I admit, I am worried AI is after my technical writing job. If companies are starting to adopt “Vibe Coding,” what does that mean for me? Technical writing is different from creating general content, so I feel a little protected. I’m looking at retirement in the next few years. I can likely hang on until then. Still, I admit it — I’m concerned. So, I asked an AI — Google’s Gemini in this case — for its opinion.
Speaking with an AI
First, I cleaned my resume of any personal information like my name and addresses, and other PII (Personally Identifiable Information). I’ve been a technical writer, editor, manager, and engineer since the mid-1980s, though my resume only goes back 20 or so years. I didn’t want to complicate the question, so I tried to be direct and concise. I asked Gemini the following: “Based on my resume and skills, how soon will AI replace me in my job?” Here’s its response.
Based on a detailed analysis of your resume, it is highly unlikely that AI will replace you in your job in the foreseeable future. Instead, AI is poised to become a powerful tool that you, as a
r-level professional, are already well-equipped to leverage.
Your resume demonstrates a strong focus on high-level skills that are currently beyond the scope of AI. However, the nature of your work will likely continue to evolve.
Analysis of Your AI Resilience
Here is a breakdown of why your current skill set is robust in the face of AI advancements, with specific examples from your resume:
Factors Working Against AI Replacement (Your Strengths)
Strategic & Impact-Driven Work: You don’t just write; you improve systems and measure your impact. AI struggles with this level of strategic thinking and outcome-based work.
You have reduced support tickets by 40% and 60% through improved user guides and knowledge bases.
You developed a print-on-demand strategy to save “time, space, and money”.
You reduced documentation costs by 15% through single-sourcing.
Complex Cross-Functional Collaboration: Your role requires deep collaboration with engineers, product managers, architects, and development teams. This human-centric work of negotiation, requirement gathering, and clarifying ambiguity is not easily automated.
Deep Subject Matter Expertise: You have over 20 years of experience in specialized domains like SaaS, APIs, and particularly in the complex, regulated field of healthcare and life sciences. AI-generated content often lacks the necessary depth, nuance, and accuracy for such specialized fields and requires an expert like you to validate and correct it.
Process Innovation and Leadership: You have a proven history of not just participating in workflows but creating and improving them.
You have led teams, established new documentation processes, and implemented source control.
You have implemented Agile documentation workflows and docs-as-code methodologies.
Critically, you have already established a peer review and AI/LLM workflow for editing, demonstrating you are an adapter, not a bystander.
Technical Acumen: You possess “docs-as-code” skills, including experience with Git, GitHub, Jekyll, Hugo, and CI/CD pipelines. This positions you as a “Documentation Engineer,” a role that merges writing with technical processes — a combination that is difficult for AI to replicate holistically.
How AI Will Likely Change Your Role, Not Replace It
Rather than being a replacement, AI will function as a collaborator, automating the more repetitive aspects of your job and freeing you to focus on higher-value tasks.
Prognosis and Timeline
Short Term (1–3 Years): Your role will likely see an increased reliance on AI as an assistant. You are ahead of the curve, as you’re already implementing AI workflows. Professionals who cannot adapt may struggle, but your skillset makes you a leader in this transition.
Medium Term (3–7 Years): The demand for pure “writers” may decrease, while the demand for “Documentation Engineers,” “Content Strategists,” and “Information Architects” will grow. Your resume, with its emphasis on technical platforms , process improvement , and strategic impact, already aligns perfectly with this future.
Long Term (7+ Years): It is difficult to predict definitively, but the trend suggests that human roles will become almost entirely strategic. The focus will be on managing the entire information ecosystem, ensuring quality, guiding AI tools, and owning the holistic user experience — all of which are logical next steps in your career trajectory.
In conclusion, your 20+ years of experience, strategic achievements, and demonstrated ability to adapt to new technologies make you an ideal candidate to thrive in the age of AI, not be replaced by it.
