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Technology, Infrastructure, Cloud & Security Design

Intermediate to Advanced (SA, EA)6-8 hoursInfrastructure decision framework + cloud pattern reference + security controls map

Where abstract architecture meets physical reality — choosing the platforms, compute, networking, and security controls that make the solution work at scale.

...and lock-in FinOps Putting it all together Cheat sheet Before we start — the one thing to hold onto Architecture decisions live in the abstract until they're made real by technology choices — the platforms,...

2 DaysIntensive

PracticalSA · EA

Architecture Solution Design Cloud Infrastructure Security FinOps View Details

AI Architecture Clarity: Understanding LLM, RAG, Agents, and MCP Through the Brain Model

A clear executive guide explaining LLM, RAG, AI Agents, and MCP using the Brain model to prevent enterprise AI instability.

...simple metaphor: Brain. Memory. Hands. Control. If you understand these four, you understand modern AI architecture. LLM = The Brain An LLM is a brain. It can: Think Write Explain Summarize Reason It...

Ai Governance Execution Read Insight

ADR Templates: 5 Variations for Different Contexts + Governance Automation

One ADR template does not fit every architectural context. Five purpose-built variations — for standard decisions, agentic AI, cross-domain impact, fast delivery, and high-risk reversals — plus governance automation to make the system run without manual follow-up.

Executive Summary Who this is for: Enterprise Architects, Solution Architects, Architecture Leads, Engineering Managers Problem it solves: A single ADR template applied to every decision...

Architecture Adr Governance Read Insight

Your HCI Proof of Concept Measures the Wrong Thing.

Most organizations evaluate private cloud and HCI platforms by running a technical POC. The POC passes. The platform fails. The reason is structural — and fixable. The Platform Fitness Evaluation Model (PFEM) tells you what to measure instead.

...POC is usually infrastructure or operations. They evaluate technical capability. Nobody asks the architecture question: Does this platform fit our operating model? That question is not in the RFP. It...

Architecture Platform Engineering Governance Read Insight

Requirements, Constraints, Trade-offs & Compromise

All levels — SA, EA, TS5-6 hoursTrade-off framework + constraint register template + requirements classification guide

The art of making the best possible architectural decision given what is required, what is constrained, and what must be sacrificed.

Quick Navigation Start here — What architecture really is Functional vs non-functional requirements Constraints Competing priorities Trade-off...

1 DayIntensive

PracticeReal decisions

Architecture Foundations Requirements Trade Offs Decision Making View Details

Quality Attributes / -ilities

SA, EA — Intermediate5-6 hoursQuality attribute reference card + -ility prioritisation matrix

The non-functional characteristics that determine whether a system is truly fit for purpose — scalability, reliability, availability, performance, security, maintainability, and more.

...is truly fit for purpose — not just whether it works, but how well it works under real conditions. Architecture is driven by quality attributes more than by functional requirements. Features can be added...

1 DayIntensive

SA · EARoles

Architecture Quality Attributes Non Functional Requirements Design Tactics View Details

MCP Is Not an AI Protocol. It Is a Governance Layer.

MCP is classified as an AI integration protocol. It is actually a governance primitive — the stable interface layer that architecture fitness functions have been missing for years.

Executive Summary Who this is for: Enterprise Architects, Solution Architects, CTOs, Architecture Leads Problem it solves: Architecture fitness functions that break the moment a team changes...

Ai Governance Strategy Read Insight

AI Knowledge Systems — RAG, Search, Memory & Internal Knowledge

Intermediate4-5 hoursKnowledge system map + RAG decision framework + memory design checklist

Many useful AI systems are not smarter because the model is smarter. They are smarter because the system can retrieve, search, remember, and ground itself in the right knowledge at the right time.

...inventing what it cannot support. In other words, a lot of apparent intelligence is really good information architecture. That is why knowledge systems deserve their own training topic. They are one of the least...

1 DaySystems Thinking

Knowledge DesignPractical

RAG Search Memory Knowledge Systems Internal Knowledge View Details

Technology Leadership & Organizational Excellence

Intermediate to AdvancedLeadership roadmap and team enablement plan

Learn to lead high-performance engineering organizations with clear decision rights, distributed leadership, and AI-augmented team management for the future of work.

...Augmentation Fractional Leadership Models Team Topology and Role Clarity Final Mental Model Key Takeaways Reference Card Success Metrics Evidence from Practice Book Your Workshop 🌟 The Only Idea You Need Effective...

2 DaysWorkshop

FoundationFor all leadership roles

Leadership Organizational Design Decision Rights AI Augmented Teams View Details

AI Capabilities, Limitations & Use Cases

Beginner to Intermediate3-4 hoursTask-to-AI fit judgment + reference materials

What AI is genuinely good at, where it will let you down, and how to match the right task to the right tool. The judgment you need before you touch a prompt.

...watched senior engineers use this to understand legal clauses, lawyers use it to understand technical architecture, and ten-year-olds use it to understand why the sky is blue. The same tool, the same capability,...

Half DayIntensive

Beginner FriendlyNo math required

Generative AI AI Capabilities AI Limitations Hallucination Use Cases AI Fluency View Details

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