Executives and business leadersAI Solution Architecture for Leaders
Duration: Half day (proposed) · Format: Workshop, on site or live online
Who it is for
Technology and business sponsors approving AI solutions.
Prerequisites
None.
Learning outcomes
- Recognise the main AI solution patterns and their trade-offs
- Ask the right questions of architects and suppliers
- Set architecture principles for AI
Curriculum
- Pattern overview: prompting, retrieval, agents, fine-tuning
- Build, buy or configure
- Cost, risk and operating model
- Architecture principles
Hands-on exercise
Review a proposed AI solution using a leader's question set.
Takeaway materials
- Decision checklist for approving AI use cases
- One-page adoption roadmap template
- Board-level briefing outline
Completion outcome
ArniTech completion certificate (not a vendor certification).
Risk, compliance and security professionalsReviewing AI Solution Architectures: Data, Threat and Control Checkpoints
Duration: 1 day (proposed) · Format: Workshop with review exercises
Who it is for
Security architects, risk and compliance reviewers.
Prerequisites
Familiarity with security or architecture review.
Learning outcomes
- Review data flows, trust boundaries and third-party dependencies
- Identify AI-specific threats and matching controls
- Record decisions as audit evidence
Curriculum
- Architecture review method
- Threats: injection, leakage, misuse, drift
- Controls and compensating controls
- Records for governance and AIMS evidence
Hands-on exercise
Perform a structured review of a sample architecture and write findings.
Takeaway materials
- Control-mapping worksheet
- Review checklist for AI use cases
- Evidence examples to request from delivery teams
Completion outcome
ArniTech completion certificate (not a vendor certification).
Engineers, architects and technical teamsAI Solution Architecture Masterclass: From Use Case to Production
Duration: 3 days (proposed) · Format: Hands-on design lab, live online or on site
Who it is for
Solution architects, senior engineers and technical leads.
Prerequisites
Experience designing or building software systems and familiarity with cloud services.
Learning outcomes
- Select patterns and models against explicit quality attributes
- Design for security, evaluation, observability and cost
- Produce a reviewable reference architecture and decision records
Curriculum
- Use-case framing and quality attributes
- Model and platform selection across vendors
- Retrieval, tools and agent design
- Evaluation, guardrails and release gates
- Security, privacy and data design
- Operations, monitoring and cost
- Governance hooks and documentation
Hands-on exercise
Capstone: design and defend an architecture for a use case from your own portfolio.
Takeaway materials
- Reference architecture pack
- Architecture decision record templates
- Evaluation and release checklist
Completion outcome
ArniTech completion certificate (not a vendor certification).
Business users and functional teamsShaping AI Use Cases for Product and Business Teams
Duration: Half day (proposed) · Format: Interactive workshop
Who it is for
Product managers and functional leads defining AI work.
Prerequisites
None.
Learning outcomes
- Frame problems as feasible, valuable AI use cases
- Describe requirements architects can build from
- Anticipate risk and oversight needs early
Curriculum
- Use-case canvas
- Data, quality and feasibility questions
- Human oversight and acceptance criteria
- Handing over to architecture
Hands-on exercise
Complete a use-case canvas for a real idea and critique it in pairs.
Takeaway materials
- Prompt and task pattern library for your functions
- Do and don't guide for sensitive data
- Quick-reference card
Completion outcome
ArniTech completion certificate (not a vendor certification).
