The Urgency
AI is already in school.
The risk is having no plan.
A child entering kindergarten today graduates college in 2042. By then, AI will be deeply embedded in nearly every industry students enter. The tools, the expectations, and the nature of work itself will look materially different from today.
Yet most schools still optimize for skills AI already does well: memorizing facts, following procedures, standardized problem-solving. Students are being trained to compete with machines — and machines will always win that competition.
This pathway doesn’t chase the hype or avoid the question. It teaches the four capabilities that stay valuable regardless of which tools dominate next year: orchestrating AI systems, exercising human judgment, learning how to learn, and building real things.
- Shift from memorization to orchestration — students learn to direct AI, not compete with it
- Cultivate the human capabilities — creativity, ethics, leadership — that compound over a career
- Build metalearning habits so students can adapt as tools and industries evolve
- Replace worksheets with real projects, real employers, and real community impact
The Core Framework
Four skills that outlast every tool update
Schools that teach students about AI give them a semester of relevance. This pathway teaches them four capabilities that stay valuable regardless of which tools come next — starting from Day 1, in every course.
Not just using one chatbot — understanding how AI systems work and combining multiple tools to accomplish complex goals. Prompt engineering, output evaluation, multi-tool workflows. This is becoming a foundational literacy for school, work, and civic life.
Genuine creativity, emotional intelligence, ethical judgment, leadership. These aren’t “soft skills” — they’re the most durable human advantages in an AI-saturated economy. Every course cultivates them through community engagement, ethical reasoning, and collaborative problem-solving.
Facts change. Tools evolve. The only permanent skill is the ability to learn new things rapidly. Students practice metalearning throughout the pathway: approaching new domains, identifying what matters, evaluating their own understanding, and adapting as technology shifts.
Every course involves making things that didn’t exist before — not worksheets, not standardized tests. AI self-portraits, bias audit campaigns, community solution prototypes, professional portfolios, public capstone projects. The future belongs to builders.
Differentiation
Why this pathway instead of a generic AI curriculum
National vendors offer semester-long AI survey courses — useful introductions, but they stop at awareness. This pathway is built for institutional adoption: a multi-year program of study with credentials, internships, and local relevance that a one-semester product cannot provide.
- Teaches students about AI — awareness without application
- No progression from literacy to orchestration to professional practice
- Zero project-based learning, zero work-based learning hours
- Geography-agnostic — same content in Maine and New Mexico
- Annual participation fees ($500–$2,200) plus $1,200 PD
- No credentials, no postsecondary articulation, no portfolio
- 3-course sequence built around AI orchestration, not just awareness
- Human-exclusive skills — creativity, ethics, leadership — in every course, not an elective add-on
- Metalearning practiced throughout: students learn how to learn new tools and domains
- Students build real things from Day 1 — portfolios, prototypes, public capstones
- 80+ hours of work-based learning with NM employers; industry certifications included
- Grounded in NM communities, culture, and industries — built for Perkins V funding
For Decision-Makers
Why administrators say yes to this model
This pathway is designed to reduce the biggest barriers that stop new programs from getting approved.
Designed to fit Perkins V and NM CTE program structures. Uses existing funding channels, not new budget lines.
Runs on existing devices with web-based tools and phased implementation. No new labs, no expensive licenses.
No coding prerequisite barriers. Designed for broad student participation across backgrounds and skill levels.
Connects AI to real New Mexico industries, communities, and postsecondary pathways — from LANL to acequias.
Built with privacy, ethics, and teacher oversight in mind. Structured to support district compliance review from the start.
Creates student work, credentials, showcases, and partnerships that communities can actually see and celebrate.
“New Mexico is a place where 1,000-year-old pueblos sit across the valley from particle accelerators. This pathway embodies that productive tension — teaching students to be deeply rooted and radically adaptive at the same time.”The Mesa and the Machine — Design Philosophy
Student Outcomes
What students walk away with
- AI orchestration fluency The ability to evaluate, combine, and direct multiple AI tools toward complex goals — not just chat with a bot, but orchestrate systems.
- A professional portfolio of things they built Curated artifacts from every course: bias audits, community prototypes, creative works, and a public capstone project addressing a real NM challenge.
- Human skills that compound Three years of practiced ethical reasoning, creative problem-solving, community engagement, and collaborative leadership — the hardest capabilities to automate and the most valuable to employers.
- The ability to learn what doesn’t exist yet Metalearning practice throughout the pathway: approaching unfamiliar domains, evaluating new tools, adapting as technology evolves.
- 80+ hours of real work experience Structured internship with a New Mexico employer — from national labs to farms to art galleries. Plus stackable credentials and SFCC college credit potential.
