When a Claude subscription gives anyone the ability to build something, that something loses market value. The competitive edge has shifted from producing code to grasping what users genuinely require.

Organizations adopting Claude Code, Cursor, or Copilot to accelerate output face an uncomfortable truth: when generation capacity becomes free, volume-based strategies collapse. Teams racing to ship more features through AI may inadvertently surrender the foundation of their product's worth.

Understanding what makes software valuable—and recognizing why chasing code quantity leads to failure—has become essential.

The Midas touch

Ovid's tale of King Midas of Phrygia illustrates the danger of abundance without purpose. After sheltering the satyr Silenus, Midas was granted a wish: everything he touched would become gold. He tested the power on an oak twig and a stone, delighted by the results. Nathaniel Hawthorne's 1851 retelling for children added a rose garden, where Midas turned every bloom to gold—still pleased, though his daughter Marygold grieved that the flowers no longer held their fragrance. Both versions reach the same turning point at the dinner table, where food and drink transform to gold in his hands. Only then did Midas grasp that his reward was a curse, not a blessing, and begged to be freed from it.

Many leaders who force-fed AI to developers are now coming to a realization similar to that of Midas.

Though the realization unfolds gradually, many organizations and their leadership are arriving at a comparable understanding. Evidence shows companies trimming AI budgets and restricting tool deployment.

Microsoft and Meta have reportedly reduced internal spending on Anthropic's Claude, while Uber and Accenture have imposed caps on employee AI tool expenditure. These moves suggest that return on investment may not materialize—McKinsey's 2026 research found that record AI spending has not improved earnings for 94% of enterprises—making the pattern clear.

The economics of plenty

Had Midas relied on gold's market value to sustain his lavish ten-day festivals, he would have discovered quickly that his gold held no worth. His touch would trigger hyperinflation, collapsing the price of gold. His ability would prove as useful as turning everything into ash.

In today's world, AI transforms everything it touches into a commodity. If Claude or ChatGPT can generate something, so can everyone else. They possess identical tools. Whether creating software or prose, AI-generated output carries value only marginally above the token cost. Its perceived worth becomes indistinguishable from raw material cost.

When coding appeared mysterious to most people, basic coding skill represented genuine value. Professionals could build careers by converting human requirements into executable code. This value accumulated across teams, departments, and organizations, with skilled developers trading their arcane expertise for compensation—whether the code served internal needs, customer projects, or commercial products.

If your software expresses user requirements translated into code, it's now worthless.

Software that merely encodes user specifications into functionality has become worthless. A page containing nothing beyond an AI summary holds no value, and software built by mechanically translating user requests into code occupies the same category.

How to avoid incinerating your software's value

Escape remains possible. When Midas sought relief from his curse, he washed in the Pactolus River. Our connection to the generation engine is not immutable, so our work need not inevitably turn to ash.

The solution is straightforward in concept but demanding in execution—precisely what many wish to sidestep. To shield your work from AI's destructive touch, you must deliver something beyond what an individual with their own Claude subscription could achieve.

For your work to be immune to AI's mortally ruinous touch, you need to provide something beyond what someone could achieve with their own Claude subscription.

This requires abandoning the feature-factory approach, where value derives primarily from converting "user wants" into code. Instead, software teams must cultivate profound knowledge of the jobs users perform and the obstacles they encounter, enabling the generation of novel ideas and business insights users would not independently discover.

This approach may yield something entirely different from what users requested, yet one that elegantly addresses many challenges embedded in their actual work. Merging deep domain expertise with knowledge of abstract, generalizable patterns enables delivery of genuinely exceptional software.

DORA's State of DevOps research has emphasized this requirement for user focus. This does not mean complying with every user request; it means comprehending their work and constraints so you can provide software they genuinely value. DORA's 2024 report demonstrates that this approach strengthens product performance, independent of delivery velocity.

We inhabit an era of surplus code, text, and visual content. The path forward demands not more, but better.