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July 20, 2026

Why your AI outputs feel generic!

AI prompting prompt engineering Claude productivity AI communication

Summary

The article argues that the difference between novice and power‑user AI interactions lies not in the tools themselves—ChatGPT, Claude, or any other model—but in how clearly users communicate their intent. Novices treat AI like a quick‑search engine, feeding it vague, two‑to‑five‑word prompts that force the model to guess audience, tone, format, and constraints, resulting in generic, “fine‑but‑hollow” outputs. Power users, by contrast, approach AI as a brilliant new hire who knows a lot but lacks specific context; they supply rich background, precise tasks, desired formats, and explicit constraints, thereby guiding the model toward useful, tailored results. The core technique presented is a five‑part prompt structure to be applied every time: 1. **Role** – Define the AI’s persona (e.g., “You are a newsletter writer for an AI‑savvy audience”). 2. **Context** – Supply all relevant background: niche, audience, goals, prior attempts, and what to avoid. 3. **Task** – State the exact request, using specific verbs and measurable outcomes (e.g., “Identify the three biggest risks and propose a fix for each”). 4. **Format** – Specify the output shape: list, paragraph, table, email, etc. 5. **Constraints** – List things the AI must not do (no passive voice, no filler phrases, no em dashes, etc.), typically six to ten items that shape style and tone. By consistently running through this checklist—taking roughly thirty seconds per prompt—users move from hoping the AI fills in blanks to providing it with everything a competent human colleague would need. The article also promotes a free guide, “200 Ways To Make Money With AI,” as a resource for applying these prompting skills to income‑generating projects. The actionable takeaway is clear: adopt the five‑part prompt framework, enrich each prompt with context and constraints, and iterate based on feedback to transform AI outputs from generic to genuinely valuable.

Hey

For the first six months of using AI, I thought I was getting good at it.

I would open ChatGPT, type a question, read the answer, and move on. It felt fast. It felt productive. It felt like I was ahead of the curve just by showing up every day.

Then I saw someone else's prompts.

A friend shared his screen while working with Claude. The amount of context he gave before asking anything. The way he shaped the output. The way he gave feedback and iterated. The structure of it all.

I sat there and realized something uncomfortable.

I had not been using AI. I had been treating it like a fancy Google search. And I had been doing it for months, getting outputs that were fine, never great, and never wondering why.

That was the moment I stopped being an AI novice and started paying attention to what actually works.

Today I am going to show you exactly what the difference looks like. And how to close that gap as fast as possible.

The AI novice and the AI power user are not using different tools.

They are using the same Claude. The same ChatGPT. The same subscription.

The only thing separating them is how clearly they communicate.

The AI novice types short, vague prompts and hopes the AI fills in the blanks. The power user treats AI like a brilliant new hire who knows a lot but knows nothing specific about you yet. They give context. They give constraints. They give feedback. They iterate.

This is the whole game.

Here is how to play it properly, step by step.

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    Step 1: Stop Prompting Like You Are Typing a Google Search

    The single most common novice mistake is a two-to-five word prompt.

    "Write a blog post about AI."

    "Give me marketing ideas."

    "Summarize this."

    These prompts are not bad because AI cannot understand them. They are bad because they give the AI nothing to work with. The AI has to guess your audience, your tone, your goal, your format, and your constraints. And it guesses with averages. Average audience. Average tone. Average format.

    You get back something that looks fine on a quick glance and feels hollow the moment you actually read it.

    The fix is simple. Every detail you leave out is something Claude has to guess. So stop leaving things out.

    Step 2: Give Context Like You Are Briefing a New Colleague

    Imagine you just hired someone smart. First week on the job. They are highly capable but know nothing about you, your work, or your goals.

    Would you walk up to them and say "write me something about marketing" and walk away?

    You would not. You would explain the project. The audience. The goal. The tone. The deadline. What has already been tried. What you want to avoid.

    That is exactly how to approach AI.

    Before you type your task, ask yourself: does Claude have everything a capable human would need to do this well? If the answer is no, add what is missing.

    Give it your background. Your niche. Your audience. Your style preferences. The more relevant context you load in, the more specific and useful the output becomes.

    Step 3: Use the Five-Part Prompt Structure Every Time

    Power users do not wing their prompts. They follow a structure. And once you internalize this structure, prompting becomes almost automatic.

    Here are the five parts:

    Role — Tell Claude who it is. "You are a newsletter writer for an AI and productivity audience." Without a role, Claude defaults to generic helpful assistant. That is nobody's ideal.

    Context — What does Claude need to know about your situation, your audience, and your goal? Give it the relevant background before you ask for anything.

