Taste Is the Thing AI Can't Copy
AI can generate a thousand options in seconds. What it can't do is tell you which one is good. As generation gets free, the scarce skill isn't making things — it's knowing what's worth making. That's taste.
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AI can generate a thousand options in seconds. What it can't do is tell you which one is good. As generation gets free, the scarce skill isn't making things — it's knowing what's worth making. That's taste.
"We're adding AI" is not a plan. It's a technology in search of a problem. The companies winning with AI didn't start with AI — they started with a problem worth solving and reached for the right tool.
One AI that does everything sounds better than many that each do one thing. In practice, specialized assistants often crush general ones at the tasks that actually matter to you.
Every week brings a new AI breakthrough that will "change everything" — and most of it is noise. Learning to separate genuine capability from hype is now a core professional skill.
The AI conversation is obsessed with the biggest, most capable models. But for a huge range of real tasks, a smaller, faster, cheaper model is the better choice. Capability you don't need is just cost.
An AI assistant can be a genuine force multiplier or a time sink that creates more work than it removes. The difference is measurable — if you bother to measure it.
The "AI will take your job" panic and the "AI changes nothing" denial are both wrong. The honest middle is more useful — and more demanding — than either comfortable extreme.
Full autonomy sounds like the goal, but handing an AI the keys to act unsupervised is rarely smart from day one. The question isn't whether to keep humans in the loop — it's where.
"Prompt engineering" sounds like an arcane new skill. It mostly isn't. Getting good results from AI is overwhelmingly about thinking clearly about what you actually want — and saying it precisely.
The dream of AI agents is autonomy — set them loose and let them work. The reality is that autonomy without guardrails is how agents cause real damage. The goal isn't a trusted agent; it's a constrained one.
Agents that dazzle in a demo collapse in the real world. The gap between demo and production is where most AI agent projects quietly die. Here's what actually breaks.
The words get used interchangeably, but an agent and a chatbot are fundamentally different things. Confusing them leads to building the wrong thing for the job.