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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.

...business (high / medium / low). Identify conflicts between high-priority attributes. Make explicit trade-offs. Document the priorities and rationale. The -ility prioritisation matrix: Quality Attribute...

1 DayIntensive

SA · EARoles

Architecture Quality Attributes Non Functional Requirements Design Tactics View Details

AI Implementation & Technical Architecture

Intermediate to Advanced5-7 hoursAI architecture blueprint + MLOps framework + deployment playbook

Turning AI prototypes into reliable, scalable production systems. MLOps, model serving, RAG architecture, monitoring, and the engineering discipline that most AI projects are missing.

...compute, high-bandwidth networking, large storage, and specialised software stacks. Choice Options Trade-offs Cloud vs on-premise AWS, GCP, Azure vs own hardware Flexibility vs control, OpEx vs CapEx...

2 DaysIntensive

ArchitectureBlueprint

AI Architecture MLOps Model Deployment AI Infrastructure Production AI View Details

Data and AI

Intermediate4-6 hoursData readiness assessment + governance framework + pipeline blueprint

The data foundations that make AI work. Data quality, governance, architecture, pipelines, and the GenAI shift from training to retrieval. Most AI failures are data failures — learn the patterns and prevent them.

...that's been happening for months: should we fine-tune or should we use RAG? After walking through the trade-offs — data freshness, cost, complexity, use case fit — the answer is usually clear. And when it's...

1.5 DaysIntensive

Data ReadinessAssessment

Data Quality Data Governance Data Architecture Feature Engineering Data Pipelines RAG Vector Databases GenAI Data AI Fluency View Details

Future of AI

Intermediate to Senior Leaders3-4 hoursAI horizon scan + strategic implications analysis + preparation roadmap

What's coming in AI — multimodal models, on-device AI, open-source momentum, protocols, regulation, and the shift to AI-native organisations. See around the corner without falling for hype.

...fits. When open-source models have been evaluated against their current closed models — they know the trade-offs. When regulatory preparation is underway — AI inventory, risk classification, documentation....

Half DayIntensive

Horizon ScanDeliverable

Future of AI AI Trends Multimodal AI AI Regulation Emerging Technology View Details

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