Everyone Is Prompting Better. Almost Nobody Is Packaging Work.

The gap between prompting ability and packaging skill is quietly reshaping how work gets done. People are getting better at asking AI to produce outputs, but remarkably few are learning how to turn those outputs into reusable, shareable, repeatable artifacts. This isn't just a technical gap. It's a mindset gap. And it matters more than most people realize right now. At Netflix, Kasia Trapszo has been talking about how senior individual contributors grow influence by moving beyond writing code and toward scaling the way entire teams work. That same shift applies here: the people who will have outsized impact aren't the ones writing the best single prompt, they're the ones who can package a workflow into something durable that others can adopt. Similarly, the online RL reading group for incoming Ph.D. students reminds us that even in deeply technical communities, the real bottleneck is often fluency in frameworks rather than raw intelligence. You can understand the concept. You just haven't learned to wrap it up so someone else can pick it up and run.

Why does packaging matter so much right now? Because AI-native tools are lowering the cost of creation but not yet the cost of distribution. Anyone can generate a spreadsheet, a summary, a data pipeline, or a slide deck in seconds. But if that output lives only in a chat window, it dies with the conversation. Packaging means building a reproducible structure around the work: a template, a saved prompt chain, a documented workflow that survives context resets and team turnover. It means thinking about your output the way a product designer thinks about a feature, not just whether it works once but whether it works repeatedly and for someone who wasn't in the room when you built it.

This is where the opportunity lies, and it's worth being honest about why most people aren't doing it yet. Packaging feels like overhead. It requires you to slow down, name your assumptions, and structure your thinking in ways that feel redundant when you're the only one using the output. But the moment you need to hand something off, onboard a colleague, or revisit your own work two weeks later, that structure pays for itself many times over. The skill isn't glamorous. It doesn't show up in a demo. But it compounds. The people who develop packaging discipline now will find themselves moving faster as teams scale, because they'll spend less time re-explaining and more time building.

The broader pattern here is worth watching. We're seeing it in media too: The Times is turning Wordle into a TV game show, which signals that proven digital formats can evolve into entirely new distribution channels when someone takes the time to package the underlying concept for a different audience. The principle is identical. The medium changes. The packaging decisions determine whether the idea travels or stays locked in its original form. The question worth sitting with is simple: for everything you're building with AI today, what would it look like if you treated it as something meant to outlast your current session? That shift in orientation might be the most productive thing you do this quarter.