Agentic AI for Teams

This framework is for delivery leaders and engineering organisations navigating the adoption of Agentic AI. It treats adoption as an organisational-capability question rather than a tooling question, grounded in XP practices, continuous delivery, spec-driven development, Team Topologies, and organisational behaviour theory.

The framework is structured in nine parts:

1. The Core Thesis - why AI is an accelerant, not a transformation tool.
2. Scoping the Problem - the three types of Agentic AI and the tooling-adoption misconception.
3. Maturity Models - individual stages, team modes and practices, and organisational readiness, with Theory of Constraints as the mechanism behind the critical stall and an explicit bounding relationship between team capability and organisational infrastructure.
4. The Adoption Sequence - clarify, harden, ease, accelerate, plus a remediation sequence for post-chaos recovery.
5. Role Positions - product, testing, design, learning, with spec-driven development as the unifying frame.
6. The Management Question - Theory X/Y as a forcing function; governance requires engineering foundations.
7. Six Principles for Adoption - constraint, interfaces, flow, sensing, decisions, experiments.
8. Open Questions - team topology, tacit knowledge, measurement, and board-level risk communication.
9. Acknowledgements and References.

Elements of the framework are hypotheses rather than proven positions. They are marked as such throughout.

The Artefacts section contains the operational tools that put the framework into action: the Underwriting Pack for board-facing risk communication, the Recovery Playbook for engagements that begin after adoption has already gone wrong, and further artefacts as they develop.

Licensed under CC BY-NC-SA 4.0.