The lazy read is that some people are just better at prompting.
Here is the more useful one. The same model, on the same task, can produce work that is genuinely good for one team and worthless for another — and the phrasing is rarely what separates them. The difference is what the model was handed before it started. Source material. A couple of worked examples. A rule for what counts as done, and what to do when the answer isn't there.
That packaging has a name now: context engineering. It covers the information, examples, tools, constraints, memory and retrieval assembled before a model acts.
The reframe matters more than the term. A prompt trick is personal and disposable — it lives in one person's head and leaves when they do. A context packet is an asset. It can be reviewed, corrected, versioned and handed to someone else. It survives a model upgrade, because it was never about the model.
This shows up first wherever the same task runs on repeat — a support queue, a weekly research pass, a legal ops review. Volume exposes the gap. One-off prompting hides it.
Next move: pick one task your team repeats. Write its packet — the goal, the source material, two examples of a good output, the format, the review rules, and what should trigger a human. Run it against three real cases, not invented ones. When it fails, assume the packet is wrong before you assume the model is.