Free resource
A practical guide on what actually works, including workflow architecture patterns, common pitfalls, and how to evaluate any AI implementation before you commit.
Why AI Projects Fail
The three root causes behind weak AI initiatives, the warning signs to catch early, and practical steps to avoid wasting time and budget.
Find the Right AI Use Case
How to identify concrete problems worth solving, distinguish real opportunities from AI theatre, and prioritize workflows by value, feasibility, and risk.
Workflow Design
A step-by-step method for connecting people, company knowledge, software tools, and models into a workflow that produces measurable outcomes.
Increase AI Literacy
What employees and managers need to understand about AI capabilities, limitations, verification, privacy, and productive everyday use.
Stop Slop Cannons
How to cultivate a culture of quality in your company and prevent high-volume, low-quality outputs that exceed your review capacity.
Make Adoption Stick
How to integrate AI into real operating processes through clear ownership, aligned incentives, useful interfaces, and outcome-based measurement.
Control AI Costs
How to match model capability and system complexity to task value, prevent uncontrolled usage, and evaluate AI spending against business outcomes.
Ask Better Vendor Questions
A practical checklist for investigating architecture, data access, security, reliability, latency, human escalation, pricing, and operational ownership before selecting a vendor.
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