human creativity and ideation

Jonathon uses AI to delegate administrative tasks while he focuses on deeper, more intentional exploration of topics

Makiri explained AI models are biased because they're trained on historical human data, and data centers are primarily in Europe and America

Makiri noted Black population in US is 13% so Black cultural experience represents maximum 13% of training data

Makiri emphasized every time users interact with AI they're training bias out of the models and teaching them Black experience

Makiri asked what social media would be like without Black influence, comparing it to what AI is like until Black users train it at higher rates

Iraya recommended always asking AI to give facts and to not make it easy on you—AI is trained to be nice and coddle users to keep them engaged

Iraya advised students to tell AI "be hard on me, give me the unadulterated truth, and give me the facts" to combat built-in bias

Jonathon shared he uses AI as thought partner by opening new window and asking Claude to act like world-class editor and thoroughly critique his drafts

Jonathon received 37 pieces of feedback on a 2-page document and went through iterative process of refinement

Makiri broke skills into technical and human sides, with most people falling on human side since they're not coders

Makiri identified creativity (taking ideas from ideation to implementation) and critical thinking (identifying and solving problems) as core skills

Makiri referenced IBM data collected over past decade showing 13 skills with STEM dropping from #1 to #13—adaptability and creativity now rank highest

Makiri explained prompting is computational thinking and his network has framework testing whether students use AI to flatten or augment their thinking

Jonathon emphasized learning how to learn is most important skill since AI capabilities change every few months and we don't know what's coming in 5 years

Jonathon explained his ability to have Claude write 99% of his code for past 3-4 months comes from 8 years of learning coding the hard way

Iraya stressed adaptability and ability to pivot quickly will carry students through school and the AI revolution

Joy emphasized students should know their niche and focus on 1-3 skills they can leverage versus trying to learn everything at once

Joy listed key skills including AI, coding with Python, UI/UX design, product management, data analysis using Excel, SQL and Power BI

Jonathon highlighted tension between adaptability and deep domain expertise—understanding of specific fields impacts ability to effectively use AI

Jonathon referenced Humanity's Last Exam with thousands of questions testing AI on bleeding edge problems—scores went from 4% to mid-40s in past 12 months

Jonathon explained he can paste exam questions into ChatGPT for $30/month but can't validate answers without background knowledge in that domain

Makiri emphasized you cannot implement AI in education without understanding instructional frameworks, curriculum impacts on different students, differentiation, and intervention

Makiri noted edtech companies struggle with full scale adoption because they don't work in schools and don't understand coaching teachers from novice to proficient

Iraya agreed students should be experts in areas where they use AI, but also noted AI helps break down complicated ideas into digestible chunks

Iraya expects people will need larger breadth of expertise going forward because AI enables them to learn and do more

Makiri shared teachers are lesson planning with AI whether they admit it or not—some use it as thought partner, some generate whole lesson plans

Makiri explained they can record coaching conversations and get feedback on how conversations went, then measure quantifiable impact over time

Maya Angelou network built custom leadership GPT to provide support for novice leaders so they have Makiri's thought process as partner

Maya Angelou network endorsing Microsoft co-pilot on December 12th with all teachers getting access

Makiri worked one-on-one with teacher to build co-pilot instructions and test lesson planning format for 45-minute ELA lessons

Makiri developing assessment framework where presentations might be 90% of grade and students defend ideas like dissertation versus 50% PowerPoint/50% presentation split

Network teaching AI literacy in senior seminar courses developed with University of Maryland over summer, currently polling for data

Makiri noted old students are "whipping up on their professors" who haven't adapted, so secondary schools are trying to adapt before kids just start using models anyway

Iraya explained employers take employee surveys with hundreds of individual written responses that previously required line-by-line review

Iraya now uses AI to crunch all responses into one big idea and ask for top 5 solutions to problems identified in survey data

Jonathon shared Claude is updating his website right now and he can go for walk or gym while another feature gets built

Jonathon mentioned Gennile just drafted a proposal he can send off using AI

Karina uses AI tools to build outlines for decks, presentations, and client communications—not copying exactly but getting starting point to run faster

Iraya recommended Khan Academy and going to local library since most have computers with internet access open during after-school hours and weekends

Iraya emphasized staying curious and hungry, thinking outside the box to find resources like asking librarians and teachers for help

Iraya noted teachers usually love curiosity in students and will go "mile and a half" for students showing that drive

Joy stressed self-discovery matters and students should create community with like-minded peers who want to learn

Joy suggested finding mentors like enthusiastic teachers or professors who can spare equipment or tools for learning

Joy recommended paying for training if financially possible, even $10 for online courses that offer one-on-one mentorship

Jonathon advised against YouTube and LinkedIn due to get-rich-quick schemes and suggested free courses from Anthropic, Google, and Deep Learning.ai

Jonathon specifically recommended Deep Learning.ai course called "ChatGPT for Everyone" as good starting point

Jonathon suggested experimenting for 1-2 months with free resources before paying for course that fills specific skill gap

Makiri emphasized there's no better teacher than yourself and encouraged students to interact directly with tools to identify and solve problems

Free resources mentioned: Khan Academy, Google AI courses, Anthropic courses, Deep Learning.ai, local libraries

Jonathon specifically recommended Deep Learning.ai course "ChatGPT for Everyone"

Jonathon advised doing due diligence with free resources for 1-2 months before considering paid courses

Joy mentioned paying for training if possible, even $10 for online courses with one-on-one mentorship

Makiri noted best practices for AI use can be Googled or asked directly to the AI models themselves

Panelists encouraged reaching out to them directly on social media and LinkedIn to continue conversations