By Jeff Altman, The Big Game Hunter
AI instantly dominates any task with a clear, standard answer, meaning traditional technical skills are rapidly losing value. To survive the next decade, your paycheck depends entirely on your ability to manage chaos, ask profitable questions, and master the final 10% of polish that machines miss. If you are relying on basic execution to protect your career, you are tracking straight toward obsolescence.
AI models excel at anything with a clear loss function. If a task has a known answer, software can execute it instantly. This means traditional education, where you are graded against a static rubric, trains you for work that is rapidly depreciating. Building a career solely on solving standardized problems guarantees obsolescence.
Over the next decade, your market value depends entirely on what falls outside model training windows: identifying ambitious problems, mastering the finally layer of polish, and cultivating irreplaceable human networks.
Look at software engineering. Traditional system design and LeetCode-style interviews no longer correlate with job performance, because AI agents can instantly generate perfect code for standard prompts. The new benchmark for top talent is how quickly someone can drop into a chaotic, undefined environment, understand the context, and identify which problems actually need solving.
Once those problems are selected, the next step is allocating computational tokens and time to solve. Managing an AI’s execution is the modern equivalent of manual labor. The market no longer rewards the ability to provide the correct answer; it rewards the ability to ask the most lucrative questions.
Because anyone can now generate a baseline product with a sloppy AI prompt, median execution has essentially zero value. This polarization creates the Last Mile Rule: the final 10% of project effort yields 90% of the actual career reward. That crucial final 10% requires relentless human iteration, building clean architecture, and applying extreme creative attention to detail. Professionals who accept an AI’s first draft will fail. The unique, human-driven finishing touches are what capture all the market’s attention and budget. Zooming out to your broader career strategy, remember that capital and code are abundant.
What remains strictly limited is real human relationships and a trusted professional reputation. Early career choices must optimize for exposure to high-level networks and communities. Time spent doing excellent work around reputable people compounds far better than maximizing your starting salary.
Think of your trajectory using the soccer metric xG, or Expected Goals. Evaluate potential employers based on the density and quality of opportunities they generate for you. Maximizing your career xG means joining teams tackling the most ambitious version of a problem. Evaluate the raw talent of that team and ignore how clunky their initial product demo might look. You won’t convert every chance into a win, but positioning yourself in high-opportunity environments ensures you are consistently in front of the goal.
To improve your positioning and access expert coaching, video courses, books, and guides from Jeff Altman, visit jobsearch.community.
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