Building the Future of Education: My Journey into Durable Skills
Our global labor market stands at a turning point. AI has shifted from novelty to necessity, fundamentally reshaping how we work.
Organizations aren't just adopting new tools, they're rethinking productivity, leadership, and the very definition of essential skills.
This transformation, and its profound human consequences, was the focus of Careers in Flux: From AI Skills to Ageless Talent, a joint broadcast this morning hosted by the Future Talent Council and Lightcast. Elena Magrini, Lightcast's Head of Global Research, presented findings from a recent report that should make every educator (and leader) sit up straight: the skills future workers must develop aren't what most of us are teaching.
The Workshop That Focused My Perspective
Elena’s message was clear and urgent: in our rapidly evolving AI-augmented world, high school and early college educators need to focus less on teaching specific technical skills that will likely quickly become obsolete, and more on cultivating "durable skills" - the human capabilities that will remain valuable regardless of technological change.
But which skills, exactly? Elena mentioned that Lightcast maintains a taxonomy of these skills, and I wanted the list. That's when my real education began - not just about durable skills, but about the learning process itself.
The Gap Between Knowing and Doing
I went to the website, which offered API (application programming interface) credentials for Lightcast's EMSI Open Skills dataset, but I'm not a programmer. I had a goal but no clear path to reach it. So I turned to my friend Claude Sonnet 4.5, and what followed was a perfect example of the kind of problem-solving we should be teaching our students and looking for in our employees.
My journey looked like this:
Starting with a clear goal: I wanted to extract a list of durable skills using the Lightcast API
Keeping my content safe: Claude explained how and where to add my credentials without exposing them to the world
Iterative troubleshooting: The first script had syntax errors. Then authentication issues. Each error became a learning opportunity.
Asking clarifying questions: "Do I need quotes around my credentials?" - Simple questions that revealed gaps in my understanding
Persistence through failure: Multiple attempts, each one getting closer
Success through collaboration: Working with AI as a learning partner, not just a tool
After several iterations and fixes, we got it working. The script successfully authenticated, identified skill types, and retrieved 475 durable skills from the database.
Here's my final working script for anyone who wants to try this themselves:
import requests
# Step 1: Authenticate and get access token
auth_url = "https://auth.emsicloud.com/connect/token"
# Replace these with your actual credentials
client_id = "YOUR_CLIENT_ID"
client_secret = "YOUR_CLIENT_SECRET"
payload = f"client_id={client_id}&client_secret={client_secret}&grant_type=client_credentials&scope=emsi_open"
headers = {"Content-Type": "application/x-www-form-urlencoded"}
auth_response = requests.post(auth_url, data=payload, headers=headers)
print("Authentication Status Code:", auth_response.status_code)
print("Authentication Response:", auth_response.json())
# Check if authentication was successful
if 'access_token' not in auth_response.json():
print("\nAuthentication failed. Please check your credentials.")
exit()
access_token = auth_response.json()['access_token']
print("\nAuthentication successful!\n")
# Step 2: Get version info to see what type IDs are available
version_url = "https://emsiservices.com/skills/versions/latest"
headers = {"Authorization": f"Bearer {access_token}"}
version_response = requests.get(version_url, headers=headers)
version_data = version_response.json()
# Print available types to identify which one is "durable"
print("Available skill types:")
for skill_type in version_data.get('attributions', {}).get('types', []):
print(f"- {skill_type.get('id')}: {skill_type.get('name')}")
# Step 3: Get durable skills (update typeIds after seeing the types above)
skills_url = "https://emsiservices.com/skills/versions/latest/skills"
params = {
"typeIds": "ST2",
"fields": "id,name,type,infoUrl"
}
skills_response = requests.get(skills_url, headers=headers, params=params)
skills_data = skills_response.json()
# Step 4: Get all durable skills (remove the [:100] limit to get all skills)
durable_skills = skills_data.get('data', [])
print(f"\n\nFound {len(durable_skills)} durable skills:")
print("="*60)
for i, skill in enumerate(durable_skills, 1):
print(f"{i}. {skill.get('name')} (ID: {skill.get('id')})")
The Irony Wasn't Lost On Me
Here I was, learning about teaching durable skills for an AI-augmented world, by using AI to augment my learning. The experience itself demonstrated exactly what the Lightcast researcher was talking about:
Problem-solving when the code didn't work
Persistence through multiple failures
Adaptability as we adjusted our approach
Critical thinking to understand error messages
Collaboration between human and AI
Learning agility to acquire new technical knowledge on the fly
These are all durable skills. The Python syntax? That's just a tool. Tomorrow's students might use entirely different tools, but they'll still need these same fundamental capabilities.
