AI in practice. Evidence over hype.
Practical guidance on AI strategy, workflow design and adoption, with leadership reflections and live venture concepts.
Turning an AI Rollout into Everyday Use
Design an adoption plan around real tasks, credible champions, protected practice time and measures that show whether the new workflow helps.
Which Workflow Should You Automate First?
A practical scorecard for choosing an automation pilot, testing the business case, and separating released capacity from cash savings.
How to Deliver an AI Pilot That Can Reach Production
Plan evaluation, ownership, security, fallback and release gates early so a pilot produces evidence for a real production decision.
AI for Health Equity Requires Evidence and Oversight
Evaluate a specific barrier to care, distinguish administrative assistance from clinical decisions, and test who benefits, who is missed and who can seek help.
Building AI Capability Through Practice and Feedback
A practical approach to developing AI capability: choose a task, practise within clear limits, review the work and retain what the team learns.
DAOs in Practice: Designing Useful Governance
A DAO needs workable rules for proposals, voting, funds and execution. Start with the decisions a community needs to make, then assess which blockchain tools help.
A Practical Playbook for Change Champions
A first-month playbook for change champions, with a role charter, a support log and clear responsibilities for the sponsor and workflow owner.
Who Owns an AI Workflow?
Assign practical decision rights for an AI workflow, from business outcomes and technical changes to exceptions, incidents and benefits tracking.
Founder Priorities: The Next Useful Step
A practical approach to choosing the next founder priority, testing assumptions and giving decisions a clear owner, budget and review point.
WSKY: A Token-Based Irish Whiskey Distillery Concept
WSKY explores a token-based fundraising campaign to launch an Irish whiskey distillery. Proposed benefits include whiskey distributions and event access; any profit-sharing feature requires legal, tax and regulatory review.
Prioritizing AI Use Cases with Evidence, Cost and Risk
Compare three hypothetical AI opportunities using operational baselines, uncertainty, total cost and explicit reasons to proceed or defer.
Defining Success and Doing the Work
A personal approach to success: decide what matters, turn it into practical action, make time to learn, and take responsibility for how you work with others.
Building a Defensible Business Advantage with AI
A defensible advantage needs more than access to an AI model. Build around a specific customer outcome, reliable operations and evidence that the service is worth choosing again.
Dalycoin: A Decentralised Venture Fund Concept
Dalycoin explores a decentralised venture fund model, with proposed participant voting and clearer records of investment decisions. Its structure, rights and financial features require further definition and review.
Effective Leadership for AI Adoption
AI adoption tests leadership as much as technology. Set clear outcomes, support people through change, and make accountability fair, specific and useful.
What Is Machine Learning? A Practical Buyer’s Guide
Choose between rules, predictive models and generative AI by testing the business task, data quality, cost and consequences of failure.
Effective Decision Making in the Age of AI
Clarify who decides, which evidence matters, when human review is required and how the result will be checked. A practical guide for AI-enabled work.
Building an Enduring Company From Everyday Decisions
A reading note on Sequoia’s Elements of Enduring Companies, with practical questions about customer evidence, operating discipline and investment decisions.