Inside Tech Comm with Zohra Mutabanna

Technical communication has moved from manual printing presses to AI agents, but the hardest parts of the work have not disappeared. Someone still has to think critically, ask the right questions, exercise judgment, understand the product, and recognize what users actually need.

Ramesh Aiyyangar, founder of Tech Write Pro and the Institute for Technical Communicators of India, joins me to reflect on nearly four decades in communication and technical communication. His career has spanned journalism, editing, advertising, public relations, technical writing, leadership, training, mentoring, and community building—giving him a long view of what changes with technology and what endures.

Ramesh challenges the idea that the future of the profession is simply a race to collect more tools or certifications. AI can take on repetitive, mechanical work, but it does not eliminate the need for discernment, structure, research, creativity, product depth, or a genuine understanding of the user. As he puts it, technical communicators are communicators first.

We also examine the new titles appearing across the field—from content strategist to context engineer. Ramesh sees them less as evidence of an entirely new profession than as renewed attention to capabilities that strong technical communicators have always needed. The opportunity is not merely to adopt a new title, but to go deeper into the product, treat documentation as a product in its own right, and take greater ownership of the customer experience.

That kind of growth requires more than individual effort. Our conversation turns to optimism, unlearning, self-reflection, honest mentoring, global networks, and the communities where practitioners can share experiments and learn from one another. Ramesh’s closing message is especially direct: our work should not be expected to speak for itself. Technical communicators must speak about the work, advocate for the profession, and give back to the communities that help it thrive.

In this episode, we discuss:

- What four decades of change reveal about technology and human judgment
- Why AI makes critical thinking and discernment more important, not less
- Looking beyond tools and certifications when planning a career
- Treating documentation as a product rather than a set of deliverables
- Going deeper into the product, engineering, and customer experience
- Why asking better questions remains a defining technical communication skill
- Unlearning old habits and moving beyond rigid career paths
- Shifting from hyper-specialization toward a more flexible, connected practice
- What new titles reveal about the profession’s longstanding core skills
- Using self-reflection to make more deliberate career choices
- What honest, individualized mentoring should provide
- Why global communities, cultural awareness, and social learning matter
- Speaking about our work and advocating for the profession

Season 8 of Inside Tech Comm is sponsored by LavaCon. Use discount code ITC26 to save $200 on registration for LavaCon 2026.

Show Credits

- Intro and outro music - Az
- Audio engineer - RJ Basilio

What happens when there is no single version of a product—and therefore no single version of its documentation?

In this episode, Fabrice Lacroix from Fluid Topics joins us to explore how made-to-order and highly configurable products are changing the way technical content must be structured, managed, and delivered.

We look at why traditional document-based approaches begin to break down as product variants multiply, and why granular, structured content, metadata, and product configuration data become critical. Fabrice explains how documentation can be assembled dynamically around the exact product a technician, support agent, or customer is working with.

This conversation also builds on recent Season 8 episodes about AI, context, and the content architecture beneath intelligent systems. Here, we take that discussion one step further: what happens when AI also needs to understand the exact product configuration before it can give the right answer?

We discuss:

• Why bespoke products create a fundamentally different documentation challenge
• Moving from document-oriented content to granular, structured content
• Mapping content to product components, configurations, and bills of materials
• Using metadata to dynamically assemble relevant documentation
• Why static PDFs struggle to keep pace with changing products
• How product context can reduce the risk of AI using the wrong information
• Why AI increases the need for explicit, structured, well-governed knowledge
• Why technical writers and content teams may become more strategically important—not less—as AI adoption grows

Season 8 of Inside Tech Comm is sponsored by LavaCon. Use discount code ITC26 to save $200 on registration for LavaCon 2026.

Show Credits

• Intro and outro music - Az
• Audio engineer - RJ Basilio

AI can retrieve and generate answers, but the quality of those answers still depends on the information beneath the model. If content is poorly structured, weakly governed, or divided into the wrong units, a more capable LLM does not automatically solve the problem.