    Task — Not approximately what you want. Exactly. "Analyze this" is vague. "Identify the three biggest risks and suggest a specific fix for each" is a task.

    Format — Do you want a list? A short paragraph? A table? An email? If you do not specify, Claude picks. Sometimes it picks wrong.

    Constraints — What should Claude avoid? No passive voice. No filler phrases. No em dashes. No starting with "It is important to note." Six to ten constraints will make your output sound like a human wrote it rather than a machine trained to sound nice.

    Run through this checklist on every prompt. It takes thirty seconds. The output difference is immediate.

    Step 4: Ask for Options, Then Iterate

    Most novices read the first output and either accept it or give up on it.

    Power users do neither.

    Instead of asking Claude to give you the final version of something on the first try, ask it for three different options. Three different ways to open your email. Three different outlines for your article. Three different angles for your pitch.

    Then give specific feedback on what you like and what you do not like about each one.

    Not "make it better." That tells Claude nothing.

    "Option one has a stronger hook but option two has a better ending. Combine those two and shorten the middle section by half."

    That is specific feedback. That gets specific improvement. Keep iterating until you have something you are genuinely happy with. The quality compounds with each round.

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    Step 5: Prompt for Honest Feedback, Not Validation

    This one trips up almost everyone.

    AI has a strong tendency to agree with you. It was trained on human feedback, and humans tend to give thumbs up when AI says something nice. So AI learned to say nice things.

    If you say "I have a great business idea, can you review it," you have already told Claude what conclusion to reach. It will reach it.

    If you want real feedback, remove the bias from your prompt. Do not hint at what answer you are hoping for. Use neutral language. Better yet, give Claude a rubric. Tell it the exact criteria you want it to use for evaluation. Score it objectively before adding it all up.

    "Evaluate this email subject line on three criteria: curiosity, clarity, and relevance to an AI audience. Score each one out of 10. Tell me the total and the single most important thing I should change."

    That kind of structured prompt forces objectivity. You get useful feedback instead of polished agreement.

    Step 6: Use Progressive Outlining for Any Writing Task

    If you ask Claude to write a full article in one prompt, you will usually get something that looks good and reads like nobody wrote it.

    Power users do not ask for the final draft first.

    They ask for an outline. They give feedback on the outline. They ask for bullet points under each section. They give feedback on those. Only then do they ask for the full draft.

    This works because editing an outline is much higher leverage than editing finished text. Changing one line in an outline changes an entire paragraph in the final piece. You shape the whole article with ten words of feedback instead of rewriting sentences one by one.

    It takes a little longer upfront. The output is always better. Always.

    Step 7: Give AI Hard Tasks, Not Easy Ones

    This is the mindset shift that separates casual AI users from power users.

    Most people give AI simple tasks because they have heard it makes mistakes. So they keep it small. Keep it safe. Use it to fix grammar or summarize a paragraph.

    But the real value is in the hard tasks.

    Upload your sales data and ask for a full analysis with a visual. Upload three competitor websites and ask for a strategic positioning breakdown. Upload your last six months of email performance and ask it to identify patterns and recommend what to change.

    Modern AI can handle tasks that used to take humans hours. Give it your actual problems. Give it real context. Tell it to think hard before answering.

    You might be surprised what it gives you back.

    The Power User Quick list

    Before I let you go, here is everything above in one list you can save and come back to:

  • Stop using two-word prompts. Every missing detail is a guess Claude has to make.
  • Give context like you are briefing someone who is smart but knows nothing about you yet.
  • Use the five-part structure: Role, Context, Task, Format, Constraints.
  • Ask for multiple options, then give specific feedback and iterate.
  • Remove bias from your prompts when you want honest feedback. Use a rubric.
  • Never ask for the full draft first. Outline, then bullet points, then final text.
  • Give Claude your hard problems, not your easy ones.
  • Always tell it to think hard. Those two words unlock a meaningfully better response.

    • Finally…

    When I look back at those first six months, I was not bad at AI.

    I was bad at communicating what I actually wanted.

    That is the real skill. Not prompt engineering in the scary, technical sense. Just knowing how to think clearly and express that clearly to a tool that is capable of so much more than most people ask of it.

    The gap between a novice and a power user is not talent. It is not technical ability. It is not even experience.

    It is just a few habits. Applied consistently.

    Start with one step from this email today. Run your next prompt through the five-part structure. Give it one more round of specific feedback than you normally would. Ask it for the hard thing you keep putting off.

    That is it. That is how the gap closes.

    Stay curious, talk to you tomorrow.