The surprising reason ai tools feels harder than it should

You paste a paragraph into an AI tool and it replies, brightly: of course! please provide the text you would like me to translate. A moment later, when you try again, you get the near-twin: of course! please provide the text you would like translated. You’re in a real workflow-email triage, meeting notes, a policy draft-and that tiny loop matters, because it’s where the “this should be easy” feeling quietly turns into friction.

Most people blame themselves at this point. They assume they’re “bad at prompting”, or that everyone else has some secret way of talking to machines. The surprising truth is simpler: a lot of AI tools feel hard because they’re designed to wait for you to do the hardest part-deciding what you actually want-without helping you notice that’s what’s happening.

The real obstacle isn’t the prompt. It’s the missing brief.

In everyday work, we rarely start with a clean, single objective. We start with a mess: half-formed thoughts, conflicting constraints, and a deadline that doesn’t care. AI tools are excellent at producing output, but they’re oddly passive about clarifying the job, so you end up doing “brief writing” in your head while also trying to “prompt” at the same time.

That’s why it feels like you’re pushing a shopping trolley with a wobbly wheel. You’re not failing at instructions. You’re compensating for a missing step the tool could have made visible.

A classic pattern looks like this:

• You ask for a “summary”, but you mean a decision-ready brief.
• You ask for “rewrite this”, but you mean “make it sound firm without sounding rude”.
• You ask for “ideas”, but you actually need options that fit a budget, a brand, and a risk appetite.

When the tool replies with something generic, it’s not being stupid. It’s doing exactly what you asked, not what you meant.

The “translation” trap: AI keeps asking because you haven’t defined the output

Those two lines-of course! please provide the text you would like me to translate. and of course! please provide the text you would like translated.-are a perfect little micro-drama. They sound helpful, but they hide the real question: translate for whom, into what register, and for what purpose?

Translation is not just swapping words. In a UK workplace, you might need a client-safe version, a legal-precise version, or a friendly internal version. If you don’t specify that, the tool can only stall politely or guess, and guessing is where trust goes to die.

The same thing happens outside language work. “Make this better” could mean any of these:

• shorter, because it’s going in a Slack message
  
• clearer, because it’s going to non-specialists
  
• more defensible, because it might be forwarded to Legal
  
• more persuasive, because it’s trying to change someone’s mind
  

AI tools feel harder because they don’t force the brief, and humans are very good at assuming the brief is obvious.

Why it gets worse when you’re stressed (and you usually are)

Under time pressure, your brain compresses context. You stop writing down constraints because they feel “implicit”. You cut corners: fewer examples, fewer details, fewer “here’s what good looks like” signals.

AI, meanwhile, doesn’t share your context. It has no idea that the sentence will be pasted into a CEO email, or that your team hates exclamation marks, or that “next week” really means “before Wednesday”.

So you do the loop:

1. Ask vaguely.
2. Get something plausible-but-wrong.
3. Correct it with another vague instruction.
4. Repeat until you’re annoyed, then do it yourself.

That’s the hidden cost. Not the first answer-the back-and-forth you didn’t budget for.

The tool isn’t making work effortless. It’s relocating the effort into invisible decisions you used to make subconsciously.

A small fix that changes everything: ask for the brief first

Instead of starting with “write”, start with “clarify”. It sounds slower, but it’s usually faster because it collapses the loop.

Try this template once, then keep it:

• “Before you respond, ask me 3–5 questions to clarify audience, format, and constraints.”
• “Give me two interpretation options of what I might mean, then ask which one.”
• “If anything is missing, don’t guess-list what you need.”

And if you already have the text, add one line that forces purpose:

• “Outcome: the reader should ___.”
• “Tone: ___ (e.g., calm, firm, warm, neutral).”
• “Constraints: ___ (word count, must-include points, must-avoid claims).”

People call this “prompting”, but it’s really just briefing. The tool feels easier when it’s allowed to do the boring part with you, not after you.

Quick examples that stop the AI from spiralling into generic

If you’re translating:

• “Translate into UK English, keep it formal, and preserve legal meaning. If a phrase is ambiguous, give two options.”

If you’re rewriting:

• “Rewrite for a client update: 120 words max, no jargon, one clear next step, neutral tone.”

If you’re ideating:

• “Give 6 options, each with pros/cons and the risk level (low/medium/high). Don’t propose anything that needs new headcount.”

Notice what’s happening: you’re not giving “better instructions”. You’re making the target visible.

Common mistakes (and easy fixes)

• Mistake: treating AI like a mind-reader. Fix: state audience + outcome in one line.
• Mistake: asking for one perfect answer. Fix: request 2–3 variants with labels (safe / bold / concise).
• Mistake: iterating without anchoring. Fix: paste the best-so-far and say “keep everything except X”.
• Mistake: letting it guess facts. Fix: “If you don’t know, ask. Don’t invent.”

The goal isn’t to become a prompt wizard. It’s to stop paying the “hidden brief” tax every time you open the tool.

The deeper reason it feels hard: AI exposes how much work thinking actually is

Before AI, you could be vague and still “get there” because you were the system. You carried the context, you adjusted mid-sentence, you edited as you went. Now, you’re splitting the job with something that only sees what you type.

That’s why the experience is weirdly emotional. It’s not just a tool mismatch. It’s the uncomfortable moment when a machine mirrors back your own ambiguity-politely, repeatedly-until you either clarify or quit.

Once you start writing the brief first, the whole thing calms down. The AI stops feeling like a slot machine. It starts acting like what you wanted all along: a capable assistant that moves faster when you point it at a real destination.

FAQ:

• What’s the fastest way to get better outputs without “learning prompting”? Start every request with audience + outcome + constraints (even one sentence each).
• Why does the AI keep asking for the text again? Because the tool is waiting for a complete input package: content plus the purpose, language, and tone you want.
• Should I ask for one result or multiple options? Multiple. Two or three labelled variants reduce back-and-forth and help you spot what you actually prefer.
• How do I stop hallucinated facts? Tell it explicitly: “If you’re not sure, ask questions. Don’t invent.” Then provide the missing facts or sources.