Patrick Bosek, co-founder and CEO of Heretto, joins me to examine how structured content shapes AI context. We begin by defining structured content and comparing the different approaches, from DITA and XML to headless content management systems. Patrick explains why the right structure depends on scale, interoperability, reuse, and the ways an organization needs to deliver information.

This conversation builds on episodes Documentation Is Becoming the Interface and The Work AI Cannot See. If documentation is becoming a surface through which people interact with products—and AI cannot infer context it has never received—then content architecture becomes part of the AI system itself. This episode moves one layer deeper to examine that foundation.

Patrick walks through chunking, retrieval-augmented generation (RAG), vector search, metadata, and knowledge graphs without treating AI as a replacement for established information practices. Metadata still provides deterministic controls. Traditional search may remain the better choice in some situations. Governance and provenance still matter when content comes from product, engineering, support, and documentation teams.

We also consider the practical side. A lone writer can begin with a small style guide, consistent Markdown, useful metadata, and an AI agent that reviews content against established rules. At enterprise scale, however, tools alone are not enough. Information modeling, information architecture, governance, and deliberate implementation have to come first.

In this episode, we discuss:

• What structured content means beyond a single format or tool
• When DITA becomes useful—and when it may be more than a team needs
• Why clean content boundaries improve chunking and retrieval
• How RAG systems retrieve information outside the language model
• Why metadata remains valuable in both deterministic and AI-driven systems
• When traditional search can compete with or outperform vector search
• How metadata can connect structured content with knowledge graphs
• Establishing authority, provenance, and a source of truth across teams
• Practical governance steps for lone writers working in Markdown and GitHub
• Why implementing a CCMS also requires information modeling and architecture
• Why a well-structured website remains important when public AI systems answer customer questions
• The difference between buying tools and building the information foundation those tools require

Season 8 of Inside Tech Comm is sponsored by LavaCon. Use discount code ITC26 to save $200 on registration for LavaCon 2026.

Show Credits

• Intro and outro music - Az
• Audio engineer - RJ Basilio

AI can summarize meetings, monitor repositories, categorize support tickets, and generate instructions. But automation does not eliminate the need to understand what customers are trying to do—or what happens when a product enters the real world.

Vinay Payapilli joins me to examine the assumptions beneath the rush to automate technical communication. Drawing on 26 years in the profession, he explains how mapping documentation’s critical path changed the problem his team was trying to solve. The largest delays were not in writing. They were in recovering context from scattered conversations and waiting for knowledgeable people to review the result.

That distinction leads us to a larger question: What must be understood before any part of the work can be handed to AI?

A system can describe the steps encoded in software. It cannot observe a cashier memorizing a sequence of keystrokes because reading the interface takes too long. It cannot know that customers are misusing a delete button because the product gives them no reason to stop. And it cannot decide, without human context, whether the customer needs another article or a better product.

Our conversation moves between documentation practice and the wider uncertainty surrounding AI:

• The difference between generating instructions and helping customers make decisions
• How AI can surface patterns that manual analysis misses
• Why customer workarounds may never appear in support data
• The role of technical writers in questioning product decisions
• Why rapid prototypes distort leadership’s expectations of delivery
• What drives the demand for an organizational “AI story”
• How practitioners can respond to disruption without pretending to predict the future

Vinay’s message is neither resistance nor blind optimism. Use AI. Experiment with it. But go deep enough into the product, the domain, and the customer’s reality to recognize what the technology cannot know on its own.

Season 8 of Inside Tech Comm is sponsored by LavaCon. Use discount code ITC26 to save $200 on registration for LavaCon 2026.

Show Credits

• Intro and outro music - Az
• Audio engineer - RJ Basilio

Documentation is not just support material anymore. It is quietly becoming a product surface, a competitive advantage, and in many cases the raw fuel that AI systems use to help customers get work done.

I’m joined by Nico Berry, a former technical writer who now works in product management at Contentful. We start with his move from technical writing into product management and the skills that carried over: technical storytelling, interviewing, and the ability to translate complexity across audiences.

