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AI Summary
- Technical writers articulate complex concepts simply and ensure information is accurate. Their work expanded with software documentation, product documentation, project management, software products, and corporate governance.
- GenAI provides tools to solve traditional problems effectively and efficiently; claims that it will make technical writing obsolete are described as baseless.
- Because GenAI may hallucinate, technical writers must evaluate GenAI-based agents, create ground truth, assess responses, and learn frameworks such as OpenAI Evals and RAGAS.
- They must produce accurate, up-to-date content; undertake data analytics including topical analysis, citation analysis, search volume, and feedback analysis; and use these insights to improve content and business outcomes.
- They should collaborate with customer-facing teams to identify queries, source FAQs, address knowledge gaps, and tailor content. Technical writers must modernize workflows with GenAI and strengthen GenAI and data analytics skills.
AI-generated content. It may contain errors.
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Technical writers are a rare breed of professionals who are capable of articulating complex concepts in simpler terms. Being a technical communicator comes with a huge responsibility of ensuring that the information they produce is accurate. Technical writers thrived when the industrial era shifted to a knowledge-based economy where the need for software documentation and product documentation was increasing. The internet boom propelled the need for technical writing profession in the areas of
- Project management – to gather all information about the project in terms of purpose, scope, technical implementation, risk, learnings, and so on
- Software product document – to gather all information about a software product, functionality in terms of product features, and so on
- Corporate governance – to gather all tribal knowledge of their organization and preserve its institutional memory
Technical writing professionals were trained in information architecture, content design, design thinking, agile, workflow, data, and analytics, in addition to basic writing skills. Technical writers have built experience in many frameworks for content creation and how to deliver documentation in an agile way! However, all this foundational knowledge is being challenged given the emergence of Generative Artificial Intelligence (GenAI) capabilities.
Technical Writer with GenAI
Being a technical writer in a world dominated by GenAI tools and capabilities is a unique experience, as technical writers feel like superheroes! Given that GenAI offers many solutions in its arsenal, technical writers now have access to different tools to solve traditional problems both effectively and efficiently! Technical writers need to embrace this GenAI technology and have a mindset that this technology is going to assist them in newer ways. The anxiety around this technology that is making the technical writing profession obsolete is a baseless claim!
New sets of responsibilities for technical writers
Being a technical writer in the GenAI era comes with new sets of responsibilities for which many technical writers are not prepared! Given that GenAI is still in its nascent stage, it is prone to hallucination, i.e., it might produce unfactual information sometimes. Building trust-worthy content and helping GenAI-based agents produce reliable responses has become a new responsibility added to technical writers’ portfolios. It is time to learn new skills and take up new responsibilities to thrive in this GenAI era. Let’s look at those new responsibilities.
1. Evaluating responses of GenAI-based agents
If your organization has deployed a GenAI-based assistive search engine that uses semantic similarity to create responses for your customer prompts, then this additional responsibility of evaluating the GenAI-based assistive search engine falls on the technical writer! If responses generated by GenAI-based assistive search are not powered by trustworthy content, then it tarnishes the reputation of your brand, and eventually, your customers will churn! This is where the technical writers come in! Given that technical writers understand your product and services holistically, they are better suited to be gatekeepers of trustworthy content being fed into GenAI-based assistive search and evaluate its responses.
The technical writers need to learn about evaluation frameworks such as OpenAI Evals and RAGAS frameworks. They need to build new skills on how to create ground truth and assess the responses of GenAI-based search engines’ response against the ground truth.
Also Read: Structuring Tables in Technical Writing for GenAI-based agents
2. Producing trusted content
To ensure that GenAI-based search engines produce accurate responses, the underlying content needs to be always accurate and up to date. If your organization is highly agile and product updates are happening every week, it is high time to ensure that software documentation is always kept up to date. This helps GenAI-based agents to serve reliable information to your customers. This also helps with the change management aspect for your customers to adopt semantic search engines powered by GenAI
3. Undertaking Data Analytics
Technical writers need to sharpen their data and analytics skill sets to master the art of producing actionable insights. These insights can help improve business outcomes and content quality. Given that GenAI produces a lot of text-based analytics, it is important to know more about
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- Topical analysis refers to the process of analyzing questions (prompts) to determine the topics they cover. This allows technical writers to get into the general themes customers are most frequently searching for. This analysis can be used to identify trends, understand customer needs, and guide content creation or product improvements.
- Source articles that are used for creating a response via GenAI are displayed as citations. These citations provide a trust factor to the customers. If citation articles for each response can be analyzed holistically, then we can understand the high-value content of your knowledge base.
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- Search volume, along with positive and negative feedback sliced across different time dimensions, shows the usage statistics of your GenAI assistive search tool. Successful responses and “unanswered question” responses show the adoption of the GenAI assistive search tool as a primary means to interact with your knowledge base.
Also read: Data Analytics Skills for Technical Writers
4. Collaboration with customer-facing teams
Collaboration with internal teams such as the customer support team, customer success team, and so on would help technical writers understand a rich set of queries that existing customers and new prospects need. This helps technical writers to tailor content to suit their needs. Moreover, the FAQs for each knowledge base article can be sourced during regular interactions with customer-facing teams. Technical writers need to strengthen their internal collaboration to address knowledge gaps in their content. More importantly, this collaboration leads to a rich and creative knowledge experience for new prospects. This helps to solidify the value proposition of the technical writing team.
Also read: Refactoring content for GenAI readiness: Best Practices and Guidelines
Closing remarks
To thrive in the GenAI world, technical writers need to adapt and have a positive mindset in terms of embracing new technological capabilities. This means technical writers will have to take on new responsibilities to efficiently deliver their services to their organization. Technical writers need to modernize all their frameworks and processes with the GenAI toolkit to increase their productivity and focus on producing business outcomes. To take up new responsibilities, technical writers need to upskill themselves on the technical capabilities of GenAI and sharpen their data analytics skills.
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