My brain on AI.Gemini AI for image generationThere’s an itch I can’t quite scratch, a low-humming anxiety beneath the surface of my daily work. It started subtly. I’d use an AI tool to quickly refactor some code, summarize a dense document, or brainstorm ideas. The efficiency gain was undeniable, intoxicating even. But lately, I’ve noticed a shift. I reach for these tools not just for speed, but because the cognitive path feels… easier. Too easy.It reminds me of muscle atrophy. Stop lifting weights, and your muscles weaken. Stop walking, and your endurance fades. I’m starting to fear a similar phenomenon happening in my mind. Am I exercising my critical thinking, my problem-solving abilities, my creativity muscles? Or am I letting them soften, relying on the AI to do the heavy lifting?I find myself generating answers more than truly thinking through problems. There’s a difference. Generating feels like pulling a pre-packaged meal from the freezer — convenient, fast, often looks good. Thinking feels like selecting fresh ingredients, chopping, seasoning, tasting, adjusting — a process that’s messier, slower, but ultimately builds skill and deeper understanding. I worry that by optimizing for the generated meal, I’m losing the culinary art of thought itself.What fades when I outsource my thinking?This touches something deeper than just forgetting facts or syntax that an AI can instantly recall; it feels like it affects the core processes of how I engage with complexity.First, there’s critical judgment. When an AI serves up a polished answer or a block of code, the friction I’d normally encounter — sifting through sources, weighing evidence, spotting flaws — often evaporates. I might skim, nod, and integrate. I realize now that friction was essential; it was the workout. It’s where I learned to sense bullshit, to question assumptions, to evaluate the strength of an argument or the elegance of a solution. Each time I bypass that effort, that judgment muscle gets a little less exercise. My fear is becoming a passive recipient, less able to distinguish the truly insightful from the merely plausible, or even the subtly wrong. In a world overflowing with information and generated content, exercising sound judgment feels like the bedrock skill, the one thing that truly matters. And it seems to be built through hard-won experience, not summoned on demand.Then there’s problem framing. AI tools are getting remarkably good at solving problems once they’re clearly defined. Yet, I believe true value often lies in the murky, upfront work of framing the problem correctly. Understanding the real needs, the hidden constraints, the human context, the ‘why’ behind the ‘what’. This requires nuance, empathy, and a grasp of the bigger picture — qualities that feel inherently human. If I increasingly lean on AI from the start, I risk short-circuiting this crucial diagnostic phase. I might get faster answers, but are they answers to the right questions?Synthesis and original insight also feel threatened. Effective synthesis involves more than just stitching summaries together. It’s about spotting novel connections between disparate ideas, creating something new from existing parts. AI can recombine elements from its training data in incredible ways. But genuine breakthroughs often seem to arise from lived experience, from cross-pollinating ideas from completely different fields, from intuitive leaps that defy predictable correlations. When I outsource the act of assembling ideas, I reduce the chances for those serendipitous mental collisions that spark true originality. I practice efficient recombination, perhaps at the expense of deep invention.My ability to maintain deep focus is another casualty. The temptation to ‘just ask the AI’ when I hit a tricky section of code or a difficult conceptual hurdle is immense. It offers an immediate escape hatch from the discomfort of sustained mental effort. This bypasses the very state of intense concentration — what some call ‘Deep Work’ — that’s necessary for producing high-value, hard-to-replicate results. I trade the satisfaction of wrestling through a complex problem for the quick dopamine hit of an instant solution, potentially rewiring my brain for shallower engagement over time.Finally, there’s the erosion of tacit knowledge. Some understanding isn’t written down; it’s absorbed through the pores by doing. It’s the intuitive feel for debugging a complex system, the gut sense that guides an experienced architect, the subtle understanding of team dynamics. Relying on AI to fix things or provide the path forward might solve the immediate issue, but it prevents me from accumulating that rich, hard-earned, embodied understanding that only comes through struggle and direct experience.My future thinking: partnering, not replacingI don’t intend this as a forecast of doom or a call to unplug entirely. I don’t believe human thinking is becoming obsolete. Instead, I see its highest value points shifting. I envision the future involving me working with the machine, rather than competing against it. The atrophy I fear is a real risk, but the outcome isn’t set in stone.I picture cognition like a multi-layered process. AI is rapidly automating the lower layers: pulling information, spotting basic patterns, handling routine tasks, summarizing, translating, generating standard content. So, where do I, where do we, continue to provide unique and growing value?It seems to lie in the higher-order functions:Judgment and Wisdom: As AI floods the world with content, the human ability to discern quality, truth, relevance, ethical implications, and long-term consequences becomes exponentially more valuable. This requires context, life experience, and a framework of values that models simply don’t possess. I become the curator, the editor, the conscience.Strategic Questioning and Direction Setting: AI needs goals; it needs purpose. My ability to ask insightful, penetrating questions — the questions that define the real problem, that set a meaningful direction — becomes a critical meta-skill. I shift from being an answer-finder to being a question-architect, guiding the powerful tools towards worthwhile ends.Cross-Domain Synthesis and True Creativity: While AI synthesizes within its data, I can connect ideas across completely different fields, drawing on unique experiences and intuition. This is where unexpected innovations often arise. It’s about leveraging my specific knowledge in novel combinations.Empathy and Human Connection: Understanding