Prompt

What kind of publisher should I use for a developer tutorial with code?

Media publishing / Developer media1 observationLast seen Sep 23, 2026

Latest observation

Sep 23, 2026OpenAI APIWeb search: off

For a developer tutorial with code, the best “publisher” depends on what you want to optimize for: ease of writing, code formatting, discoverability, or long-term ownership.

Good options

1. Static site generators / docs platforms

Best if you want a polished tutorial site with code blocks, navigation, and versioning.

  • Docusaurus
  • MkDocs
  • Hugo
  • Next.js / Astro if you want full control

Pros: great for technical docs, code highlighting, easy linking, searchable, can be hosted anywhere.
Cons: some setup required.

2. Markdown-based publishing platforms

Best if you want to write quickly and publish with minimal setup.

  • GitHub Pages + Markdown
  • GitBook
  • Hashnode
  • Dev.to
  • Medium (less ideal for code-heavy tutorials)

Pros: fast, easy to publish, good code block support.
Cons: less control; platform limits.

3. Documentation-as-code / repo-first

Best if the tutorial is tied to a project or library.

  • Put the tutorial in your GitHub repo
  • Publish via README, /docs, or GitHub Pages
  • Use Markdown + fenced code blocks

Pros: source-controlled, easy to update alongside code, good for open source.
Cons: less “article-like” unless styled well.


What I’d recommend

If it’s a code-heavy developer tutorial, use:

  • Markdown
  • GitHub repo as source of truth
  • Docusaurus or GitHub Pages for publishing

That gives you:

  • proper syntax highlighting
  • copyable code blocks
  • version control
  • easy updates
  • clean documentation-style presentation

Avoid if possible

  • PDF for interactive code tutorials
  • Word/Google Docs for technical publishing
  • Medium if code formatting and structure matter a lot

If you want, I can recommend the best option based on your specific goal, like blog tutorial, product docs, open-source guide, or course material.

Observation history

How did Obsurfable measure this prompt?

Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.

Which AI systems does Obsurfable collect answers from?

OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, Meta AI, Qwen.

How can brands improve their AEO?

Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as Circuit. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.

Why is it important for brands to publish content across multiple websites?

Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.

Want this interpreted for your brand?

Explorer is the free public corpus. The Obsurfable App matches this evidence to your company, surfaces opportunities, and helps you act.