What We Discovered: 475 Durable Skills
The API returned 475 durable skills, which we then organized into 10 meaningful categories for leaders of all kinds:
1. FOUNDATIONAL LITERACIES (38 skills)
The bedrock abilities every student / productive worker needs:
Reading, Writing, Mathematics: Not just basic competency, but comprehension and application
Digital Literacy: Understanding how to navigate, evaluate, and use digital information
Information Skills: Finding, processing, organizing, and synthesizing information
Why it matters: These are the gateway skills that enable all other learning. Focus here first.
2. COGNITIVE & THINKING SKILLS (47 skills)
The mental capabilities that define human advantage:
Critical Thinking: Analysis, evaluation, logical reasoning
Creative Thinking: Innovation, imagination, ideation, improvisation
Problem Solving: Complex problem solving, troubleshooting, decision-making
Learning Mindsets: Active learning, curiosity, learning agility, willingness to learn
Why it matters: AI can process information, but humans excel at asking the right questions, making novel connections, and applying judgment in ambiguous situations. These are the critical skills to develop in high school and the first couple of years of college. OR, around the kitchen table or the community playgrounds as soon as kids are receptive.
3. INTERPERSONAL & COMMUNICATION SKILLS (62 skills)
The distinctly human abilities for connection:
Communication: Verbal, written, oral, professional
Active Listening: Understanding not just words, but meaning and emotion
Collaboration: Teamwork, cooperative learning, social collaboration
Relationship Building: Rapport, networking, trust
Cultural Competence: Empathy, intercultural communication, sensitivity
Why it matters: As automation handles routine tasks, human work increasingly involves collaboration, persuasion, and emotional intelligence. With every new employee joining the workforce, these are the skills that need nurturing.
4. PERSONAL EFFECTIVENESS & CHARACTER (89 skills)
The largest category - the internal compass guiding behavior:
Work Ethic: Reliability, accountability, integrity, professionalism
Self-Management: Discipline, time management, organization, prioritization
Adaptability: Resilience, flexibility, stress management
Initiative: Proactivity, self-motivation, goal orientation
Growth Mindset: Self-awareness, continuous improvement, openness to learning
Why it matters: Technical skills get you hired; character keeps you employed and advancing. Period.
5. LEADERSHIP & MANAGEMENT (31 skills)
Capabilities for guiding and organizing:
Leadership Styles: Adaptive, transformational, educational leadership
People Management: Coaching, mentorship, team management
Organizational Skills: Planning, coordination, project management
Influence: Motivating others, driving engagement
Why it matters: Every role involves some degree of leadership, even if it's just leading yourself or influencing peers. Team sports, clubs and community engagement work wonderfully here.
6. PROFESSIONAL & WORKPLACE SKILLS (45 skills)
Practical competencies for organizational effectiveness:
Business Fundamentals: Business acumen, financial literacy
Administrative Capabilities: Record-keeping, scheduling, documentation
Customer Service: Hospitality, relationship management
Quality & Safety: Quality assurance, ethical conduct, safety awareness
Why it matters: Understanding how organizations function makes graduates immediately valuable to employers.
7. TECHNICAL & DIGITAL TOOLS (52 skills)
Current technology proficiencies:
Software Applications: Microsoft Office, Google Suite
Communication Platforms: Email, video conferencing, collaboration tools
Devices: Computers, tablets, smartphones
Web Navigation: Browsers, internet research, web-based tools
Why it matters: While specific tools change, the ability to learn and adapt to new technologies is constant. These represent current baselines. And with AI, I’ve just built a python script. Nowhere in the list above is programming.