users, colleagues, the nuances of human interaction, the emotional landscape — these remain profoundly human strengths. Building trust, fostering collaboration, considering the human impact of technology requires sensibilities AI can only simulate.Systems Thinking and Integration: Seeing the entire ecosystem — how technical components interact with market dynamics, user behavior, and social trends — is crucial. AI might optimize a piece, but I need to ensure the whole system works, that it’s resilient, ethical, and serves its intended purpose.Knowing facts AI can retrieve instantly feels less important for my future value than the ability to apply that knowledge effectively, guided by sound judgment and clear purpose. It requires using the immense leverage AI provides without letting it dictate my intellectual agenda.Cultivating my cognitive garden: My antidotes to atrophyAvoiding this mental softening isn’t passive. It requires conscious effort, deliberate practice — tending to my mind like a garden that needs active cultivation. Here’s how I’m trying to approach it:Wielding the tool deliberately:Purposeful Use: I try to be explicit about why I’m using AI for a given task. Is it genuinely freeing me up for higher-order thinking, or am I just avoiding effort? I aim to use it for specific, well-defined tasks where it provides clear leverage, rather than as a default for all thinking.Prompting as Discipline: I’ve found that crafting a truly effective prompt forces me to clarify my own thinking first. What result do I actually need? What are the constraints? What does success look like? This process itself is a valuable cognitive exercise.Critical Review: I treat AI output as a first draft, a suggestion, a sparring partner — never the final word. I actively review, question, and refine it. This keeps my judgment muscle engaged.Embracing cognitive resistance:Manual First: For tasks involving skills I want to preserve, I often try to tackle them manually first. Write the initial outline, sketch the core logic, wrestle with the argument. Then I might bring in AI to help refine, check, or explore alternatives. I need to consciously choose the cognitive stairs sometimes, even when the elevator is available.Seeking Challenge: I try to read books and articles that stretch my understanding, engage in discussions that challenge my perspectives, and occasionally tackle problems just outside my comfort zone. This builds mental resilience.Protecting Deep Focus: I actively schedule and defend blocks of uninterrupted time for focused work. Turning off distractions and allowing myself to sink into complex problems feels essential for producing work of real depth and for maintaining my ability to concentrate.Deepening my specific knowledge:Going Deep: I focus on cultivating deep expertise in my core domains — the intricacies of Android development, system design, maybe even exploring intersections with other interests. Broad AI knowledge is becoming commoditized; deep, specific knowledge built through focused effort and experience feels far more durable and valuable.Connecting the Dots: I actively look for ways to connect ideas from different areas of my knowledge and experience. Reading widely and talking to people with different backgrounds helps spark these cross-domain insights.Elevating questions over answers:Problem Definition First: I’m trying to invest more time and mental energy upfront in deeply understanding and framing the problems I’m working on. Asking “why” multiple times, mapping the context, clarifying the true goal before seeking solutions. This feels like higher-leverage work.Interrogating the AI: When an AI provides an answer, I ask myself: What assumptions is it making? What context is it missing? How might its training data bias the result? This helps me use the tool more critically.Practicing meta-cognition:Thinking About Thinking: I try to regularly step back and reflect on how I’m using these tools and how they’re affecting my thought processes. Is this specific use case empowering me or making me intellectually lazy? Journaling or simply pausing to consider this helps.Explaining to Solidify: Trying to explain a concept clearly to someone else — without leaning on the AI — is a powerful way to test and deepen my own understanding. It forces articulation and reveals gaps.Valuing the analog and disconnected:Offline Thinking: I find immense value in stepping away from the screen. Going for walks, thinking with pen and paper, allowing my mind to wander without digital input often leads to clearer thoughts and unexpected ideas. Boredom can be surprisingly productive.Focused Reading: Engaging with physical books or long-form articles forces a type of sustained attention that feels increasingly rare and valuable.Playing the long game: My human algorithmI see this fear of skill atrophy as a protective instinct, rather than simple pessimism. It’s my mind’s way of saying, “Hey, don’t get too comfortable, don’t outsource the functions that make you fundamentally you.” AI offers staggering capabilities, unprecedented leverage. But leverage needs a firm hand and a clear mind guiding it.My goal is to integrate AI wisely and intentionally, rather than simply resisting it. It means playing the long game — focusing on the sustainable cultivation of the skills that matter most, going beyond just immediate productivity gains: judgment, creativity, critical inquiry, wisdom. These feel like core components of my own human algorithm, the one that allows me to navigate complexity, solve meaningful problems, and build things of lasting value — whether that’s robust software, strong relationships, or a thoughtful approach to the future I’m helping shape.The muscle of my mind doesn’t have to waste away. But keeping it strong in the face of these powerful new conveniences requires conscious choice and deliberate effort, every single day. The challenge lies in using the tools effectively without letting them dictate my thinking, ensuring that the ghost in the machine remains firmly human.p.s: I used AI to restructure sentences and grammar checks within this article. Only after I wrote my thoughts first.References & further: 1. Taste is your unfair advantage2. The 3-Level Prompting System That Makes AI Insanely Useful3. Mind Mapping your way to eternal sunshine….Notebook LM way!Wrestling with skill atrophy in the age of generated thought was originally published in UX Collective on Medium, where people are continuing the conversation by highlighting and responding to this story.