But the conversation quickly moves into a bigger question: What happens to documentation when AI becomes another way users interact with a product?

We unpack headless CMS, structured content, APIs, and MCP in practical terms. Nico explains why separating content from presentation matters when that content may be consumed not only by websites and apps, but also by LLMs that interpret it for users or take action on their behalf.

That shift makes context, structure, and governance increasingly important. If AI becomes another interface to your product, the quality of the experience still depends on the quality of the information underneath it.

We also get into the tradeoffs: hallucinations, lower-quality AI-generated content, brand trust, data privacy, and a concern that gets less attention than job replacement—the fragmentation that comes from being expected to do more simply because AI makes us faster.

This conversation is ultimately about more than using AI to write documentation. It’s about what documentation becomes when AI starts consuming it.

Season 8 of Inside Tech Comm is sponsored by LavaCon. Use discount code ITC26 to save $200 on registration for LavaCon 2026.

Show Credits

• Intro and outro music - Az
• Audio engineer - RJ Basilio

Technical writers do work that can influence products, customers, and business outcomes. Yet we can still find ourselves described as the people who make things look good or “do the documentation.”

In this episode, I talk with Nibu Thomas about changing that narrative.

Nibu’s own career has moved through several S-curves—from manufacturing and quality-focused work to documentation leadership, marketing, and go-to-market support. We use that journey to explore what happens when you stop defining your career by the deliverables you produce and start thinking about the value you create.

A big part of that shift is storytelling. How do you tell the story of your career? How do you make your value visible on a resume when a hiring manager may be scanning hundreds of them? And how do you build a professional network before you actually need something from it?

We also talk about what AI changes for technical writers. As tools become better at generating and updating documentation, Nibu argues that writers need to move closer to customers and business outcomes—and think beyond producing more content.

Some highlights from our conversation:

• Finding the common thread across career transitions
• Moving beyond tools and deliverables when describing your work
• Using storytelling to communicate your professional value
• Building relationships outside your immediate professional circle
• Approaching networking with kindness rather than reciprocity
• Making your resume stand out when hiring managers have little time
• Connecting technical communication work to revenue and cost savings
• Moving closer to customers and product outcomes
• Rethinking the technical writer’s value as AI takes on more content work
• Treating yourself as the product you need to position

If you've ever struggled to explain what you bring to the table beyond “I write documentation,” this conversation offers another way to think about your career.

Season 8 of Inside Tech Comm is sponsored by LavaCon. Use discount code ITC26 to save $200 on registration for LavaCon 2026.

Show Credits

• Intro and outro music - Az
• Audio engineer - RJ Basilio

Video feels like the “obvious” way to teach software until you’re the one stuck updating walkthroughs after every release. We sit down with Sagar Garuda, founder and CEO of Zenious, to talk about the real bottleneck behind product education videos: the editing, the reviews, the sync work, and the high cost of keeping content current when a SaaS product changes fast.

We follow Sagar’s path from engineering to technical writing, then through customer education leadership at fast-growing startups, where onboarding speed and tribal knowledge become existential scaling problems. He explains how multiple teams describe the same product differently across the customer journey and why technical writers create the most value when they stop operating in silos and start orchestrating a single source of truth across help portals, knowledge bases, LMS content, and digital adoption platforms.

Then we get concrete about how Zenious approaches the workflow: record your screen, speak naturally, and let transcript-based editing handle polishing, tightening, and syncing audio to what’s happening on screen. We also explore why structured documentation matters more in the AI era, how “knowledge layers” power contextual AI, and where human judgment still beats automation when deciding what belongs in customer-facing content.

If you’re building a documentation strategy, scaling customer education, or trying to make video sustainable for your team, subscribe, share this with a content friend, and leave a review with your biggest challenge: what’s the one thing that keeps you from shipping more video?

Season 8 of Inside Tech Comm is sponsored by LavaCon. Use discount code ITC26 to save $200 on registration for LavaCon 2026.

