In this episode, we dive into responses to the evolving digital landscape shaped by AI in search engines and changes in social media.

We explain how Cherryleaf took inspiration from the viral success of the Museum of English Rural Life (Merl) and used AI chatbots to analyse Merl's approach.

We share the key lessons learned - such as embracing an authentic voice, leveraging unique content, blending education with entertainment, and encouraging engagement - and details how Cherryleaf adapted these for a technical writing services company.

Discover the creative content pieces we've launched, including "Technical Writer Superpowers," "Technical Writing Bingo," and "Dungeons and Documents," and hear about the initial results in terms of engagement and reach. We also discuss future plans and how other organisations can adopt similar strategies.

Technical Writer Superpowers

Technical Writing Bingo

Dungeons and Documents

Technical writing jargon explained: 📦 Single-sourcing

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.

Summary:

In this episode, Ellis Pratt explores the critical issue of data privacy for technical writers using AI tools and chatbots. He delves into the potential risks, from data leaks and copyright infringement to compliance violations and intellectual property concerns. The episode also provides practical solutions and strategies for mitigating these risks, empowering technical writers to leverage AI responsibly and ethically.

Key Discussion Points:

The Promise and Peril of AI: AI offers significant productivity gains for technical writers (content creation, first drafts, automation of tasks), but introduces critical privacy risks.

Potential Risks of Using AI:

Data Leaks: Inputted data becoming part of the AI model, accessible to others.

Copyright Infringement: AI generating content based on competitor data.

Data Breaches: Risk of AI providers being hacked.

Data Sovereignty: Data stored in different countries potentially conflicting with regulations.

Compliance Violations: Risks related to regulated industries (healthcare, finance).

Intellectual Property Rights: Ambiguity over who owns AI-generated content.

Practical Solutions and Mitigation Strategies:

Sanitising Content: Replace sensitive data (API keys, product names) with placeholders.

Generic Examples: Use generic rather than actual customer data.

Limiting Data Input: Provide only the minimum amount of data required.

Review and Redact: Carefully review content before inputting to AI.

Check Public Domain Status: Determine if the content is already publicly available.

AI Provider Privacy Policies: Review data retention policies and opt-out options.

Choosing Secure Tools: Select tools with better data deletion options (e.g., Google GeminiAI Studio, Claude).

Managing Data Controls: Understand how to control data collection settings (e.g., ChatGPT).

Private/Managed LLMs: Consider private, self-hosted, or managed AI models for sensitive data.

Develop Policies and Procedures: Create guidelines for team use of AI, tiered approaches based on document sensitivity.

Content Filters: Implement filters to check for sensitive information.

Audits and Assessments: Engage IT security for impact assessments and security audits.

Actionable Takeaways:

Prioritise Data Sanitisation: Make it a core practice before using any AI tool.

Review Privacy Policies: Understand the data handling practices of your AI providers.

Implement Security Measures: Protect proprietary and confidential information through policies, technology, and human oversight.

Collaborate with Security and Legal: Engage relevant internal teams to ensure compliance and minimize risk.

Start Small and Stay Informed: Gradually introduce AI with low-risk documentation and keep up to date on the latest privacy risks and solutions.

Quotes:

"AI and chatbots offer in technical writing…a huge promise of a way to be more efficient and more effective in what we do. But…we do need to be aware that there is a privacy risk, and we need to address that."

"AI…is both a powerful productivity tool and a potential risk. So we need to think about those two aspects and manage it."

"So we're going to be on a tightrope, a privacy tightrope."

Cherryleaf specializes in fixing developer portals and technical documentation. If you're struggling with user feedback, contact us at [email protected] for expert guidance.

CC Flickr image: Stock Catalog

In this episode of the Cherryleaf Podcast, we explore the challenges of receiving and responding to criticism as a technical writer. Documentation plays a crucial role in user experience, and receiving feedback—whether constructive or harsh—can be an opportunity for growth. We discuss practical strategies for handling feedback, evaluating its validity, and implementing improvements to enhance documentation quality.

✅ Why receiving feedback (even negative) is better than receiving none

🔹 IBM Quality Matrix for documentation assessment

Cherryleaf specializes in fixing developer portals and technical documentation. If you're struggling with user feedback, contact us at [email protected] for expert guidance.

