Resources
In-depth guides on AI skills assessment methodology, hiring practices, integrity, and workforce benchmarking.
The 10 AI Persona Types: Understanding AI Fluency Profiles
A complete guide to AISA's 10 AI persona types — from Bystander to Oracle. What each persona means, how they differ, and what they signal about a candidate's AI fluency.
The 2026 AI Skills Report: What Assessment Data Reveals About Builder Proficiency
A framework for understanding AI proficiency patterns across roles, dimensions, and personas — what AISA's scoring system is designed to surface and why it matters for hiring and L&D.
Hiring the Next Generation: Why Traditional Tech Interviews Fail AI-Native Builders
Traditional technical interviews were designed for a world where the hard part was writing code from scratch. AI-native work demands entirely different skills — here's how to assess them.
The AI Skills Gap: How to Benchmark and Upskill Your Existing Team
A practical guide for L&D leaders: measure your team's AI proficiency with evidence-based assessment, identify dimensional gaps, and build targeted upskilling plans.
Beyond Multiple Choice: How Conversational Evidence Prevents AI Cheating
MCQ-based AI assessments are trivially gamed. AISA's dual-track conversational architecture generates unfakeable evidence of real proficiency — here's how it works.
The AISA Rubric: 5 Dimensions of AI Proficiency
A deep dive into AISA's 11-criterion scoring framework across 5 dimensions — what each measures, how scoring works, and why articulating the 'why' matters more than the 'what'.