Edison AI Academy · Program OverviewAI ASSOCIATE ARCHITECT

AI Associate Architect

Design AI systems, workflows, and product concepts with technical depth.

A structured program for students ready to design AI-powered systems, workflows, and product prototypes with greater technical and strategic depth.

Age range
16–22
Duration
30 weeks
Format
Hybrid
Level
Advanced
Cohort
6–10 students
Outcome
Shipped AI system + capstone
Program overview

Systems, automation, and technical implementation.

A structured program for students ready to design AI-powered systems, workflows, and product prototypes with greater technical and strategic depth.

  • What this program is

    Systems, automation, and technical implementation.

  • Who it is for

    Students who want to move from using AI tools to designing AI systems.

  • What students build

    Shipped AI system with technical defence

  • What students learn

    Students architect end-to-end AI systems with mentor sponsorship, design agent workflows, and ship a shipped capstone that operates in the real world.

  • How students are taught

    Small cohorts of 6–10 students, mentor ratio 1 mentor : 5 students. Edison runs on case-based learning, rotating studio roles, prototype-first modules, and public showcase to external panel.

  • Final outcome

    Shipped AI system + capstone

Every Edison program runs on the same five-mode cycle — Inquiry → Explore → Build → Critique → Exhibit — with depth and autonomy calibrated to the level. AI Associate Architect is calibrated for the advanced stage.

Students are mentored in small cohorts, defend their work in studio critique, and exit each module with a portfolio-ready artefact they can demonstrate, explain, and improve.

The Edison Learning Engine

How a program assembles into capability.

Edison programs are not a sequence of lessons. They are a learning engine — six parts that fit together to produce thinkers who can build with AI, defend their work, and lead.

  1. 01

    Curiosity Core

    Students begin with questions, not templates. They learn to investigate problems before reaching for tools — the genuine intellectual engine of the program.

  2. 02

    AI Fluency Layer

    Students learn how to use AI systems as thinking partners, research assistants, and creative collaborators — across prompts, models, tools, and workflows.

  3. 03

    Builder Studio

    Students move from ideas into prototypes — turning abstract concepts into tangible AI-powered outputs through structured, hands-on experimentation.

  4. 04

    Systems Thinking Ring

    Students learn to see the whole system: users, constraints, incentives, workflows, ethics, and impact — the connective tissue that turns parts into outcomes.

  5. 05

    Communication Lens

    Students learn to present their thinking clearly, explain how their solution works, defend their decisions, and refine in response to critique.

  6. 06

    Final Prototype Engine

    Every module ends with a working prototype that students can demonstrate, explain, and improve — the assembled output of the entire learning engine.

Course Content

The learning pathway, module by module.

Each module builds on the last. Students complete short cycles of inquiry, build, and critique, ending with a final showcase artefact.

  1. M01

    Module 01

    Systems & Automation

    Architect end-to-end systems with AI in the loop.

  2. M02

    Module 02

    Agent Patterns

    Tool use, planning, and the limits of current agents.

  3. M03

    Module 03

    Engineering Practice

    Version control, evaluation, and reliability.

  4. M04

    Module 04

    Mentor Studio

    1:1 mentor sessions with industry advisors.

  5. M05

    Module 05

    Capstone Build

    An ambitious, public-facing system shipped end-to-end.

Tool ecosystem

Students learn with the tools modern builders actually use.

The AI Associate Architect toolkit is curated to match the depth and ambition of this program. Students learn to choose, combine, and switch between tools — not memorise a single platform.

Category

AI Engineering

  • ChatGPT
  • Claude
  • Cursor

Category

Prototyping & Deployment

  • Lovable
  • Replit
  • GitHub
  • Vercel

Category

Data & Systems

  • Airtable
  • n8n
  • Make

Tools evolve. Edison teaches the durable thinking — choosing the right tool, combining tools well, and switching when a better tool emerges.

Your Instructor
Faculty

Edison AI Academy

Founding faculty

Students learn from instructors who combine AI fluency, curriculum design, strategy, and practical implementation experience. Edison AI Academy is built around the belief that young people do not just need to learn tools — they need to learn how to think, build, and lead with them.

Cohorts are deliberately small (6–10 students, mentor ratio 1 mentor : 5 students), so every student is known, stretched, and held to a high standard.

We teach young people how to think, build, and lead with AI — not just how to use it.

Fees and Funding

Edison AI Academy is a selective program. Fees reflect the small cohort size, mentor ratio, and the depth of the work students complete.

Flexible payment plans may be available for accepted students. Bursaries and scholarships are reviewed individually as part of the admissions conversation.

We frame this as an investment in your child's future readiness, not a transactional fee for content delivery.

Contact

Not sure if AI Associate Architect is the right fit?

Speak with Edison AI Academy about your child's goals, current skill level, and best-fit pathway. We will recommend the right program and the next available cohort.

We respond within two business days.

Next step

Find out where to begin.

We will recommend the right pathway based on individual student's unique interest, skills and ambitions.