In this episode, we reflect on 2024's trends and explore what may be coming in the world of technical writing and content development in 2025. From the impact of AI to evolving policy requirements and shifting market dynamics, we look into the key factors shaping the field.

Reflections on 2024

AI and Technical Writing

Policy and Procedure Writing

Training and Development

Future Trends and Predictions

Get Involved

Thank you for tuning in! We wish all our listeners a joyful holiday season and a prosperous New Year. Stay tuned for more insights in our upcoming episodes.

In this episode, Ellis discusses the importance of networking and meeting other technical communicators, especially for those who work solo or in small teams. He explores various avenues for connecting with industry peers, from conferences and meetups to virtual groups and informal gatherings.

Key Topics Discussed:

Challenges of Solo Technical Communicators

Conferences & Meetups

• Ellis mentions conferences like TCUK and Tekom and describes the more casual atmosphere of meetups, such as those organised by ISTC and Write The Docs London.

Benefits of Attending Events

Navigating Networking for Introverts

• Tips on starting conversations, showing empathy, and practicing conversational balance to ease networking anxiety.

Write The Docs London Event Recap

• Highlights from recent presentations by Neo4j’s David Oliver on building a documentation team and Mark Woulfe on using dashboards to analyze documentation performance.

Alternative Networking Ideas

Tips for Speaking at Meetups

Final Thoughts

Connect with Ellis Pratt:

• Website: Cherryleaf.com

We explore an intriguing development in content creation: AI-generated audio from technical documentation.

We’ve prepared two examples to showcase this technology, and we discuss its potential impact and applications.

We used the user guide for Audacity, the popular audio editing application, to generate an AI-narrated overview:

https://youtu.be/yPlfAPpqGuw?si=cCJeZ-hfvg_o--fg

We also created an audio overview of Transport for London’s API using only their OpenAPI (Swagger) file as the source:

https://youtu.be/-j1yiFz8-Tc?si=WaRHpn0mgID8J4qX 

We'll also publish a transcript of this podcast on the Cherryleaf blog.

About Cherryleaf:

Cherryleaf

In this episode of the Cherryleaf podcast, we explore the latest trends in technical communication as revealed by an in-depth analysis of conference themes from 2024.

By examining data from leading events such as Tekom, TC World, LavaCon, and the STC Summit, we identify eight major themes shaping the industry, with a surprising dominance of AI and generative technologies.

Listen in to understand how these trends are influencing content strategy, user experience, compliance, and more, and learn how to position yourself at the forefront of these developments in technical communication.

We'll also publish a transcript of this podcast on the Cherryleaf blog.

About Cherryleaf:

Cherryleaf

Remember the excitement when ChatGPT burst onto the scene? Suddenly, it seemed like AI was going to revolutionise everything, including our field of technical communication.

But now, 18 months and six Cherryleaf AI podcast episodes later, we're asking the big question: Was it all just hype?

You've probably heard some folks saying AI isn't delivering the promised return on investment. And others swearing it's changing the game. So, what's the real story?

In this episode, we'll examine these claims through the lens of technical writing. We'll:

1. Examining recent claims about AI's lack of ROI

Whether you're an AI enthusiast or a sceptic, stick around. Let’s figure out where AI really stands in the world of technical documentation.

We'll also publish a transcript of this podcast on the Cherryleaf blog.

About Cherryleaf:

Cherryleaf

Goldman Sachs

https://www.goldmansachs.com/intelligence/pages/gs-research/gen-ai-too-much-spend-too-little-benefit/report.pdf?

Ed Zitron

https://www.wheresyoured.at/pop-culture/

Ethan Mollick: 

https://static1.squarespace.com/static/5d35e72fcff15f0001b48fc2/t/668d08608a0d4574b039bdea/1720518756159/chatgpt-full.pdf

https://x.com/emollick/status/1815563452640854093

MadCap Software

https://www.madcapsoftware.com/blog/madcap-ixaccms-ai-positron/

We've created some YouTube Shorts on promoting the value of techcomm. We talk about the process of creating the videos and the content in the videos.

See also:

Cherryleaf's YouTube Shorts

Uncovering and communicating the value of your tech comm teams' work, with Keren Brown 

We'll also publish a transcript of this podcast on the Cherryleaf blog.

About Cherryleaf:

Cherryleaf