Lowest-Risk Entry Point
Start with a summer workshop
Not ready to launch a full pathway? Start with the 5-day summer workshop. It introduces the same four pillars in compressed form: students learn how AI works, practice judgment and creativity, adapt quickly across unfamiliar tools, and build public-facing work — all in one week. It gives schools a visible, community-friendly way to test demand, recruit students, and demonstrate what AI education actually looks like.
Demystify AI through hands-on stations. Train classifiers, interrogate chatbots, create AI self-portraits of future New Mexico.
Train classifiers with local data, run bias labs on image generators, encounter deepfakes. Build a "Fix the Bias" campaign.
Visual storytelling, narrative co-writing, AI music. Create "Postcards from Future NM" and a collaborative digital mural.
Case studies on water, wildfire, healthcare, language. Guest speaker from NM tech/research. Launch culminating projects.
Finalize "AI for Good in NM" projects. Public showcase for families, SFCC faculty, industry partners. Pathway enrollment info.
- Low-risk pilot before full implementation
- Student recruitment tool for the full pathway
- Family and community engagement moment
- Early proof point for district and state stakeholders
- Professional development for staff
- Functions as a smart first step, not a side event
The Program of Study
A practical way to launch AI education in high school
This is not a full computer science rebuild. It is a 3-course CTE pathway where the same four pillars deepen over time: Course 1 builds literacy and confidence, Course 2 develops orchestration and ethical judgment, and Course 3 applies all four in real workplaces and public-facing projects. Schools can adopt in phases.
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Unit 1 — Weeks 1–3
What Is AI?
Defining AI, brief history, AI in daily life, the hype cycle. Unplugged sorting games and Turing tests. "AI Audit" of students' own tech use.
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Unit 2 — Weeks 4–6
How AI Sees the World — Perception
Sensors, computer vision, speech recognition, NLP basics. Train image/sound classifiers with Teachable Machine. NM connection: LANL remote sensing.
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Unit 3 — Weeks 7–9
How AI Thinks — Representation & Reasoning
Data foundations, decision trees, knowledge graphs, recommendation systems, intro to neural networks. NM connection: Sandia decision-support systems.
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Unit 4 — Weeks 10–12
How AI Learns — Machine Learning
Supervised/unsupervised/reinforcement learning, generative AI basics, training data supply chain. NM connection: agricultural AI in the Rio Grande valley.
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Unit 5 — Weeks 13–15
AI, Bias & Society
Algorithmic bias, Indigenous data sovereignty, surveillance and privacy, environmental cost of AI, regulation. Bias Audit project and Community Perspectives Panel.
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Unit 6 — Weeks 16–18
AI Futures — My Voice, My Community
AI workforce landscape, NM AI careers, capstone communication project for a public audience. Portfolio assembly and pathway planning.
Tools: Google Teachable Machine, ChatGPT Education, Hugging Face Spaces, TensorFlow Playground, Canva, Google Sites
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Unit 1 — Weeks 1–3
Power User — Advanced AI Interaction
Prompt engineering, multi-modal AI, output evaluation, academic integrity. Compare ChatGPT, Gemini, Claude, and open-source models.
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Unit 2 — Weeks 4–6
Ethics Lab — Frameworks for Hard Questions
Consequentialism, deontology, virtue ethics, care ethics, Indigenous ethics. FATE framework. Deep case studies including NM-specific AI dilemmas.
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Unit 3 — Weeks 7–10
AI Across Domains — Applied Intelligence
Healthcare, environment, creative arts, journalism, education, government, business. Domain deep dives with NM industry connections.
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Unit 4 — Weeks 11–15
Design Thinking + AI — Community Solutions
5-week PBL: identify a real NM community problem, conduct empathy interviews, design an AI-informed solution, present to community panel.
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Unit 5 — Weeks 16–18
Portfolio & Professional Readiness
Digital portfolio curation, resume writing, mock professional interviews, internship preparation. Microsoft AI-900 certification alignment.
Additional tools: Perplexity AI, Runway ML, Suno AI, NotebookLM, Figma, Miro, Kialo, Google Colab
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Unit 1 — Weeks 1–3
Professional Launch
Workplace expectations, internship orientation, professional communication, workplace AI audit, capstone topic exploration and proposal.
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Unit 2 — Weeks 4–12
Internship Immersion + Capstone Development
Minimum 80 hours on-site/remote/hybrid. Weekly classroom seminar for reflection, capstone workshops, guest speakers, advanced AI topics. Supervisor evaluations at weeks 6 and 12.
