In this project you will design a prompt chain that takes a single blog topic and turns it into a publish-ready article — outline, draft, edit, SEO, and meta description, all driven by carefully written prompts. By the end you will have a reusable system you can apply to any niche and a finished post to drop straight into your portfolio.
Most people use AI to write blog posts the wrong way. They paste a topic into a chat, ask for "a 1,000-word blog post", and complain when the output is bland. The fix is to stop treating the AI as a writer and start treating it as a small editorial team that needs a brief. In this project we build that brief as a chain of prompts, each focused on one job: ideation, outline, draft, edit, headline, and meta description.
The deliverable is a real, finished blog post — around 1,000 words — saved as a Markdown file along with the prompts used to produce it. That folder becomes the artefact for your portfolio.
A blog post is not one task. It is six. Trying to do all six in one prompt produces a Frankenstein output that is mediocre at all of them. A prompt chain breaks the work apart so each prompt can do its job well and so you can inspect (and fix) the result of every step.
Think of it like a small newsroom. The ideator picks the angle. The editor builds the outline. The writer drafts. Another editor polishes. The SEO person handles the title and meta. Combining them into a single prompt is like asking one intern to do all five jobs at once — they will do none of them well.
Here is the kind of prompt most beginners reach for, and why it falls flat.
One-shot blog prompt
Write a 1000-word blog post about prompt engineering for beginners.
The output will be generic — a wall of "what is", "why it matters", and "in conclusion". The headline will be flat. The structure will be a list of obvious sub-headings. There will be no specific examples, no voice, no point of view. It reads like every other AI blog post, which is exactly the problem.
Below is the full chain. Run each step in order, paste the output of step N into the input of step N+1, and read the result before moving on. Adjust if anything is off.
Step 1 — Ideation prompt
You are an experienced content strategist for a developer-focused blog.
Topic: "Prompt engineering for beginners."
Audience: developers with 1–3 years of experience who have tried ChatGPT
casually but never built anything serious with it.
Suggest 5 specific blog angles for this topic. Each angle should:
- have a clear point of view (not "What is X?")
- promise a concrete outcome the reader will get
- avoid clichés like "in today's world" or "game-changer"
Return the angles as a numbered list with a one-line rationale for each.
Pick the angle that excites you most. For this walkthrough we will go with: "The five small habits that separate developers who get great AI results from those who don't."
Step 2 — Outline prompt
Build an outline for a 1,000-word blog post with this angle:
"The five small habits that separate developers who get great AI results
from those who don't."
Constraints:
- Hook the reader in the first 2 sentences.
- Each habit becomes one H2 section with a short story or example.
- End with a "What to do tomorrow morning" practical section.
Return: H1, intro paragraph (2 sentences), then H2/H3 outline with
1-line summaries for each section. No fluff sections.
Read the outline. Cut anything obvious. If two sections are similar, merge them. This is the most important step — fix the structure now and the draft writes itself.
Step 3 — Draft prompt (per section)
You are a senior technical writer. Voice: friendly, direct, no hype.
Write the section below as ~150 words of flowing prose.
Use one concrete code example or scenario.
Avoid: filler phrases, "in today's fast-paced world", "leveraging".
Section:
H2: Habit 2 — They version their prompts like they version their code.
Summary: developers who treat prompts as throwaway text get throwaway
results. Show what a "prompt file" looks like in a Git repo.
Run this prompt once per section. Stitch the sections together. The draft now has actual specifics instead of generic platitudes.
Step 4 — Edit prompt
Edit the draft below.
Rules:
- Cut any sentence that does not earn its place.
- Replace passive voice with active where natural.
- Remove every "in conclusion", "as we have seen", "it is worth noting".
- Keep my voice — do not turn this into a corporate blog.
- Target 1,000 words.
Return: the edited post and a 5-bullet changelog of the biggest edits.
Draft:
"""
...paste the stitched draft here...
"""
The changelog is the secret weapon — it forces the AI to explain its edits so you can accept or reject them line by line.
Step 5 — Headline + meta prompt
You are an SEO-aware content editor.
For the post below, propose:
- 5 candidate headlines (each ≤ 60 characters, no clickbait)
- 1 meta description (140–155 characters, includes the primary keyword
"prompt engineering")
- A URL slug in kebab-case
- 5 internal-link anchor phrases I could use to link from other posts
Post:
"""
...paste edited post...
"""
Step 6 — Publish prompt
Convert the final post into a Markdown file with YAML frontmatter
containing: title, description, slug, date (today), and tags
(3 relevant tags).
Then add a short "About this post" footer block (1 paragraph)
written in first person.
You now have a Markdown file ready for any static site generator — Astro, Hugo, Next.js — or a copy-paste into your CMS. Save the entire chain in a folder named blog-writer-project/: the brief, the six prompts, the intermediate outputs, and the final post.
Pick a topic you actually know well. Run the ideation prompt and force yourself to choose the angle that feels least obvious. Notice how much harder — and better — the draft becomes when the angle is not the boring default.
Take the edit prompt and add one extra rule for your own voice — for example, "Use British spellings (organise, behaviour, summarise)" or "No sentences longer than 22 words". Compare the edited draft to the unedited one and see what the rule changes.
Save your six prompts in a single Markdown file called blog-writer.md. Next week, swap only the topic and run the chain again. The fact that the same chain works on two completely different topics is what makes this a system rather than a one-off prompt.
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