The ability to understand, evaluate, supervise, and responsibly deploy AI systems.
AI literacy is not education — it's decision readiness. Forget generic AI courses. This is for builders and decision-makers who need real skills.
Different audiences, different needs. Same goal: competent AI decision-making.
For engineers, technical founders, and system designers who build with AI. Prompting is NOT the focus.
Understanding what AI can and cannot do. Failure modes, edge cases, and reliability boundaries.
How to evaluate AI outputs beyond accuracy. Building test suites for non-deterministic systems.
Identifying and mitigating biases. Post-incident analysis for AI-related failures.
Understanding the economics of AI. When to use expensive models vs. cheap ones.
Designing systems where humans can intervene. Escalation triggers and override mechanisms.
Recognizing when traditional approaches are better. Avoiding AI theater.
Audience: Engineers, Technical Founders, System Designers
For founders, product leaders, and operations/strategy folks who make decisions about AI. Non-technical, no math required.
Understanding organizational risks of AI adoption. Security, reliability, and reputation concerns.
Cutting through marketing claims. What questions to ask. Red flags to watch for.
Policies, oversight, and accountability structures for AI systems in your organization.
Honest assessment of AI value. Hidden costs. When hype exceeds reality.
Assessing if your team is ready for AI adoption. Skills gaps and training needs.
What to ask your technical team. Understanding their answers without being an expert.
Audience: Founders, Product Leaders, Operations & Strategy
Open, practical materials that anyone can use.
Complete course outlines and learning paths for both tracks.
Practical tools for evaluation, decision-making, and implementation.
Focused documents on specific topics. No fluff, just actionable insights.
Reference implementations showing AI literacy principles in practice.
AI literacy isn't about using AI tools. It's about knowing when to use them, how to evaluate them, and when to walk away.