How AI Agents Publish to Medium, Substack & Dev.to

Publishing across platforms like Medium, Substack, and Dev.to used to require a ton of manual effort — rewriting intros, adjusting formatting, handling SEO fields, and navigating each platform's quirks. In 2025, teams that scale content aren’t doing any of that manually anymore. They rely on AI agents that can not only draft and optimize content but also publish it across multiple platforms with the right formatting, the right tags, and the right canonical logic. And at the very top end of this automation, platforms without APIs are no longer blockers — computer-use agents now handle that too. For a deeper overview of scaling content operations, check out our content at scale guide.

What This Article Covers

• How to leverage AI agents for platform-specific SEO optimization on Medium, Substack, and Dev.to.
• A step-by-step framework for automating the publishing process from ideation to analysis.
• Insights into maintaining quality and brand voice through human-in-the-loop checkpoints.
• Practical scenarios illustrating the use of AI agents in various content strategies.
• A detailed implementation guide for setting up AI-driven publishing workflows.

The Power of Platform-Specific Optimization

Each platform—Medium, Substack, and Dev.to—has its own set of SEO levers and community dynamics that must be respected to maximize reach and engagement.

Medium’s SEO Levers

Tags, canonical URLs, and engagement signals (especially claps) matter most. Medium also has strict formatting rules that AI agents must respect when generating or posting content.

Substack’s Unique Dynamics

Substack relies heavily on subscriber behavior. Open rates and forwards are key discovery signals. AI agents need to write newsletter-optimized intros and subject lines.

Dev.to’s Technical Edge

Dev.to prioritizes tags, code block accuracy, and community upvotes. The platform is ideal for technical content and tutorials.

The AI Agent Publishing Framework

The “AI Agent Publishing Framework” automates the entire content lifecycle:

1. Ideation Engine: Generates topics using keyword maps, search gaps, and trending queries.
2. Generation Module: Drafts SEO-optimized content with platform-specific variations.
3. Quality Gate: Uses automated checks and optional human review to ensure accuracy and brand voice alignment.
4. Publishing Layer: Connects directly to APIs or uses computer-use agents for platforms without functional APIs.
5. Performance Analyzer: Tracks engagement, SEO results, and platform signals.

How Gentura Does This

Gentura extends this framework with capabilities most teams don’t have:

• Proprietary computer-use agents that can publish to platforms without APIs (Medium, Dev.to, Substack) by safely simulating human actions.
• Platform selection logic based on topic type, keyword difficulty, domain rating requirements, and historical performance.
• High-DR targeting rules, where important commercial pieces go to authoritative platforms and longer-tail educational content is distributed more broadly.
• End-to-end automation, from research → drafting → humanization → editing → enrichment → publishing → monitoring.
• Deep SEO intelligence, using tens of thousands of datapoints per writing plan to match keywords to the right platform and format.

This makes Gentura one of the only systems capable of scaling high-quality content across multiple platforms — even those that don’t expose APIs.

Practical Scenario: SaaS Startup

A SaaS startup wants to publish technical tutorials on Dev.to, thought leadership on Medium, and weekly digest content on Substack.

Gentura agents:

• Analyze the keyword difficulty for each topic.
• Select Dev.to for technical tutorials (high technical relevance, code block support).
• Choose Medium for stories and opinion pieces (strong DR and internal algorithm).
• Use Substack for digest-style updates (strong subscriber engagement).
• Publish automatically using a mix of API calls and computer-use agents.
• Set canonical URLs and format content to match each platform’s algorithm.

How to Implement This in Your Marketing

1. Define Content Taxonomy
   Map content types (tutorials, explainers, roundups) to matching platforms.

2. Build Prompt Templates
   Create platform-specific templates for intros, CTAs, and formatting.

3. Set Up Model Access
   Ensure your LLM has the right context and retrieval layers.

4. Integrate Platform Publishing Methods

   • API where possible
   • Computer-use agents where APIs fall short (Medium, Dev.to, Substack)

5. Set Up Human Review
   Only for high-visibility posts or compliance-sensitive content.

6. Schedule Distribution
   Time posts for platform-specific engagement windows.

7. Monitor & Iterate
   Track claps, email opens, upvotes, and SEO lift.

For a deeper dive, see our article on automating multi-platform distribution.

FAQ

How do I set up an AI agent to publish directly to Medium?
Use API integrations where possible, or computer-use agents to simulate human interactions with the UI.

Can I cross-post AI content without SEO penalties?
Yes — always assign a canonical URL to the original article.

How do I maintain quality when publishing at scale?
Use human-in-the-loop checkpoints for high-value content and rely on automated QA for the rest.

Can I publish purely AI-written content?
Yes, but adding human oversight helps improve style and prevents hallucinations.

Conclusion

Publishing to Medium, Substack, and Dev.to at scale requires more than an AI writing tool — it demands an orchestrated pipeline with platform-aware logic, automated formatting, and reliable distribution. With computer-use agents and deep SEO intelligence, Gentura automates the entire process end to end, so you don’t have to touch a single interface. If you'd rather have autonomous agents run this entire workflow for you, Gentura can do it on autopilot while you focus on product.