Beyond static docs: trends in documenting software solutions and their impact on the tooling

whoami — ● Lana Novikova ○ Technical writer with 10+ years of experience ○ Shifting to the product management ○ Developing product for documentarians by documentarians #Writerside

5 minute introduction to Trend watching ● What is Trend Watching? ○ Identification of long-term trends impacting industries. ○ Helps anticipate changes and shape strategic decisions.

Anatomy of trend Weak signal Driver Wildcard Trend A significant dynamic of change A new or early indication of future change Unexpected and high-impact events A measure that has been steadily changing

Diffusion of innovation

Gartner hype curve

Gartner hype curve

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Documentation tools market state ● Growing competition in specialized documentation tools ● Increased focus on user experience and engagement ● Rise of AI-first documentation platforms ● Emphasis on integration capabilities ● Shift towards more dynamic and adaptive content delivery systems ● More specialisation

Why documentation is evolving ● Shifting user expectations ● Technological disruption ● Evolving business needs ● Broader cultural shifts

Trends

Trend: Personalization and adaptive content ● Description: Documentation adjusts in real-time based on user interaction, creating a unique journey for each user. ● Signals/drivers: ○ Development of Generative AI, specifically models that understand context — such as OpenAI’s Codex or Google’s BERT — can track user behavior and adapt responses based on previous interactions ○ More synergy between cognitive science/behavioral science and software/tech comm ● Need: Customization based on user’s tech stack, learning style, and difficulty level. Personalization

Trend: Personalization and adaptive content ● Description: Documentation adjusts in real-time based on user interaction, creating a unique journey for each user. ● Signals/drivers: ○ Development of Generative AI, specifically models that understand context — such as OpenAI’s Codex or Google’s BERT — can track user behavior and adapt responses based on previous interactions ○ More synergy between cognitive science/behavioral science and software/tech comm ● Need: Customization based on user’s tech stack, learning style, and difficulty level. ● (counter) Weak signal: Ethical challenges and user reluctance towards over-personalisation and sharing data with AI Personalization

Trend: Cloud-based and collaborative tools ● Description: Cloud-based documentation tools have transformed the way teams work by making it easier to create, access, and collaborate on documents from anywhere, in real time. ● Signal: More documentation tools are cloud-based, supporting real-time collaboration. ● Driver: ○ Notion, Confluence, and Google Workspace have popularized the model of collaborative, cloud-based workspaces ○ Internet access and mobile networks development ● Need: Ensure accessibility and streamline teamwork for geographically dispersed teams and team members with various levels. Simplicity

Trend: Data-driven and analytics-enabled documentation ● Description: Data-driven documentation tools incorporate built-in analytics, user behavior tracking, and content performance metrics to help teams understand how users interact with documentation. ● Signals: Platforms like Google Analytics, Hotjar, and Pendo are increasingly integrated with documentation portals. ● Drivers: ○ Organizations are prioritizing data-driven approaches across all departments (marketing, support, HR). ○ Advances in AI and machine learning make it easier to analyze large datasets and uncover patterns. ● Need: Understand user behavior and improve content based on data, coming up with the framework for applying analytics and data to the documentation effectiveness AI Personalization

Trend: Data-driven and analytics-enabled documentation ● Description: Data-driven documentation tools incorporate built-in analytics, user behavior tracking, and content performance metrics to help teams understand how users interact with documentation. ● Signals: Platforms like Google Analytics, Hotjar, and Pendo are increasingly integrated with documentation portals. ● Drivers: ○ Organizations are prioritizing data-driven approaches across all departments (marketing, support, HR). ○ Advances in AI and machine learning make it easier to analyze large datasets and uncover patterns. ● Need: Understand user behavior and improve content based on data, coming up with the framework for applying analytics and data to the documentation effectiveness ● (counter) Weak signal: Data fatigue (too many metrics) and integration hurdles (especially for desktop tools) AI Personalization

Trend: New era in search and content findability ● Description: Search and content findability are evolving beyond simple keyword-based search engines to systems that understand user intent and context. ● Signal: Chatbot-like interfaces and conversational AI systems are being integrated into documentation tools, enabling users to “chat” with the documentation. ● Driver: ○ Major advancements in conversational AI, particularly with models like GPT-4 and BERT ○ Popularity of Perplexity, You, and the recent release of SearchGPT ○ Rise of self-service support ● Need: Users need quick, accurate access to specific content within extensive documentation. They want to find relevant information without needing to know precise terminology or navigate multiple layers. AI

Trend: Notebooks and interactive documentation ● Description: Notebook-like interactive documentation transforms traditional documentation into an experience where users can not only read content but also execute code, interact with live data, and explore real-world examples within the documentation itself. ● Signal: Platforms like Jupyter Notebooks, JetBrains Datalore, and Google Colab have popularized the notebook format, where code, visualizations, and text can coexist in an interactive environment ● Drivers: ○ Users want to test code and see immediate results ○ Development of cloud-based and remote environments ● Need: Blend learning and doing, creating hands-on documentation experiences without requiring users to set up local environments Hybridisation

Trend: Community-Driven Content Creation ● Description: Community-driven content creation leverages the collective expertise and insights of users, developers, and subject matter experts to create, improve, and expand documentation. ● Signals: ○ Platforms like Stack Overflow, Reddit, and Quora showcase the power of crowdsourced information and community expertise. ○ People trust peer-to-peer information more. ● Driver: ○ Needs and regulations requiring localisation and accessibility. ● Need: Community-driven documentation allows users to help each other, reducing the burden on support teams. Users who contribute valuable content are motivated by the opportunity to share their expertise and gain recognition. Co-Creation

Trend: Sustainability in documentation • Description: This trend focuses on creating eco-friendly, minimalist documentation that uses fewer digital resources, reduces energy consumption, and supports corporate sustainability goals. • Signals: – Many companies have set ambitious sustainability targets, driving changes across all aspects of operations, including digital resources. – Many companies have adopted net-zero carbon emissions targets. – Concepts like “green coding” (optimizing code for minimal energy use) are gaining traction and can extend to documentation practices as well. • Drivers: – Regulations: Some countries are implementing or considering regulations related to digital sustainability and energy use. • Need: Alignment with the larger organizational mission. Naturality

Weak signals A weak signal is an indicator of a potentially emerging issue, that may become significant in the future. Weak signals supplement trend analysis and they can be used to expand on alternate futures. Bridging between formats with a unified Abstract Syntax Tree (AST) Transparent and trustworthy (AI) docs Demand for more semantics?

Is your documentation strategy evolving as fast as the technology it describes?

Personalisation Cloud-first Data-driven AI-based search Notebook-like Community-driven AI-adjusts information for personal preferences of the reader Cloud-first, in-browser tools are getting popular Tools incorporate built-in analytics, user behavior tracking, and content performance metrics Search and content findability are evolving beyond simple keyword-based search engines to systems that understand user intent and context Docs being transformed into an experience where users can not only read content but also execute code. Community-driven content creation leverages the collective expertise and insights of users. TRENDS this is the slide to make a photo of

Thank you! Questions? — @_Unsolved_ Please fill a small anonymous survey @lananovikova@techhub.social @lananovikova10 @svetlana-novikova

More on trend hunting » Trendhunter report: https://go.trendhunter.com/2024-trend-report » Trends, Change Drivers and Megatrends: Understanding the Big Picture and Path-Dependencies https://www.futuresplatform.com/blog/megatrends-trends-a nd-change-drivers-the-larger-picture-and-path-dependencies » Wildcards of the future: https://fjintelligence.com/wildcards-of-the-future-preparing-f or-the-unpredictable/