The Modern Enterprise Architect's Handbook
A practical operating guide for turning enterprise strategy into coherent architecture, investable transition states, governance, and evidence.
- Enterprise architecture
- AI governance
- Transformation
Insights
Connected thinking for consequential systems, with practical field guides and dated briefs across enterprise architecture, cyber risk, AI governance, agentic systems, and resilience.
5 field guides · 27 insight briefs
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Showing all 32 insights.
A practical operating guide for turning enterprise strategy into coherent architecture, investable transition states, governance, and evidence.
A field guide to deciding when graph-enhanced retrieval is worth the extra machinery and how to pilot it safely.
A practical decision guide for determining when graph retrieval solves a real query-shape problem that vector search cannot.
The spine metaphor explains the shift from AI systems that generate answers to agentic systems that carry intention into consequential action.
The article argues that the durable enterprise advantage in agentic AI sits in the harness around the foundation model rather than in the model alone.
Retrieval-augmented generation still serves search-shaped work, but agents need governed context across tools, permissions, workflows, memory, and state.
The article uses HBR and medical-query research to argue that LLMs should not be treated as strategists or oracles.
The article argues AI is shifting from brute-force scaling toward algorithmic efficiency as training data and hardware scaling encounter limits.
AI coding agents can leak secrets when shell output containing credentials enters the conversation context sent to a model.
A bridge-building metaphor for invisible engineering work: guidance, quality gates, controls, documentation, and structural decisions.
The article argues that low-level automation skills are being commoditized as AI systems make tool operation and technical integration easier.
What 3 a.m. crisis management reveals about operational resilience, decision authority, recovery evidence, communication, and real readiness.
The article explores AI as a partner for creativity, cybersecurity work, personal development, mentorship, pattern recognition, and collective intelligence.
Solution architects are often miscast as pre-sales engineers despite working at the intersection of business strategy, technology, and delivery.
Why GenAI pilots fail when designed for demos instead of operations, and how to connect use cases to workflows, controls, evidence, and measurable value.
The article argues that complex LLM work has moved from single "magic prompts" to chained, tool-using, validated workflows.
AI augmentation is more than prompts. The article presents context engineering as the discipline that makes effective human-AI work possible.
Canada's AI policy moment shifts from stalled legislation toward parallel investment in compute infrastructure, adoption, and stronger governance.
What yottabyte-scale data growth means for architecture, infrastructure, governance, and decisions leaders must make before capacity becomes critical.
The article synthesizes five recent AI-security sources from IBM X-Force, Nature/Scientific Reports, F5, Darktrace, and Google DeepMind.
What machine-to-machine communication, autonomy, and public-sector adoption reveal about governing AI systems that interact beyond direct human supervision.
The article argues that cybersecurity risk assessment should be evidence-based rather than driven by geopolitical bias.
This opinion piece argues that frontier AI development is increasingly concentrated among a small number of corporate and government actors.
An opinion analysis of Qwen2.5-Max and what rapid model competition reveals about AI capability, market concentration, governance, and strategic dependence.
How to turn AI accountability and fairness from statements of intent into operating controls, accountable ownership, reviewable evidence, and decisions.
How collaborative intelligence changes AI from passive automation into an active partner, and what human oversight, role design, and accountability require.
How mental and physical well-being affect cybersecurity resilience, decision quality, team recovery, and performance during sustained high-pressure incidents.
The article explains how generative AI changes cybersecurity through both new defensive capabilities and new risks.
Continuous Threat Exposure Management is an ongoing risk process combining asset discovery, vulnerability assessment, threat context, and validation.
A practical approach to responsible AI in enterprise and public-sector settings, connecting governance principles to controls, accountable owners, and evidence.
How voice cloning changes impersonation and trust risk, why familiar voices no longer prove identity, and which controls reduce deepfake-enabled fraud.
This broad guide surveys AI's role in cybersecurity across defensive applications, strategy, ethics, human factors, and future outlook.