What problem does it solve? Choosing and running the right delivery process is hard: teams cargo-cult frameworks, misread Agile success statistics, scale prematurely, and adopt AI tooling without fixing underlying flow problems. This Skill provides an evidence-grounded reference for selecting methodologies, measuring flow, scaling deliberately, and designing teams. ## Core Features & Use Cases - Methodology Selection: Uses the Cynefin framework to match work type (Clear, Complicated, Complex, Chaotic) to predictive, Agile, Kanban, or hybrid approaches, with honest assessments of Scrum, SAFe, LeSS, Nexus, Shape Up, PMBOK, and PRINCE2. - Flow Metrics & Forecasting: Covers DORA metrics, Little's Law, cycle time, throughput, WIP limits, Monte Carlo forecasting, and Flow Framework metrics for data-driven delivery management. - Team & Org Design: Applies Team Topologies, psychological safety research, OKRs, Continuous Discovery, and staged adoption roadmaps, including guidance on AI's measured impact on delivery performance. - Use Case: A VP of Engineering asks whether to adopt SAFe for 12 teams. The Skill walks through Cynefin classification, checks whether teams have stable flow and healthy DORA baselines first, and recommends starting with Nexus or LeSS before committing to full SAFe. ## Quick Start Ask the assistant to recommend a delivery methodology for your team's context, for example by describing your team size, work type, and predictability requirements.
