The LegacyForward Framework — Revised

Most enterprise AI initiatives fail for the same five reasons. LegacyForward.ai is a practitioner framework built to break that pattern — three pillars that address each failure mode directly, in the environment enterprises actually operate in.

The core question every AI initiative must answer before a dollar is spent — and the transformation-versus-automation distinction that most organizations get wrong.

The three-stage framework for evaluating, validating, and tracking value — and the anti-patterns that destroy AI portfolios before anyone notices.

Why Agile breaks for AI — and the five-phase delivery methodology built for systems whose outputs cannot be predicted with certainty.

The five delivery anti-patterns that cause AI systems to fail in production — and the key questions to ask at every phase gate before it is too late.

Five architectural patterns for deploying AI alongside the enterprise systems that will not be replaced — starting from the premise that most AI strategies ignore.

The data challenges endemic to legacy environments and the anti-patterns that cause AI integration to fail in production even when the coexistence pattern was chosen correctly.

How Signal Capture, Grounded Delivery, and Legacy Coexistence form a closed feedback loop — and the six principles that underpin everything.

The LegacyForward.ai framework at a glance — summary tables for Signal Capture, Grounded Delivery, Legacy Coexistence, and Core Principles.