AI Strategy notes
Decision frameworks for choosing AI work that is worth building, measurable, and practical for the team that has to operate it.
AI Strategy essays
The full set, newest first. Each note is written to help you make a decision rather than to recap the news.
Is Your Website Ready for AI Agents?
Can an AI assistant tell a buyer whether your business can help? Check your service facts, access rules, and enquiry process with one real question.
The Self-Improving AI Assistant: Why Memory Needs More Than Chat History
The best AI assistant will not just remember your chats. It will separate personal memory from source-backed world knowledge, then improve both over time.
AI Native Readiness: The 2026 Assessment for Companies Moving Beyond AI Tools
A practical, research-backed framework for assessing whether your company is ready to move from scattered AI usage to AI-native operating workflows.
Why the Next SaaS Product Might Not Need a UI
Agent-first software changes what founders should build: less dashboard, more context, APIs, permissions, audit trails, and workflows agents can operate.
Enterprise AI Strategy Roadmap: A Practical Playbook for Leaders
A practical enterprise AI roadmap covering readiness, data governance, shadow AI risk, KPIs, pilot selection, and production rollout.
From Idea to AI MVP: How Rapid Prototyping Actually Works
Building an AI MVP fast sounds impossible. Here's the methodology we use to go from concept to working prototype without cutting corners on quality.
Category guide
Choose the workflow before the technology
AI strategy becomes useful when it changes the order of investment. Instead of collecting a long list of ideas, a team should identify recurring work, quantify the current friction, assess the evidence and controls available, and select the smallest intervention that can prove value responsibly.
The strategy guides in this category connect readiness, workflow selection, governance, product validation, and operating change. They are designed for leaders who need a defensible first move and a decision gate—not an abstract transformation slogan or a roadmap detached from the people doing the work.
Use these articles to prepare an AI opportunity workshop, compare candidate workflows, define a pilot scorecard, or turn scattered experiments into a 30/60/90-day operating plan with owners and measurable outcomes.
Questions these guides should help answer
- Q1Which recurring workflow has a named owner and a costly, observable bottleneck?
- Q2What evidence, data access, and governance are required before testing it?
- Q3Which business metric should change if the workflow is genuinely better?
- Q4What explicit decision will be made after the first validation cycle?