Just Enough AI, Part 1: AI for Search and Discoverability
Blog post from ReadMe
Technical writers contribute institutional knowledge, product-testing experience, and user understanding that generative AI cannot fully replace, but AI can supplement documentation workflows when used thoughtfully. The first installment of a three-part series focuses on improving documentation search and discoverability, areas where AI performs well by summarizing, structuring, and retrieving information across large bodies of content. It recommends AI-powered documentation search tools such as ReadMe’s Ask AI, which can be trained on a company’s content, configured for tone, detail, models, and restricted topics, and monitored through question and response analytics. The piece also emphasizes making documentation accessible to AI systems through agent-friendly features such as LLMs.txt files, link headers, agent skills, and direct MCP server connections for coding tools, helping those tools use accurate API details rather than inferred information.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| MCP | 3 | 8,729 | 854 | 211 | -20% |
| AI Coding Assistant | 2 | 1,513 | 470 | 139 | -19% |
| LLM | 1 | 5,068 | 1,020 | 229 | -34% |
Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.