How to Ask an LLM to Write Stuff

What You'll Need

⏱ Time: 20 minutes  |  📋 Tasks:

• Open three browser tabs: chatgpt.com, claude.ai, gemini.google.com
• Create a free account on each (if you haven't already)
• Keep this lesson open in a fourth tab to follow along

Generic Output Is a Sign of Generic Instructions

You needed a professional email, so you opened a chatbot, typed "Write me an email about X," and got back something so generic it was useless. Bloated paragraphs. The wrong tone. Confidently wrong facts. You closed the tab and thought, "AI just isn't there yet."

I've been there too. And here's what I've learned: the problem isn't the AI. It's the instructions you gave it.

This lesson is the first step in a journey from blaming the tool to directing it. Every hour you invest now in learning how to communicate with these models pays back for the rest of your career. AI isn't going away. The question is whether you learn to drive or stay in the passenger seat.

LLM as Sous Chef

Imagine a sous chef who has memorized every recipe ever written. Every cuisine, every technique, every ingredient. They can execute any dish flawlessly — but only if you tell them what to make.

You walk into the kitchen and say, "Make me something good." The chef freezes. "Something good" could mean a thousand different things: spicy or mild, hot or cold, a five-minute snack or a twelve-course meal. The chef has all the knowledge but zero ability to read your mind. So they guess. And what they guess is the most generic, middle-of-the-road dish they can think of.

That's an LLM. A large language model has read a staggering amount of text — books, articles, code, conversations — and learned which words tend to follow which other words. When you type a prompt, it predicts the next word, then the next, then the next, building a response one word at a time. It doesn't think or feel or understand the way you do. It pattern-matches. It is the most skilled sous chef in the world — but it cannot read your mind.

This is why "Write me an email" gives you generic garbage. The chef needs specifics. The model needs context. The difference between slop and signal is how much of that context you provide.

The Human Intern Test

Before you hit enter, ask: If I gave these exact instructions to a new intern on their first day, would they know what to do? If not, your prompt needs more context.

Here are the most common traps new prompters fall into — and what to do instead:

• Don't assume the model knows what you know. It doesn't know your business, your client, or your preferences. State them explicitly. What feels obvious to you is invisible to the model.
• Don't skip the audience. Writing for a CEO, a teenager, and a regulator requires three completely different approaches. If you don't specify who, the model guesses — and likely guesses wrong.
• Don't bury the lede. Put the most important instruction first. If you need a 3-sentence email, say that in the first sentence of your prompt, not the last.
• Don't ask for "good" or "better" — define what that means. "Make it professional" is too vague. "Use formal language, address them by title, and include the invoice number" tells the model exactly what to do.
• Don't use one prompt for two tasks. If you need a summary and a separate list of action items, send two prompts. One task per prompt keeps each result focused.
• Don't be afraid to give negative examples. "Write like this example" is powerful. "Don't write like this example" is even more powerful — it draws a boundary the model can follow.

The fix is simple: give the model the context you'd want if you were the intern. Who you are, what you need, what to include, what to avoid, what format. When you treat the prompt like a manager who takes the time to brief you, the results change completely. This isn't about you being bad at prompting — you just needed a framework, and now you'll have one.

The FAINT Framework — A Mental Model That Sticks

Talk to an LLM like briefing a capable assistant who has never met you. They need five things — and FAINT helps you remember them all:

Frame + Aim + Include + Nix + Tone = FAINT. Don't stress — it's not so hard to make the problem FAINT! Cover these five things and the model knows exactly what you want.

That's the whole skill. Everything else is practice.

Actually Try This — Write Better Prompts in 5 Minutes

Step 1: See the slop for yourself

Open ChatGPT, Claude, and Gemini in three tabs. In each one, type this prompt — it's a reasonable attempt, not a caricature:

Write my marketing proposal for a client to sell social media management services.

This looks specific — it mentions marketing, a proposal, a service. But watch what happens. All three will produce something with [Client Name] and [Project Scope] placeholders. They're still guessing — politely, confidently, generically. The chef making "something good." This is the baseline. This is slop.

Step 2: Give it something real to work with

Start new chats in all three and paste this instead. Don't just read it — type or paste it. You need to see what happens when you give the model context.

I'm a small marketing agency owner.

I need a one-page proposal for a potential client who owns a local bookstore. They want help with social media and email marketing.

Include:
- A brief intro about my agency (humble, no hype)
- Two services I'm proposing: social media management + monthly newsletter
- A rough timeline for the first 90 days
- A pricing section with two options

Don't include:
- Corporate jargon or buzzwords

Tone: professional but warm
Length: one page when printed
Format: clean sections with headings

Step 3: Compare the three responses

Look at what each model produced. You'll notice real differences:

• ChatGPT — Structured, well-formatted, follows your bullet points closely. Often includes a brief rationale for its choices. Good at producing something you can use as a first draft with minimal editing.
• Claude — More natural flow. The tone lands closer to "professional but warm." Better at sounding like a real person wrote it. May ask clarifying questions before answering.
• Gemini — Direct and concise. Tends to give you the shortest response. Integrates Google search results if relevant to the topic.

Now here's the important part. Pick one real task you've been putting off — an email you need to send, a summary of an article, an outline for a project. Open ChatGPT and type the prompt from step 2, but filled in with your own details. Then open Claude and paste the same thing. Compare. Which version do you prefer? That's not a test — that's you learning which tool fits which job.

Your Takeaway — The Prompt Template

The single most useful thing you can do is save this template and use it before every prompt this week. Download 1a Basic Chatbots - 1 Prompt Template.md — save it to your desktop, notes app, or wherever you'll find it next time.

## Context
Who I am: [role or background]
What's happening: [situation or background the model needs]
Who this is for: [audience or recipient, if any]

## Task
I need: [one sentence describing what you want]

## Requirements
Include:
- [must-have 1]
- [must-have 2]
- [must-have 3]

Exclude:
- [avoid 1]
- [avoid 2]

## Style
Tone: [professional / friendly / formal / playful / urgent]
Length: [one paragraph / under 100 words / one page / three sentences]
Format: [plain text / bullet points / table / markdown / JSON]

The first time this template gets you a usable result in one try instead of three, you'll understand why specificity matters. Use it once. Then use it again. After a few times, you won't need the template anymore — you'll just know what the model needs.