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AI Learning Path for Technical Architects

A structured learning guide for technical architects looking to understand modern AI/ML capabilities, agentic workflows, and architecture automation patterns.

Disclaimer: This learning path been created from a learning path based on human intiution. Learning notes were fed into Claude Code, it was tasked with producing this learning path based on those notes. The path has been reviewed by a human, any fully AI generated content that has not been validated has been marked with (AI Generated). Additionally this guide contains hypotheses about how AI Agents could be used to aid Architects, these have been marked with (Hypothesis).

Who This Is For

This learning path is designed for technical leaders who need to:

  • Understand how AI can augment development workflows
  • Evaluate AI tooling and patterns for their teams
  • Design systems that integrate with AI/ML capabilities
  • Make informed build vs. buy decisions for AI-powered solutions

How to Use This Guide

Each topic includes:

  • Video resources (primary learning material)
  • Key concepts (80/20 insights)
  • How it works (technical explanations with diagrams)
  • Common approaches (trade-offs, no prescriptive "winners")
  • Try it yourself (hands-on experiments where applicable)

Capability Matrix

Topic Difficulty Key Architectural Takeaway Section
Agentic AI Evolution Introductory How LMs evolved from simple prompts → RAG → autonomous agents 01-foundations
AI Safety & Control Intermediate Understanding adversarial AI, monitoring, and the capacity gap 01-foundations
MLOps Principles Introductory ML systems are 10% ML, 90% good engineering 01-foundations
Prompt Engineering Introductory CoT, few-shot examples, systematic evaluation 02-core-patterns
RAG Architecture Intermediate Vector stores, chunking, retrieval for domain-specific knowledge 02-core-patterns
Agentic Workflows Intermediate ReAct, reflexion, tool use, multi-agent collaboration 02-core-patterns
Vibe Engineering Intermediate The paradigm shift in AI-assisted development 03-development-workflows
Spec-Driven Development Intermediate Context compression: maintaining understanding at AI generation speed 03-development-workflows
Agent Skills Framework Intermediate Anthropic Skills: procedural vs. declarative AI capabilities 03-development-workflows
Context Management Introductory Giving LMs the right context to reduce hallucinations 03-development-workflows
ADR Automation Advanced Using agent skills for architecture governance 04-governance-automation
Security Automation Advanced Threat modeling and IaC security auditing with agents 04-governance-automation
Integration Contracts Advanced API contract validation and schema governance 04-governance-automation
Architectural Drift Prevention Advanced Preventing the comprehension gap and measuring drift with ADI 04-governance-automation

Suggested Learning Paths

Path 1: Foundations First (Recommended for teams new to AI)

01-foundations/
  → agentic-ai-evolution.md
  → mlops-principles.md

02-core-patterns/
  → prompt-engineering.md
  → rag-architecture.md

03-development-workflows/
  → vibe-engineering.md
  → context-management.md

Path 2: Hands-On Development (For teams already using AI tools)

03-development-workflows/
  → vibe-engineering.md
  → agent-skills-framework.md
  → context-management.md

02-core-patterns/
  → prompt-engineering.md
  → agentic-workflows.md

Path 3: Architecture Governance (For teams experienced in leveraging AI tools)

01-foundations/
  → ai-safety-control.md

02-core-patterns/
  → agentic-workflows.md

04-governance-automation/
  → adr-automation.md
  → security-automation.md
  → integration-contracts.md

Quick Navigation

By Role

  • Enterprise Architects: Focus on 04-governance-automation
  • Solution Architects: Start with 02-core-patterns + 03-development-workflows
  • Security Architects: Prioritise ai-safety-control.md + security-automation.md
  • Team Leads: Begin with vibe-engineering.md + context-management.md

By Use Case

  • Evaluating AI tools: Start with agent-skills-framework.md + vibe-engineering.md
  • Building AI-powered systems: Focus on 02-core-patterns section
  • Governance & safety: Navigate to 01-foundations/ai-safety-control.md + 04-governance-automation
  • Team enablement: Begin with 03-development-workflows section

Resources

Contributing

This is a living learning guide. If you've discovered valuable resources or have insights to add, contributions are welcome.