I'm a leader and I want to evaluate and govern AI investments in my organization

From orienting on what even needs governing, to the calls that actually get argued: cost, speed, hallucination, security, and autonomy.

Basic — Get Oriented

Build Your AI Stackbeginner

Map your work onto the six jobs AI is actually good at

ML, GenAI, or Just Software?advanced

Sort a client request into classical ML, GenAI, or plain software — and decompose it when it's more than one

Advanced — Make the Call

Build vs. Buy vs. Promptadvanced

Reframe a vague "we want AI to do X" ask into a real problem statement

Reading a Vendor Demoadvanced

Recognise a demo as a cherry-picked trace, not evidence of production behaviour

The Data Readiness Auditadvanced

Audit a client's data against six readiness criteria before any model work starts

Token Economics & Cost Modelingadvanced

Turn a vendor's per-token price into a real monthly cost, not a naive multiplication

The Latency Reality Checkadvanced

Explain why prefill is fast and decode is slow, and what that means for any "sub-200ms" claim

Hallucination & Guardrailsadvanced

Name the specific reason a model hallucinated — missing grounding, missing abstention pressure, or both

Prompt Injection & Data Leakageadvanced

Tell direct prompt injection apart from indirect, and explain why retrieved content is untrusted input

Agent Blast Radiusadvanced

Tell an agent that answers apart from one that acts, and explain why "automation" hides that difference