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P work isn't just harder than D work.
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The right place to put a human checkpoint varies dramatically by domain.
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Not everyone wants to shift to P work.
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You can't measure P work with throughput metrics.
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When a human approves bad AI output, is it the human's fault or the system's?
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The final part.
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P work failures aren't like bugs.
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Kai runs an audit tool.
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When AI automates the deterministic layer, the market for D skills reprices fast.
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A year in.
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Traditional org charts were engineered to move D work efficiently.
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Six months in, Kai's agent has a personality now.
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A morning in 2031.
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AI is collapsing the cost of building digital products.
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Every time we've made a productive tool more efficient, we used more of it, not less.
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Every decade, technology makes us dramatically more productive.
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If P work is the new bottleneck, your team model has to change: who you hire, how you structure ownership, how decisions get made, and what you measure.
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When to stop checking, when to keep going, and what actually changes when AI takes over the deterministic layer.
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Hallucinations, misunderstandings, and drift — the three types of P work failures, and exactly where to put your human checkpoints to catch each one.
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AI is offloading your deterministic work.
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As AI masters deterministic execution, the real leverage shifts to probabilistic work — where ambiguity is the job, errors compound, and someone has to own the consequences.
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Your morning routine is D→D→D.
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Your AI product isn't 'AI-powered.'
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Everyone's building 'AI agents.'
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I was tired of PM case studies that feel like homework.
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Everyone's adding 'AI' to their LinkedIn title.
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The next generation of great product managers won't just manage — they'll build.
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What changed when I started sharing my roadmap, experiments, and trade-offs in the open.
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The complete journey of building a portfolio website from scratch: architecture decisions, deployment nightmares, and why being a Full Stack PM means shipping your own products.
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The product manager role is quietly transforming.