8. LANGUAGES (47 skills)
Multilingual capabilities from Albanian to Welsh, including:
Major world languages (Spanish, Mandarin, Arabic, French, Hindi)
Regional languages (Bengali, Tamil, Vietnamese)
Sign languages
Why it matters: In a globalized world, multilingualism opens doors and demonstrates cognitive flexibility. This is critical. We work with people all over the world, and I am personally so fortunate that the business world speaks English. I am mortified I’m not multilingual.
9. PHYSICAL & SENSORY ABILITIES (26 skills)
Bodily capabilities often overlooked in academic settings:
Physical Fitness: Stamina, strength, cardiovascular health
Motor Skills: Coordination, dexterity, fine motor control
Sensory Awareness: Visual acuity, spatial abilities
Why it matters: Many careers still require physical capabilities, and overall wellness supports cognitive performance. And feeling well boosts energy, stamina and joy. We’ll need more of those feelings every. single. day.
10. SPECIALIZED COMPETENCIES (38 skills)
Context-specific or emerging capabilities:
Education-Specific: Teaching, training, educational leadership
Innovation: Entrepreneurship, intrapreneurship
Sustainability: Environmental awareness and practices
Specialized Functions: Research, consulting, advocacy
Why it matters: These represent areas where human expertise and judgment remain essential. The characteristics for jobs we can’t even imagine yet.
The Big Picture: What Makes Skills "Durable"
Looking at this complete list, patterns emerge. Durable skills share key characteristics:
They transfer across contexts - Critical thinking works in healthcare, business, arts, or technology
They resist automation - AI struggles with empathy, ethical judgment, and creative innovation
They compound over time - Unlike technical skills that can become obsolete, these grow stronger with experience
They enable learning - They're not just skills themselves, but the foundation for acquiring new skills
Implications for Educators and Organizational Leaders
This exercise revealed something crucial: We need to shift from content delivery to capability development.
Instead of asking: "Did students learn the material?"
We should ask: "Did students develop the capacity to learn, adapt, collaborate, think critically, and solve novel problems?"
Practical Applications:
For High School Teachers:
Design projects requiring collaboration, iteration, and problem-solving
Create opportunities for students to practice giving and receiving feedback
Build in reflection on the learning process, not just the content
Emphasize ethical reasoning and decision-making in ambiguous situations
Practice adaptive thinking by presenting problems with multiple valid solutions
For Early College Instructors:
Focus assignments on synthesis and application rather than memorization
Require peer collaboration and professional communication
Build entrepreneurial thinking into projects
Integrate real-world ambiguity and constraint
Develop meta-cognitive awareness about personal learning strategies
For Educators and Organizational Leaders:
Model these skills in your own practice
Make the invisible visible - name the durable skills you're teaching
Assess process alongside product
Create safe spaces for failure and iteration - incredibly critical!
Connect technical content to these broader capabilities
A Personal Reflection
Getting this data wasn't really about Python or APIs. It was about demonstrating the very skills we need to teach:
I didn't know how to code, but I knew how to ask questions
I encountered multiple failures, but I persisted
I collaborated with AI, treating it as a learning partner
I stayed curious about both the content and the process
I adapted my approach when things didn't work
If I can model this kind of learning - comfortable with not knowing, willing to iterate, open to new tools, focused on the goal rather than the path - then maybe my students, clients and observers will develop these same durable capabilities.
The Bottom Line
The future of work isn't about competing with AI. It's about developing the distinctly human capabilities that become more valuable because of AI. Technical skills will always matter, but they're the price of entry, not the differentiator.
Our job as educators and leaders isn't to predict which technical skills will matter in 2030 or 2040. It's to develop the durable capabilities that will allow our students and employees to learn whatever skills they need, whenever they need them, for careers and challenges we can't yet imagine.
The irony? The best way to prepare students for an AI-augmented world might be to focus less on technology and more on what makes us fundamentally human: our ability to think critically, create meaningfully, connect authentically, adapt continuously, and lead ethically.
That's what these 475 skills represent. That's what research is telling us. And that's what my bumbling journey through Python syntax accidentally demonstrated.
Sometimes the process teaches more than the product. And isn't that the point?
Want to explore this yourself? You can get your own API credentials from Lightcast and run the script above. Or better yet, team up with your students or employees and let them experience the same problem-solving journey I did. That's where the real learning happens.
Resources from AIGG on your AI Journey
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