Prompt engineering

Prompt engineering is the craft of phrasing an instruction to a model so it reliably produces what you want: being specific about the task, the format, the constraints and the examples, rather than tossing a vague request and hoping. The same model gives wildly different results depending on how you ask, so a few minutes spent framing the request saves you a round of corrections later.

The core moves are simple and durable: state the goal plainly, give it the role and the rules, show one or two examples of good output, and ask it to reason before it answers when the task is hard. Say you're drafting a cold-email sequence in Claude , "write me some emails" gets you generic mush, but "you're a B2B founder writing to a CFO, three emails, under 90 words each, one clear ask, here's an example I like" gets you something you can almost send. Say you're researching a competitor in Perplexity: naming the exact sources you trust and the format you want (a five-row table, not an essay) is the difference between a usable answer and a wall of text. Or say you're spinning up a first-draft pitch deck in Gamma , telling it the audience, the narrative arc and the slide count up front beats nudging it slide by slide.

As models get stronger, raw prompt tricks matter less and clarity matters more, which is why the discipline has broadened into context engineering: deciding what the model sees, not just how you word the ask. For a founder it's a daily multiplier , less a hack than a habit of thinking clearly and saying exactly what you mean.