Prompt

Guest posting sites for AI tools

Media & Publishing / Developer Media4 observationsLast seen Sep 21, 2026

Latest observation

Sep 21, 2026PerplexityWeb search: on

For AI tools in 2026, the best guest posting sites are AI/ML‑focused pubs and general tech blogs that accept external contributors. Aim for publications where your ICP (data scientists, ML engineers, product/AI founders) already reads. neuraplus-ai.github

High‑signal AI/ML guest post targets

Towards Data Science (Medium)

  • Focus: Data science, ML, AI tutorials and explainers.
  • Authority: Very high (DA ~85+).
  • Notes: Strong editorial standards; best for practical ML/AI how‑tos and case studies. neuraplus-ai.github

KDnuggets

  • Focus: Data science, ML, AI news and tutorials.
  • Authority: High.
  • Notes: Accepts expert submissions; good for tooling, benchmarks, and industry trends. marketinglad

Analytics Vidhya

  • Focus: Data science/ML learning, tutorials, competitions.
  • Authority: High (DA ~75+).
  • Notes: “Write for us” program; great for beginner/intermediate ML/AI content. neuraplus-ai.github

Unite.ai

  • Focus: AI industry, startups, tools, and research.
  • Authority: Solid.
  • Notes: Welcomes AI tool posts and founder stories. marketinglad

AI Time Journal / The AI Journal / AIthority / Synced Review

  • Focus: AI news, research, enterprise AI, and tools.
  • Authority: Mid‑high.
  • Notes: Good for product announcements, thought leadership, and technical explainers. neuraplus-ai.github

O’Reilly Community

  • Focus: Advanced technical content (AI/ML, data, cloud).
  • Authority: Very high.
  • Notes: Expert submissions; best for deep, original technical pieces. marketinglad

MLearning.ai and Data Driven Investor (Medium pubs)

  • Focus: ML/AI tutorials, industry insights.
  • Authority: High (via Medium).
  • Notes: Good reach for practical AI content. marketinglad

Refrens AI, zPlatform, Globussoft AI

  • Focus: AI/SaaS tools, industry insights.
  • Authority: Growing.
  • Notes: Actively accept “write for us” AI guest posts; good for early traction. refrensai

General tech/startup pubs that accept AI content

  • Forbes Technology Council (paid council model; not traditional guest posts). bestprompt
  • TechCrunch (product launches; competitive, editorially driven). bestprompt
  • VentureBeat, The Next Web, ReadWrite (AI/startup news; pitch strong product stories). bestprompt

How to pitch AI tool posts effectively

  • Lead with a concrete outcome or insight: “How we cut LLM latency 3× with X” or “A practical guide to RAG evaluation in production.” neuraplus-ai.github
  • Include code, diagrams, or benchmarks: Editors favor posts with runnable examples or real metrics. neuraplus-ai.github
  • Avoid pure promo: Position the tool as a case study or example within a broader tutorial/insight. neuraplus-ai.github

If you tell me your AI tool’s category (LLM infra, vector DB, eval/observability, agents, RAG tooling, etc.) and ICP (DS/ML vs product/engineering), I can suggest 5–10 specific post ideas and the best 3 pubs to pitch first.

Observation history

How did Obsurfable measure this prompt?

Obsurfable records AI answers to buyer-style prompts in its research corpus (4 observations 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 dotdotPR. 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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