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AI & Agentic Systems Strategy Workshop
CIO, CTO, Chief AI Officer, VP EngineeringAI operating model, governance policy, compliance roadmap, 90-day action plan

Develop a clear, governed AI and agentic systems strategy that delivers business value while managing risk, cost, and compliance.

...capability. Keep it in mind. Purpose The goal of this workshop is simple: develop a clear, governed AI and agentic systems strategy that delivers business value while managing risk, cost, and compliance. I've...

2 DaysStrategic
Operating ModelGovernance Framework
AI StrategyAgentic SystemsAI GovernanceResponsible AIView Details
Automation & Agentic Systems
Intermediate to Advanced (SA, EA, TS)6-7 hoursAutomation opportunity map + agent architecture blueprint + MCP/A2A integration guide + Agentic Risk & Cost Framework

How AI-powered architectures that plan, act, and use tools autonomously are reshaping integration and workflow — covering agentic patterns, MCP and A2A protocols, orchestration frameworks, human-in-the-loop design, guardrails, observability, and economic risk management.

Quick Navigation Start here — The evolution of automation What agentic systems are Architecture patterns for agents MCP and A2A protocols Human-in-the-loop design Governance...

1.5 DaysIntensive
CurrentSA · EA · TS
ArchitectureAI AgentsAgentic SystemsMCPA2AAutomationOrchestrationView Details
The AI Evolution Stack: How AI Systems Mature from Simple Models to Governed Platforms
The AI Evolution Stack: How AI Systems Mature from Simple Models to Governed Platforms

A structured guide explaining how AI systems evolve from simple model usage to governed platforms, and how to scale complexity without losing architectural control.

...for: Technology leaders, architects, founders scaling AI beyond experimentation Problem it solves: AI systems growing in complexity without proportional governance Key outcome: A clear evolution model ---...

Technology StrategyAi GovernanceEnterprise AiExecutionOperating ModelAiAi StrategyRead Insight
From Creation to Autonomy: Understanding Generative AI, AI Agents, and Agentic AI Through a Workplace Analogy
From Creation to Autonomy: Understanding Generative AI, AI Agents, and Agentic AI Through a Workplace Analogy

A clear executive guide explaining Generative AI, AI Agents, and Agentic AI using a corporate office analogy to prevent autonomy risks in enterprise AI.

...Architects, AI Strategy Leaders Problem it solves: Confusion between Generative AI, AI Agents, and Agentic AI leading to misplaced expectations and unmanaged risk Key outcome: Clear understanding of autonomy...

Technology StrategyAi GovernanceEnterprise AiExecutionAiAi StrategyRead Insight
Nobody Uses ADRs as an Agentic Decision Log. They Should.
Nobody Uses ADRs as an Agentic Decision Log. They Should.

Why Architectural Decision Records are the only structure most organizations already have that can govern AI agent accountability — and how to extend them into an Agentic Decision Log before the EU AI Act deadline.

...accountable when it is wrong Key outcome: A practical method to extend Architectural Decision Records into an Agentic Decision Log — creating agent accountability without building new governance infrastructure Time...

ArchitectureArchitecture GovernanceEnterprise ArchitectureAi GovernanceAi StrategyRead Insight
ADR Templates: 5 Variations for Different Contexts + Governance Automation
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.

...context is defined by four variables: Reversibility — how costly is it to undo? Blast radius — how many systems or teams are affected? Decision origin — human or agent? Velocity requirement — does this need...

Enterprise ArchitectureArchitecture Decision RecordsGovernanceAi GovernanceDocumentationRead Insight
AI Agents and Automation
Intermediate to Advanced6-8 hoursAgent use case map + architecture blueprint + governance framework

AI agents — what they are, how they work, the protocols shaping them (MCP, A2A), and the governance you need before you let one act on your behalf. The bridge between AI that talks and AI that does.

...from automation to agency Agents vs traditional automation The agent loop — how they actually work Agentic reasoning patterns Protocols — MCP and A2A Tool use — giving agents hands Memory — what agents...

2 DaysIntensive
Agent DesignWorkshop
AI AgentsAgentic AIMCPA2AMulti Agent SystemsAI OrchestrationView Details
Effective Prompt Engineering
Beginner to Advanced6-8 hoursFull prompt design framework + personal prompt library

Every major prompt engineering technique — from basic clarity to advanced agentic reasoning. Not a list of tips. A mental model you can apply to any task, any tool, any context.

...answer Step-Back — zoom out first Least-to-Most — build up from simple Advanced techniques — for production systems, agentic workflows, maximum quality Prompt Chaining — one task per prompt Generated Knowledge...

2 DaysIntensive
19 TechniquesComplete Coverage
Prompt EngineeringLLMsGenerative AIProductivityAI WorkflowsView 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.

...that bridge development and operations. AI needs MLOps. The equivalent practices for machine learning systems, extended to address the unique challenges of ML: data versioning, model versioning, experiment...

2 DaysIntensive
ArchitectureBlueprint
AI ArchitectureMLOpsModel DeploymentAI InfrastructureProduction AIView Details
Your AI Agents Are Making Architecture Decisions. Nobody Assigned Them That Role.
Your AI Agents Are Making Architecture Decisions. Nobody Assigned Them That Role.

AI agents are making micro-architecture decisions in production. No ADR recorded them. No review board approved them. No architect ever saw them. Here is the structural fix.

...Who this is for: CTOs, Enterprise Architects, Architecture Leads designing or operating AI-powered systems Problem it solves: Structural drift caused by AI agents making undocumented, unreviewed architecture...

Enterprise ArchitectureAi GovernanceAgentic AiTechnology StrategyArchitecture DecisionsRead Insight
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