Show Credits

• Intro and outro music - Az
• Audio engineer - RJ Basilio

What if we stopped thinking about AI simply as a tool for doing our existing work faster—and started treating it as a new material for designing experiences?

In this episode, I talk with Josh Clark and Veronica Kindred, co-authors of Sentient Design, about what happens when intelligence moves beyond the chatbot and becomes part of the interface itself.

Josh and Veronika define sentient design as the practice of creating intelligent interfaces that are aware of context and intent and can adapt to users in the moment. We explore what that looks like in practice, from dynamically assembled dashboards to AI agents that behave more like collaborators within an interface.

And for technical communicators, there’s an interesting implication: our ability to define context, instructions, rules, guardrails, and behavior could make us important contributors to these emerging experiences.

Want to explore the ideas further? Inside Tech Comm listeners can get 20% off Sentient Design from Rosenfeld Media with code SENTIENT-TECHCOMM through October 31, 2026.

Some highlights from our conversation:

• Moving from AI as a tool for production to a material for product
• What sentient design actually means—and what it doesn’t 
• Combining probabilistic AI with deterministic systems 
• How adaptive interfaces can respond to context without giving AI unlimited control 
• Why technical communicators may have a new audience: the AI systems themselves
• What Salesforce and Cisco are already experimenting with in adaptive interfaces 
• Why AI could change collaboration across content, design, development, and product 
• Making room for experimentation and “mad science” 
• Using defensive design to build trust and guardrails into AI experiences 
• Designing AI to express uncertainty instead of pretending to know everything 
• Why critical thinking and AI literacy may become more—not less—important 

Season 8 of Inside Tech Comm is sponsored by LavaCon. Use discount code ITC26 to save $200 on registration for LavaCon 2026.

Show Credits

• Intro and outro music - Az
• Audio engineer - RJ Basilio

We talk with Lindsey Rix about moving beyond AI anxiety and experimenting with what AI can actually make possible for technical writers.

Drawing from her presentation, Content Is the Strategy, Lindsey shares how she moved from experimenting with custom agents and AI skills to working with developer-adjacent tools, source code, and MCP connections. She explains why she starts with the problem rather than the tool, how AI is helping her gather and interpret information more efficiently, and why technical writers’ language, research, critical-thinking, and problem-solving skills may become even more valuable.

Some highlights from our conversation:

• Reframing AI from threat to tool through hands-on experimentation
• Using content standards, patterns, and style guidance to improve AI results
• Recognizing how technical writing skills translate to prompt engineering and AI workflows
• Learning new tools by building personal projects outside work
• Creating repeatable AI “skills” from real pain points and busywork
• Drafting from pull requests and source code using connectors and MCP
• Asking for read-only access and demonstrating value through small experiments
• Building resiliency by troubleshooting, iterating, and continuing to learn

Season 8 of Inside Tech Comm is sponsored by LavaCon. Use discount code ITC26 to save $200 on registration for LavaCon 2026.

Show Credits

• Intro and outro music - Az
• Audio engineer - RJ Basilio

We talk with Sharon Burton, editor of Women in Technical Communication, about how women’s stories reveal the real history of technical communication and why our work is bigger than “typing words.” We connect documentation to revenue, customer stickiness, and institutional knowledge while facing the disruption and cost realities of AI. 

Episode highlights:

• Sharon’s path into TechCom and how the book comes together 
• How the field flips from mostly men to mostly women over 50 years 
• Why AI changes workflows but does not replace task analysis and judgment 
• Tying documentation and user assistance to retention, adoption, and revenue 
• Why being left off the “team” slide hurts and how writers validate each other 
• Using conferences to learn the current language for proving value 
• Shared patterns for women in tech across cultures and generations 
• Documenting careers and decisions before retirements erase context 
• The pay gap still showing up in today’s data 

Season 8 of Inside Tech Comm is sponsored by LavaCon. Use discount code ITC26 to save $200 on registration for LavaCon 2026.

Show Credits

• Intro and outro music - Az
• Audio engineer - RJ Basilio