An AI strategist explains why she stopped setting New Yearâs goals
DA
3 days ago7 min read
Every January, weâre subjected to the same corporate liturgy: set ambitious goals, map the year with military precision, and commit to executing harder than before. We frame this as discipline or vision, but after years of working at the intersection of artificial intelligence, organizational strategy, and leadership, Iâve come to see it for what it often is: a ritual of pressure built on a flawed assumption.The dominant narrative suggests success springs from wanting more and pushing faster, a logic that mirrors the brute-force training of early neural networksâmore data, more parameters, more compute. Yet, just as weâve learned that smarter architectures and efficiency often outperform sheer scale in AI, I realized a parallel truth in human endeavor.Most people arenât failing due to unclear objectives; theyâre failing because their cognitive and emotional capacity is already exhausted before the year even begins. This realization, drawn from observing both algorithmic systems and the executives who deploy them, fundamentally altered my approach.I no longer begin January by asking what I want to achieve. I begin by auditing how I want to work, a subtle but profound shift from goal-first to capacity-first planning.Traditional New Year planning operates on a stable-environment fallacy, assuming predictable time, consistent energy, and controllable attentionâa model as outdated as a linear regression trying to parse todayâs multimodal AI landscape. The reality of modern leadership is a constant state of interruption: back-to-back meetings, the ceaseless ping of Slack, the quiet accretion of decision fatigue.Layer on personal responsibilities, emotional labor, and the cognitive load of navigating rapid technological change, and itâs no wonder so many meticulously crafted January plans collapse by March. We set goals in a vacuum, ignoring the operating systems required to support them, optimizing for ambition over sustainability.The result isnât a lack of discipline; itâs burnout disguised as motivation, a form of overfitting where the model performs perfectly on the training data of a idealized plan but fails catastrophically in the noisy, real-world test environment of daily life. My pivot was to replace the question, âWhat do I want to accomplish this year?â with a more computationally honest one: âWhat is my actual bandwidth?â Here, capacity isnât just calendar slots; itâs the multidimensional resource of energy, focused attention, decision bandwidth, and emotional resilience.Before setting a single goal, I now design for capacity across four vectors, much like tuning a modelâs hyperparameters. First, energy rhythms: identifying when Iâm most creative for strategic thinking versus when Iâm drained for administrative tasks, rejecting the fallacy that all hours are computationally equal.
#featured
#AI strategist
#New Year goals
#capacity planning
#leadership
#productivity
#work systems
#burnout prevention
Stay Informed. Act Smarter.
Get weekly highlights, major headlines, and expert insights â then put your knowledge to work in our live prediction markets.
Second, decision load: auditing how many low-stakes decisions could be automated, delegated, or eliminated, as each one consumes cognitive cycles that could be allocated to higher-value problems. Third, friction points: pinpointing what consistently slows progress, be it meetings without agendas or tools that donât integrate, analogous to debugging a pipelineâs bottlenecks.
Fourth, leverage: identifying where systems, technology, or team members can create multiplicative outputs without requiring linear increases in my personal input. Only after this systems audit do I consider objectives.
This approach isnât about doing less; itâs about intentional allocation, a principle core to efficient AI design. As a strategist, I constantly see organizations rush to adopt cutting-edge LLMs or agents without addressing the broken human workflows and data silos underneathâa classic case of adding a powerful new model atop a faulty infrastructure.
The same mistake plagues personal planning. Capacity-first planning forces an early confrontation with trade-offs and resource constraints.
If you intend to launch a new initiative, what existing process must be deprecated? If growth is the aim, where must complexity be reduced? This normalizes a truth rarely voiced in leadership circles: you cannot run all processes concurrently without throttling the entire system, and attempting to do so is a sign of poor architecture, not strength. The most effective leaders I know are ruthless about protecting their capacity, understanding that clarity, judgment, and strategic presence are finite and non-renewable resources in any given cycle.
Consequently, my January ritual is no longer a sprint but a systematic audit. I review what *actually* worked the previous year, not just what looked impressive on a roadmap.
I identify tasks that delivered disproportionate drain relative to their impact, applying a form of loss function analysis to my own workflow. I redesign my calendar and communication protocols before I ever draft a goal.
Some years, the resulting container is expansive; other years, itâs intentionally constrained. Both can be successful if they are honest reflections of available resources, avoiding the boom-and-bust cycles that so many mistake for ambition.
In a world defined by exponential change and constant context-switching, leaders donât need more pressure; they need better, more resilient system design. The most effective way to begin a year is not by demanding more from yourself, but by architecting systemsâboth technological and humanâthat support sustainable execution.
Design your capacity first. Let your goals follow. You may well find that you accomplish more by asking less of your overtaxed neural wetware, and more of the thoughtfully engineered systems in which it operates.
