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What Execution Skills Should Children Learn for the AI Future

Purpose

Many parents focus on academic achievement: good grades, good schools, good credentials.

But in the AI era, “get good grades, get a stable job” is becoming less reliable. AI automates routine cognitive work. What remains valuable are skills that create tangible outcomes.

I found a framework for execution skills - abilities to make things happen. These skills create independence regardless of employment status.

The Problem with Traditional Focus

Traditional education prepares children for employment in existing organizations:

Traditional path
Study hard → Get credentials → Apply for jobs → Work for someone

This path is shrinking. AI handles more tasks each year. Job security is eroding.

What children need instead is the ability to create value directly:

New path
Develop skills → Build something → Create opportunities → Make your own path

Five Execution Skills

Here’s the framework:

AI Era Execution Skills
┌─────────────────────────────────────────────────────────┐
│ AI Era Execution Skills ("做得出") │
├─────────────────────────────────────────────────────────┤
│ 1. Health → Maintain your body, understand │
│ medical knowledge │
│ 2. Software → Go from idea to working product │
│ 3. Engineering → Turn concepts into physical reality │
│ 4. Leadership → Build and lead organizations │
│ 5. Citizenship → Navigate legal and social systems │
└─────────────────────────────────────────────────────────┘

1. Health Maintenance

This is foundational. Everything else depends on having a functional body and mind.

What it means:

  • Understanding your own body (what’s normal, what’s not)
  • Basic medical knowledge (when to seek help, what questions to ask)
  • Sustainable health habits (sleep, exercise, nutrition)
  • Mental health awareness (stress management, recognizing problems)

Why it matters: AI cannot manage your health for you. Medical AI can assist with diagnosis and treatment. But understanding your own body, making lifestyle choices, and advocating for yourself in medical situations - these remain human responsibilities.

2. Software Development

This doesn’t mean everyone becomes a programmer. It means understanding how to turn ideas into digital products.

Progression path:

Software Development Learning Path
Level 1: No-code tools → Build simple apps without coding
Level 2: Scripting → Automate tasks with code
Level 3: Full development → Build applications with frameworks
Level 4: Deployment → Ship and maintain software

Why it matters: Software increasingly defines how value is created. Even non-programmers benefit from understanding how digital products are built. This skill lets you prototype ideas, automate your work, and understand the technology that shapes modern life.

3. Engineering Mindset

This is about making physical things - from furniture to products to infrastructure.

What it includes:

  • Design thinking (understanding requirements, constraints)
  • Material knowledge (what properties, what costs)
  • Manufacturing processes (how things get made at scale)
  • Quality and safety considerations

Why it matters: AI can generate designs. But physical production still requires human oversight. Understanding materials, processes, and tradeoffs remains valuable whether you’re making something yourself or working with manufacturers.

4. Organizational Leadership

This means creating, joining, and leading groups - not just following.

What it includes:

  • Starting projects and recruiting people
  • Making decisions under uncertainty
  • Managing conflict and disagreement
  • Building systems that work without you

Why it matters: AI cannot lead organizations. Leadership requires understanding human motivation, navigating uncertainty, and making judgment calls. These are permanent human skills.

5. Social Participation

This is about understanding how government, law, and public systems work.

What it includes:

  • Knowing your rights and how to exercise them
  • Understanding legal processes (contracts, disputes)
  • Navigating government services
  • Participating in civic processes

Why it matters: These systems are human-designed and human-operated. Understanding them gives you options. Not understanding them leaves you vulnerable.

Comparison: Traditional vs Execution Skills

Traditional FocusExecution Focus
Academic credentialsPractical capabilities
Preparation for employmentAbility to create opportunities
Theoretical knowledgeHands-on ability
Following instructionsBuilding and leading
Job securitySelf-reliance

Both can coexist. But traditional education already covers the first column. Parents need to add the second column themselves.

Why These Skills Resist Automation

Why AI Struggles with These Skills
┌────────────────────┬─────────────────────────────────┐
│ Skill │ Why AI Struggles │
├────────────────────┼─────────────────────────────────┤
│ Health │ Bodies vary, symptoms are │
│ │ subjective, judgment required │
├────────────────────┼─────────────────────────────────┤
│ Software │ AI writes code, humans must │
│ │ define problems and judge value │
├────────────────────┼─────────────────────────────────┤
│ Engineering │ Physical constraints, safety, │
│ │ material properties need humans │
├────────────────────┼─────────────────────────────────┤
│ Leadership │ Human motivation, uncertainty, │
│ │ judgment calls remain human │
├────────────────────┼─────────────────────────────────┤
│ Citizenship │ Human systems need human │
│ │ navigation and advocacy │
└────────────────────┴─────────────────────────────────┘

The pattern: AI processes information. Humans must still gather information, make judgments, and take action in the physical world.

Common Mistakes

Mistake 1: Treating health as secondary

Academic pressure often sacrifices sleep, exercise, and mental health. But health is foundational. Without it, other skills become irrelevant.

Mistake 2: Ignoring practical skills

Parents sometimes view hands-on skills as “less than” intellectual pursuits. But in the AI era, practical capability may matter more than academic achievement.

Mistake 3: Assuming skills develop later

“I’ll let them be a kid first.” But these skills take years to develop. Starting early with age-appropriate versions builds foundations.

Mistake 4: Not providing building opportunities

Children need chances to actually build things - software, physical projects, organizations. Reading about skills is not the same as practicing them.

Practical Approach

Start with what’s accessible:

Age-Appropriate Skill Development
Age 5-10: Health habits, simple building projects, family
projects, understanding basic rules and systems
Age 11-15: Basic coding, hands-on making, team projects,
understanding how organizations work
Age 16-18: Software development, real projects, leadership
roles, navigating real systems (applications,
permissions, processes)

The key is providing opportunities, not adding more “subjects.” Real projects teach better than lessons.

Summary

In this post, I showed five execution skills for the AI era: health maintenance, software development, engineering mindset, organizational leadership, and social participation. The key point is these are “hard skills” that create independence - the ability to build your own opportunities rather than waiting for employment.

Traditional education focuses on credentials for existing jobs. Parents need to supplement with skills that create value directly.

Final Words + More Resources

My intention with this article was to help others share my knowledge and experience. If you want to contact me, you can contact by email: Email me

Here are also the most important links from this article along with some further resources that will help you in this scope:

Oh, and if you found these resources useful, don’t forget to support me by starring the repo on GitHub!

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