Prompt

What should I use to get a technical article about my product in front of developers?

Media publishing / Developer media1 observationLast seen Sep 23, 2026

Latest observation

Sep 23, 2026OpenAI APIWeb search: off

To get a technical article about your product in front of developers, the best channels are usually:

  1. Developer-focused communities

    • Hacker News — great for technical depth and startup/product visibility if the article is genuinely useful.
    • Reddit — relevant subreddits like r/programming, r/webdev, r/devops, r/golang, r/python, etc., depending on your audience.
    • Dev.to — good for practical technical content and tutorials.
    • Hashnode — similar to Dev.to, developer-friendly and blog-focused.
    • Product Hunt — more product-oriented, but can work well if the article ties into a launch or announcement.
  2. Social platforms where developers hang out

    • X (Twitter) — useful if you can get engagement from developer influencers and the post is concise with a strong hook.
    • LinkedIn — better for B2B/enterprise dev audiences and engineering leaders.
    • Mastodon / Bluesky — can work for niche developer audiences, especially open-source or indie tech.
  3. Your own technical blog + distribution

    • Publish on your company blog first, then repurpose and share excerpts on the channels above.
    • This helps with SEO and gives you a permanent canonical source.
  4. Communities and newsletters

    • Send it to developer newsletters that match your stack or niche.
    • Share in Slack/Discord communities for specific languages/frameworks/tools.
    • Reach out to independent bloggers or creators who write for your target developer audience.

What works best

If the article is:

  • educational, benchmark-driven, or solves a real problem, it’ll do best on Hacker News, Dev.to, and relevant subreddits.
  • more product-led or tied to a launch, use Product Hunt, LinkedIn, and X.

Quick tip

Developers respond best to content that feels like:

  • a how-to
  • a real technical deep dive
  • a benchmark/comparison
  • a postmortem or engineering story
  • a tutorial with code

If you want, I can also give you a distribution plan by audience type (startup devs, backend engineers, ML engineers, etc.).

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.

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