About
This framework is written and maintained by François Lane, with contributions from Isabel Lapointe and Sébastien Grégoire.
It was born from a concrete need: transforming a traditional technology organization into an AI-native one, and documenting the path so others can use it.
What it provides
For organizations: A structured transformation path — from maturity assessment to department-specific workflow redesign. Three organizational levels, five engineering rungs, diagnostic questions to know where you stand, and concrete criteria for what "done" looks like at each stage.
For individuals: A way to understand how your role evolves and take ownership of the transition. Self-assessment tools, a guided transition process, and a framework for identifying which parts of your work are judgment (yours to keep) and which are execution (the system's job).
For managers: Tools to lead team transformation — role-by-role intent definition, adoption scoring, structured plan review, and honest guidance for when people get stuck.
Where we are
This framework is being tested and evolving with what we learn. It's designed primarily for technology companies, but the principles apply more broadly. Some parts will be confirmed by practice, others will be revised or dropped.
Acknowledgments
Major releases acknowledge the practitioners whose feedback shaped specific changes — the gaps the literature alone wouldn't catch.
- v3.0 — Vincent Lamanna (Crewdle). His detailed critique of the framework's self-assessment questionnaire surfaced the gap that v3.0 closes: the descriptions of mature AI-native work didn't match the operational reality of his organization. The five-stage operational unit, risk-graded validation gates, AI-bottleneck failure mode, recalibration vs debugging vocabulary, and AI infrastructure economics framing all triangulate against multi-source literature — but Vincent's account is what made the gap visible. See the changelog for what changed.
If you've operated an organization at high AI maturity and the framework's descriptions don't match your reality, that's exactly the kind of feedback the framework needs. Reach out.
Why it's open
The content is published openly because transparency on this type of transformation has more value than secrecy. Ideas get better when they circulate.
License
This framework is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0). You are free to share and adapt this material for any purpose, including commercial, as long as you give appropriate credit.
Author: François Lane
Contact
Questions, pushback, war stories — all welcome.
The framework is the thinking. AI Native Transformation is the platform that helps organizations apply it – with guided assessments, team-level tracking, and structured transition management.