AlphaEvolve and the Mechanics of Problem Formation: The Risk of Motivational Abyss Due to an Autocatalytic Loop of Competency Degradation

The announcement of AlphaEvolve from Google DeepMind presents an evolutionary agent for algorithm creation that combines the creative capabilities of large language models with automated evaluators. The system reduces engineering optimization time from weeks of expert work to days of automated experiments.

How does this technology change the research paradigm in modern epistemological tradition?

The traditional motivational paradigm for researchers in mathematics, physics, chemistry, biology, and engineering consisted of finding meaning in the process of discovery, in the intellectual challenge of solving complex problems, and in personally traversing the path from problem to solution.

The new paradigm promises numerous gains in the instrumental dimension while remaining silent about the existential dimension of intelligence.

There are no gains without losses. And if the mind says that gains are more important than losses, analyzing the instrumental dimension, then wisdom asks where the path of technological acquisition for humanity leads, without regard to human losses.

The list is constantly being supplemented with new losses:

• Enthusiasm in one’s own ideas, instead of curating others’
• Romance of discovery instead of the role of “systems architect”
• Feeling of uniqueness as a bearer of creative thinking
• Sense of professional identity
• Meaning in overcoming complexity
• Lived experience of thinking, its existential richness
• “Eureka moment” after a long struggle with a problem
• Intellectual triumph Having lost the values of the phenomenology of creative cognition, we may find ourselves in a motivational abyss if we don’t balance these fields in time.

Researchers would then implicitly cultivate skills of:

• Metric blindness (optimization becomes hostage to chosen criteria);
• Loss of intuitive understanding (atrophy of human understanding of “why this works”);
• Contextual fragmentation (brilliant solutions in isolation, but problematic in systemic interaction).

That is, we fall into an autocatalytic loop of competency degradation, where by delegating optimization to systems, we risk losing the ability for holistic thinking and systems analysis.

I deliberately borrowed the term “autocatalytic degradation” from chemistry, which best reflects this elegant but cruel process: degradation products become catalysts for their own decomposition.

By perfecting intelligence as a function, we impoverish intelligence as a way of human existence. To avoid destroying the process of thinking as a source of human meaning for the sake of technological growth, we need compensatory mechanisms in the future to balance the instrumental and existential dimensions.