Core vs. Context

In the AI Story

The framework's power lies in its prescriptive clarity. Core work deserves maximum investment, ownership, and strategic attention. Context work should be minimized, automated, or outsourced — not because it is unimportant but because it does not differentiate. Moore's consulting engagements have consistently shown that companies underperform because they confuse the two, treating context work as core (defending legacy processes that no longer differentiate) or core work as context (outsourcing the capabilities on which future competitiveness depends).

In the AI era, the reclassification is dramatic. For a software company, writing code was core when writing code was hard — when the ability to produce functional software at scale was a competitive advantage. When AI writes code, the advantage evaporates. Code becomes context. Core migrates to product vision, architectural judgment, and user insight — the capacities that determine what gets built. For a law firm, legal research was core when research required expertise and patience. When AI performs legal research, research becomes context. Core migrates to legal strategy, client counsel, and the judgment connecting legal knowledge to human situations.

The reclassification is not optional and is not symmetric. Companies that recognize the shift early can redirect investment toward the new core while automating the old core as context. Companies that do not recognize the shift continue investing in what has become context, which means they are spending their capital to defend commoditized capabilities while their competitors invest in what now differentiates. The Software Death Cross of 2026 was in part a market recognition that many SaaS companies had not reclassified — they were still treating code and product features as core when the core had already migrated to the ecosystem and data layers.

The Geoffrey Moore — On AI volume argues that the core-versus-context reclassification extends to individual careers as well as corporate strategy. The professional whose identity was built on executing a specific craft must recognize that the craft is migrating from core (what I am paid for) to context (what AI now does). The new core — judgment, domain knowledge, client relationship, strategic direction — was always more valuable than the execution layer but was buried under it. The reclassification is painful because it demands reconstructing professional identity around what was never visible on the surface.

Origin

Moore developed core versus context in Living on the Fault Line (2000) as a framework for executive decision-making about resource allocation during technology transitions. The book was written during the late-1990s dot-com era when traditional companies faced disruption from internet-native competitors.

Key Ideas

Core differentiates, context qualifies. Core is the capability customers choose you for; context is everything else you must do to compete.

Invest in core, automate context. The strategic prescription is ruthless prioritization.

General-purpose technologies reclassify both. AI does not just change capabilities — it changes what counts as core and what counts as context.

Companies that don't reclassify defend commoditized advantages. Investing in yesterday's core while competitors invest in tomorrow's is how incumbents lose.

The reclassification applies to careers. Professional identities built on execution must reconstruct around judgment as AI commoditizes execution.