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Unit 3 — Weeks 13–18
Capstone Completion & Public Showcase
Intensive capstone production, peer review, comprehensive portfolio assembly, public presentation to industry partners, SFCC faculty, families, and community. Pathway exit interview.
Credentials earned: AI Capstone Micro-Credential, AI Literacy Professional Certificate (TMP/SFCC co-issued), Microsoft AI-900, CompTIA ITF+
Program at a glance
Implementation
What it takes to launch
School leaders need to know whether a new program is realistic. This one is built to be. Schools can start with a workshop, a single-course pilot, or a phased multi-year rollout.
- 1 lead CTE instructor with AI literacy professional development
- Existing Chromebooks or laptops — all tools are browser-based
- Teacher-managed AI tools with documented parental consent process
- Pathway or pilot timeline — start with workshop, Course 1, or full sequence
- Local advisory development with industry and postsecondary partners over time
Recommended timeline
- Spring 2026 Finalize curriculum, gain NMPED approval, begin employer recruitment
- Fall 2026 Launch Course 1 pilot with first cohort (25–30 students)
- Spring 2027 Launch Course 2; refine Course 1 based on pilot data
- Fall 2027 Launch Course 3 capstone/internship; first full-pathway cohort
- 2028–29 Full operation, first graduates, replication package for other NM districts
Funding Fit
How schools can fund it
This pathway is built to align with the structures schools already use to launch and sustain CTE programs. It does not require new funding streams.
- Perkins V for program development, PD, devices, certifications, and WBL coordination
- Existing CTE staffing and scheduling structures
- Summer workshop as entry point for early recruitment and pilot validation
1S1 Graduation Rate • 2S1 Academic Proficiency • 3S1 CTE Concentrator Proficiency • 4S1 Non-Traditional Participation • 5S1 Program Completion • 5S2 Postsecondary Placement
NMAC 6.29.3 alignment: Programs of Study, Curriculum & Instruction, Work-Based Learning, Student Leadership, Assessment, Equity & Access, Industry Partnerships, Advisory Committee
Funding references describe alignment and fit, not guaranteed funding. Consult your district CTE coordinator for specific Perkins eligibility.
Institutional Proof
Built for credibility from day one
This pathway is not a concept — it is a fully designed program of study with institutional foundations already in place.
Common Questions
What decision-makers ask first
No. The model is built around literacy, ethics, and practical career relevance — not trend-chasing. It gives schools a structured response to technology students are already using. The curriculum is grounded in established frameworks (AI4K12, ISTE, UNESCO) and designed for long-term CTE viability, not a one-year experiment.
No. This pathway is designed for CTE adoption, not a full CS rebuild. It sits within the Information Technology career cluster and requires one CTE instructor with AI literacy professional development. No coding is taught — this is AI literacy, not software engineering.
No. The entry point is open-access and built for broad participation. Course 1 requires zero prerequisites beyond basic digital literacy. Students who can use a web browser and create documents are ready to begin.
Yes. The entire tool stack is browser-based and Chromebook-compatible. Google Teachable Machine, ChatGPT Education, Canva, Google Workspace — all free or low-cost, all running in a browser. No specialized hardware, no new lab setups.
The model is structured around teacher-managed accounts, documented parental consent, no student PII in AI tools, content filtering on all devices, and a maintained tool compliance matrix. All AI interactions happen through education-licensed accounts under teacher oversight. Designed to support district privacy and compliance review processes.
Start with the 5-day summer workshop or a Course 1 pilot. The model is intentionally phased. Many schools will begin with the workshop as a recruitment and proof-of-concept event, then add Course 1, then build the full pathway over 2–3 years as demand and capacity grow.
Because tool-specific training expires quickly. The durable value is not memorizing one platform’s interface, but learning how to evaluate tools, direct them well, exercise judgment where automation falls short, keep learning as systems change, and build work that matters in the real world. Those four capacities stay useful even as specific products come and go.
This is not just content. It is a complete pathway strategy: implementation roadmap, funding logic, local NM relevance, industry-recognized credentials, 80+ hours of work-based learning, community engagement, and a replicable model for adoption. Generic AI curricula give you lessons. This gives you a fundable, defensible program of study.
Explore whether this pathway fits your school, district, or region.
Start with a planning call, a workshop, or a pilot-year conversation. We’ll walk through whether this four-pillar model fits your students, your staffing reality, and your CTE goals — then map the most practical launch path.
Ideal for principals, district CTE leaders, early college partners, and state stakeholders evaluating future-ready CTE options for New Mexico students.
Questions? Reach us at iragreenberg@gogentic.ai