Unified Framework for Scaling Generative and Agentic Systems
Three interlocking layers: Strategy, Operations, and Engineering keep AI products aligned from the first decision through the last deployment.
Each layer addresses a specific failure mode. Together they form the complete operating model for building AI products that survive contact with the real world.
What to build, whether it is worth building, and the governance constraints that must be resolved before engineering begins — from vision through scale.
Context, Action, Deliverables, Actors: the operating cadence that keeps strategy and engineering synchronized at every stage, from pilot to production.
Six evidence-driven stages from Discovery through Continuous Improvement with measurable gates, failure taxonomies, and production monitoring at every step.
The technology is not the bottleneck. The absence of a shared operating model connecting strategy, engineering, and operations is.
Seven chapters. Two live case studies. Three layers built for product managers and engineers who are ready to build AI products that last.
Intensive programs for product managers, engineers, and AI governance leads. Applied learning on real use cases using the full framework stack.
Master the 7 Phase Roadmap. Define AI products with governed scope, validated data, and explicit risk thresholds before any engineering begins.
Deploy CADA Steering across every stage. Keep strategy and engineering synchronized from pilot through production and continuous operations.
Apply AgileGenAI to real builds. Retrieval baselines, failure taxonomies, proof of concept gates, and production monitoring at every stage.
Enterprise teams, corporate workshops, and individual practitioners. Available in person or remote, with custom programs for organizations deploying AI at scale.
We respond within 24 hours to discuss format and availability.