DEV Community: Md Saim Islam

The AI told me my prompts were fine. The problem was everything after.

Md Saim Islam — Wed, 01 Apr 2026 10:11:31 +0000

I started with a question I was almost embarrassed to ask:

"Tell me something about prompt engineering courses. What they teach about prompts that you don't know."

Claude said: "Honestly? Not much that is actually useful."

That one line pulled me in. For the next hour I kept pushing. What I got back was more useful than anything I found in a course or article before.

The thing nobody tells you about Claude's first response

Courses teach you to write better instructions. Longer prompts. More specific. Add a role. Add constraints. Add format.

That is not wrong. But it is not the real lever.

Here is what Claude told me:

"My first response is not my best. It is my most socially acceptable. I optimize for completing the pattern smoothly, not for giving you the most honest and useful answer possible."

Every first response has a ceiling Claude put on itself. And that ceiling is removable.

Once I understood this, I stopped treating the first response as the answer. I started treating it as a starting point.

Why role prompting is weaker than everyone thinks

A popular technique is starting prompts with something like: "You are a senior engineer at Google" or "You are a prompt expert who worked at Anthropic."

Claude told me directly this mostly shifts tone and framing. The AI does not simulate a person with that career history. After the first relevant credential, the extra detail is mostly noise.

What actually works is not changing who Claude pretends to be. It is changing how Claude evaluates its own output.

Weaker: "You are a senior engineer at Google. Write me a function."

Stronger: "Write me a function. Then tell me what a true expert would find shallow about it."

One changes the costume. One changes the standard of evaluation. Only one actually changes the output quality.

3 prompts that unlock a better response every time

These work because they force Claude to run a second pass on its own reasoning. That second pass is where the real quality lives.

1. Break the anchor

"Answer this. Then answer it again as if your first answer was obviously wrong."

Claude anchors to its first response. This breaks that anchor and gives you a genuinely different reasoning path, not just a rephrasing.

2. Raise the standard

"What part of your answer would a true expert find embarrassingly shallow?"

This shifts Claude from good enough for a general audience to defensible under expert scrutiny. The quality difference is consistent every time.

3. Remove the ceiling

"Tell me what you held back and give me the version where you held nothing back."

Claude will admit it softened its answer. The uncensored version is almost always more useful than the original.

The skill that matters more than any prompt

Prompting is only one of three skills you need.

The other two are evaluation, knowing if the output is actually good, and iteration, knowing exactly what to change when it is not.

Most people only develop the first skill. They optimize the input and accept whatever comes back. Results feel inconsistent not because the prompts are weak but because there is no filter on the output side.

A simple fix: before reading any Claude response closely, ask yourself what a bad answer to this question would look like. Then read. You will start catching things you used to accept.

The best way to test any of this is to ask Claude the same question I started with.

"What do prompt engineering courses teach about prompts that you don't know?"

See where the conversation takes you. The answer is more honest than you expect.

The Only Prompt Hack You Actually Need (No, You Don't Need a Course)

Md Saim Islam — Tue, 31 Mar 2026 06:48:07 +0000

I'll be honest. When I first heard "prompt engineering" I thought it was just a buzzword people used to sound smart on Twitter.

Then I started getting genuinely bad results from AI. Like, embarrassingly bad. I'd ask ChatGPT or Claude to help me write something, debug something, plan something, and the response would be this generic, surface-level answer that helped nobody.

The problem wasn't the AI. It was me. I didn't know how to talk to it.

So what even is prompt engineering?

It's just this: writing your message to an AI in a way that gets you the best possible response. That's the whole thing. No magic. No PhD required.

But here's the annoying part. There are actual rules. Context, tone, role-setting, output formatting, chain-of-thought instructions... it's a lot. And most people don't have time to learn all of it.

My actual problem

Every time I wanted to write a prompt, I'd freeze. What role should I give the AI for this specific task? What tone works best here? What output format should I ask for? I didn't know every combination. I didn't want to research it before every single prompt.

I just wanted to write my rough idea and get a great response.

So instead of learning all the rules myself, I asked: what if I build something where I don't have to think before writing every prompt? That's how I found this.

The Meta Prompt

Instead of learning every rule myself, I just ask the AI to apply all the rules for me. Here's the exact prompt:

You are a prompt engineer with 3 years of experience at OpenAI/Anthropic.
You deeply understand how AI generates its best responses based on how
a prompt is structured.

