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Technical debt is about messy code, but cognitive debt happens when developers lose understanding of the software. AI can create code fast, but teams may struggle to know why things work or how to change them. To avoid problems, teams must slow down, share knowledge, and keep clear explanations of all changes.
Highlights
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Cognitive debt, a term gaining traction recently, instead communicates the notion that the debt compounded from going fast lives in the brains of the developers and affects their lived experiences and abilities to “go fast” or to make changes. Even if AI agents produce code that could be easy to understand, the humans involved may have simply lost the plot and may not understand what the program is supposed to do, how their intentions were implemented, or how to possibly change it.
Cómo se puede llevar este concepto a otros campos. Por ejemplo, a educación o consultoría?
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Cognitive debt is likely a much bigger threat than technical debt, as AI and agents are adopted. Peter Naur reminded us some decades ago that a program is more than its source code. Rather a program is a theory that lives in the minds of the developer(s) capturing what the program does, how developer intentions are implemented, and how the program can be changed over time. Usually this theory is not just in the minds of one developer but fragments of this theory are distributed across the minds of many, if not thousands, of other developers.
Esta idea está interesante y responde a mi pregunta del comentario anterior. Programa puede reemplazarse por proyecto (o cambiar la acepción de “Programa” a una lógica de proyecto) y aplica perfectamente. De hecho, de alguna manera presta respaldo a mi preocupación constante por cultivar un entendimiento compartido en todo el equipo de la teoría a la base del proyecto ya que, de otro modo, empiezan a construirse “piezas que no calzan” o que no están alineadas.
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But as we dug deeper, the real problem emerged: no one on the team could explain why certain design decisions had been made or how different parts of the system were supposed to work together. The code might have been messy, but the bigger issue was that the theory of the system, their shared understanding, had fragmented or disappeared entirely. They had accumulated cognitive debt faster than technical debt, and it paralyzed them.
Un ejemplo de lo que se describía en términos generales en la última cita. Me quedo con la pregunta: ¿cuáles estrategias son efectivas para cultivar el entendimiento compartido, así como también monitorear su salud e intervenir ágilmente cuando se detectan problemas?
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Teams should establish cognitive debt mitigation strategies. For example, they may wish to require that at least one human on the team fully understands each AI-generated change before it ships, document not just what changed but why, and create regular checkpoints where the team rebuilds shared understanding through code reviews, retrospectives, or knowledge-sharing sessions.
Algo similar a esto es lo que busco con la realización de actas. Permitirnos tener una fuente de verdad a la cual podamos acudir en caso de alguna duda o discrepancia. En este sentido, es importante ser explícito respecto de la necesidad de que el acta se asume validada si no recibe comentarios de una semana a otra.