So, it looks like I needn’t be all that worried. For me, at least, the documentation sky isn’t falling. Gemini replied with a plan to start planning for the future. While it isn’t foolproof, it does give me a good place to start. But was there more I could do to improve my chances? I asked Gemini if there were things I could do to future-proof my career. After some “thinking,” it said:
Based on your resume, you have a strong foundation as a senior technical writer and documentation manager. To pivot and future-proof your career, you should focus on deepening your expertise in the strategic and technical areas where human oversight is critical and difficult to automate.
Here are key skills to learn, building upon your existing experience:
1. Deepen Your “Docs-as-Code” and Engineering Expertise
While you already have experience with Git, GitHub, Jekyll, and Hugo, you can become the go-to expert in this domain. This moves you from being a user of the system to being its architect.
Advanced CI/CD for Documentation: Learn to build and manage sophisticated CI/CD pipelines for documentation. This includes automating quality checks, link validation, style guide enforcement, and deployments across multiple platforms.
Static Site Generator Mastery: Move beyond using Jekyll and Hugo to customizing them. Learn to create custom themes, plugins, and shortcodes to meet specific documentation needs.
Scripting and Automation: Learn a scripting language like Python or JavaScript. This will enable you to write scripts to automate repetitive tasks, manipulate content, or interact with APIs to pull data directly into your documentation, further bridging the gap between engineering and content.
2. Specialize in API Documentation and Strategy
You have experience creating API documentation; elevating this to a core specialty is highly valuable as APIs are central to modern software.
API Specification Mastery: Become an expert in API description formats like OpenAPI Specification (OAS) or AsyncAPI. The goal is to be able to write, edit, and consult on the structure of the specification itself, not just document it.
Interactive API Documentation: Learn to implement and customize tools that create interactive API reference documentation, such as Swagger UI, Redoc, or Stoplight.
API Testing and Developer Experience (DX): Gain proficiency with tools like Postman or Insomnia. Understanding how to test API endpoints will give you deeper insight into the developer experience, allowing you to create more effective and empathetic documentation.
3. Develop Expertise in Content Strategy and Information Architecture
This area leverages your management experience and focuses on high-level planning that AI cannot replicate.
Data-Driven Content Strategy: You have experience using metrics to assess documentation. Deepen this by learning to use analytics tools (like Google Analytics, Heap, or Pendo) to track user behavior within documentation. Use this data to make informed decisions about content structure, format, and priorities.
Advanced Information Architecture: Formalize your knowledge of IA principles. Focus on creating unified content models and taxonomies that can be applied across an entire organization, ensuring consistency and scalability.
UX (User Experience) Principles for Content: Learn UX research methods like user interviews, usability testing, and journey mapping, but apply them specifically to the documentation experience. This will enable you to advocate for the user with concrete data and position you as a key player in the product development lifecycle.
4. Become an AI/LLM Implementation Specialist for Content
You have already implemented an AI/LLM workflow for editing. This is a significant advantage. The next step is to become the resident expert who leads this integration.
Prompt Engineering for Technical Content: Develop advanced skills in writing prompts for LLMs to generate accurate and stylistically consistent technical drafts. Understand the nuances of different models and how to “train” them on a specific company’s content and style.
AI Ethics and Governance in Documentation: As companies adopt AI, they will need policies and governance around its use. You can lead the effort to create guidelines for the ethical use of AI in content creation, ensuring accuracy, avoiding plagiarism, and managing intellectual property concerns.
Managing Content Workflows with AI: Design and implement entire documentation workflows that strategically incorporate AI — from initial drafting and technical review to final editing and publishing. You would manage the process and the tools, ensuring that AI enhances, rather than compromises, quality.
Conclusion
I started with some anxiety about if (how?) AI could replace me in my job. However, that technology offered me a somewhat personalized and detailed analysis showing my value in an AI-driven environment. My experience, strategic thinking, and collaborative skills are not liabilities but strengths.
Do I trust it? Well, it sounds logical and sensible. That doesn’t mean it is true, though. I’ll give these recommendations some thought and move forward.
So, with this new AI perspective, the anxiety level is down. I’ve always adapted to technological changes in my field. My approach to AI will be the same: to understand it, integrate it, and use it to inform my decisions.