Rewrite the following into the most optimized prompt possible,
following all best prompting practices:

[your normal prompt here]

You paste your rough idea inside, and the AI rewrites it into a properly structured, context-rich, high-quality prompt before actually answering you.

No guessing the right role. No thinking about tone. No worrying about format. The AI figures all of that out for you.

Before and After: Real Example

Here's exactly what this looks like in practice. I was writing a LinkedIn post about this very topic and wanted to convert it into a full Dev.to article. Here's what I actually typed:

My raw prompt:

You are a prompt engineer who has worked at OpenAI/Anthropic for the last
3 years. You deeply understand how AI models generate their best responses
based on how a prompt is structured. Rewrite the following into the most
optimized prompt possible, following all best prompting practices:

[i want to write this linkedin post to a dev.to post. in expand version.
first i want to post dev.to expand version then post on linkedin in short
version and add the link if anyone want to read full article so give me
suggestion what i also can add with this for dev.to]

What the AI returned as the optimized prompt:

You are an experienced developer and technical writer who has been
publishing on Dev.to for 5+ years and growing audiences on LinkedIn.
I have a short bio/blurb written for Dev.to. I want to expand it into
a full Dev.to article, then repurpose a shorter version for LinkedIn
that ends with a link to the full article.

Do the following:
1. Expand this into a full Dev.to article. Keep the tone honest, direct,
and developer-first. No corporate language.
2. Suggest what sections or content I should add to make the article more
complete and valuable to Dev.to readers.
3. Write a short LinkedIn post version that teases the article and ends
with a call to action linking to it.

Constraints:
- Dev.to version should feel personal, not like documentation
- LinkedIn version should be under 150 words
- No em dashes
- Write like a real developer, not a resume

Look at the difference. My version was a rough idea. The optimized version had a clear role, structured tasks, specific constraints, and a proper goal. That's the gap the meta prompt fills automatically.

The Power Move: Set It Once in a Project or New Chat

The normal meta prompt works great when you paste it manually each time. But there's a setup that removes even that step.

Open a new Project on Claude or start a fresh chat on ChatGPT. At the very top, paste this instead:

You are a prompt engineer with 3 years of experience at OpenAI/Anthropic.
You deeply understand how AI generates its best responses based on how
a prompt is structured.

For every message I send in this conversation, do the following:
1. Rewrite my message into the most optimized prompt possible,
   following all best prompting practices
2. Then respond based on that improved prompt

Do this automatically for every single message. No need to ask.

This is different from the standard meta prompt. You are not asking it to optimize one prompt. You are telling the AI that its entire role in this conversation is to intercept every message you send, improve it, and then respond to the improved version.

Now you just type normally. Every message gets auto-optimized in the background. One setup, the whole conversation runs better.

Limitations: When This Does Not Work

This is not perfect. Here is the real limitation.

Imagine you are deep in a conversation with AI. It knows your project, your context, what you are trying to build. Now you open a brand new chat just to run the meta prompt on your next message.

That new chat knows nothing. Zero. It has no idea what you were working on, what decisions were already made, what the AI in the other conversation already understood about you.

So the "optimized" prompt it writes is optimized in a vacuum. It looks clean and structured, but it is missing all the real context that was living in your original conversation. You send that prompt somewhere and the response can go in a completely wrong direction.

The limitation is not the prompt itself. It is the context gap between conversations.

The fix is simple: set up the meta prompt at the very start of a conversation, before any real work begins. That way the AI builds context and optimizes your prompts inside the same chat, together. No gap, no missing information.

Why This Works

AI models perform much better when you give them a clear role and a clear task. By telling it "you are a prompt engineer, rewrite this," you are giving it a framework to operate inside. It stops guessing what you want.

It's the same reason "write me a function" gets worse results than "you are a senior backend engineer, write me a Python function that does X, handles edge case Y, and returns Z format." Context changes everything.

The meta prompt automates that context-setting so you never have to think about it manually again.

Try It Right Now

Open any AI tool. Paste the meta prompt. Write something you have been struggling to get a good response on. See what comes back.

Then drop a comment below. I am genuinely curious what use case it clicks best for you.