In this episode, Ellis explores how AI agents, especially autonomous AI agents, are reshaping the landscape of technical communication. What are they? How do they differ from traditional AI tools? And crucially, what does their rise mean for technical writers?

Blending two recent blog posts, Ellis walks us through emerging tools like Manus, Opera's browser AI, and AgentQL, and what these changes mean for how we create, structure, and deliver documentation.

What AI agents and autonomous AI agents are — and how they're evolving

The four key traits of autonomous agents:

Insights from new AI tools

Ellis explores three main ways AI agents could change the role of technical authors:

Content for Autonomous AI Consumption

Structuring content for AI readability

Multimodal delivery (text, audio, UI elements)

Built-in accessibility for dynamic adaptation

Documentation as Agent-Ready Data

Writing docs as if they were APIs

Emphasis on semantic structure, metadata, and clarity

AI Agents as Co-Creators

Personalised content generation

Agent-driven feedback loops

Enhanced content curation and adaptation tools

"Autonomous is the key word. It signifies something that’s self-governing, that can operate independently, with little human oversight."

"The real transformative potential of AI lies in autonomous AI agents."

"Rather than being replaced, technical writers could become the architects of AI understanding."

📄 Blog post: The Rise of Autonomous AI Agents

📄 Blog post: Meet Your Future Co-Worker – AI Agents

🌐 Manus AI

🌐 Opera’s AI-Powered Browser Agent

🎤 Rachel Lee Nabors on AgentQL

📧 Contact: [email protected]

For more insights into the future of tech comms, AI tools, and professional development for technical writers, visit cherryleaf.com or follow us on LinkedIn and Twitter.