Becoming AI-Ready: A Structured Workflow for Engineers, Scrum Masters & Product Leaders" by Mark Kendall

The article "Becoming AI-Ready: A Structured Workflow for Engineers, Scrum Masters & Product Leaders" by Mark Kendall argues that the value of delivery teams in the AI era is shifting from raw coding velocity to "structured intent." Since AI accelerates existing patterns, a weak structure leads to accelerated chaos, while a strong structure leads to accelerated excellence. To manage this, the author introduces the Intent-Driven Delivery Model (IDDM).

https://www.learnteachmaster.org/post/becoming-ai-ready-a-structured-workflow-for-engineers-scrum-masters-product-leaders

The 5 Core Elements of the IDDM

The framework suggests that before any AI tool is prompted or code is written, five elements must be defined to ensure AI acts as an amplifier rather than a source of "entropy" (disorder):

1. Goal Clarity: Moving beyond vague tasks (e.g., "Add auth") to specific outcomes (e.g., "Enable secure login using existing providers without new data stores"). This reduces rework and AI misalignment.

2. Constraint Boundaries: Explicitly defining what is Allowed (e.g., Next.js, current logging) and Not Allowed(e.g., new third-party vendors, unapproved databases). This forces the AI to be deterministic rather than probabilistic.

3. Output Structure: Defining exactly what "done" looks like (e.g., Code + Tests + API documentation) to ensure cleaner PRs and faster reviews.

4. Failure Conditions: Defining what would make the solution wrong (e.g., any new external service introduced). This allows teams to catch AI errors much earlier.

5. Observability Expectations: Ensuring every feature includes required logs, traces, and metrics. AI-generated code without visibility is considered an "invisible risk."

The "Shared Markdown Contract"

The author proposes documenting these five elements in a simple, version-controlled Markdown file (a "Feature Contract"). This serves as a "shared cognitive memory" that is easily readable by both humans and AI agents.

Impact by Role

• Engineers: Experience less rework and safer AI usage through higher predictability.

• Scrum Masters: Benefit from clearer backlog refinement and less "AI-induced scope creep."

• Product Managers: See better alignment between technical execution and product intent.

Conclusion

The article concludes that AI won't replace professionals, but unstructured workflows will be replaced by structured ones. The 30-day plan for teams to upgrade involves gradually integrating these contracts, constraints, and failure conditions into their existing sprint cycles.