# Mintlify Blog The latest updates and insights from Mintlify This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Rise of the Knowledge Engineer DevFeed: [Rise of the Knowledge Engineer]() Original publisher: [Read original article]() Author: David Isquick Published: 2026-09-16T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [Documentation](), [Artificial Intelligence](), [AI-assisted coding](), [Users]() Tags: [agents](), [ai](), [ai-trends](), [api](), [developers](), [documentation](), [knowledge-base](), [operational](), [source-of-truth](), [support](), [workflows]() ### AI overview The article examines the rise of the knowledge engineer as companies increasingly serve AI agents that read documentation, compare products, solve support problems, and perform tasks. It argues that organizations need operating systems and processes to keep knowledge accurate, accessible, consistent, and retrievable, because incorrect information can spread through generated code, support responses, and automated workflows. ### Source excerpt Agents are one of the largest audiences for company knowledge, accounting for 66% of measured web traffic across documentation powered by Mintlify. The emerging role responsible for keeping that knowledge accurate and retrievable is the knowledge engineer. ## Highlights from the 2026 State of Knowledge Report DevFeed: [Highlights from the 2026 State of Knowledge Report]() Original publisher: [Read original article]() Author: Lauren Volpi Published: 2026-09-16T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [Documentation](), [Artificial Intelligence](), [HTML](), [Website](), [MCP]() Tags: [2026](), [ai](), [ai-agents](), [ai-trends](), [documentation](), [llms-txt](), [markdown](), [mcp](), [report]() ### AI overview Mintlify's 2026 State of Knowledge Report examines how AI agents are changing documentation readership and access. It reports that agent requests exceeded human page loads on Mintlify-powered sites in August, with many agents using Markdown, llms.txt, agent skills, and MCP tool calls. Controlled tests across 20 documentation sites found that linking Markdown pages to llms.txt improved agent navigation and reduced token consumption. ### Source excerpt AI agents overtook humans as the primary readers across Mintlify-powered sites. In August alone, agents made 257 million web requests compared to 131 million human page loads, which means agent traffic now outnumbers human traffic by nearly 2:1. ## Mintlify rebuilds automations around pre-built templates for common use cases DevFeed: [Mintlify rebuilds automations around pre-built templates for common use cases]() Original publisher: [Read original article]() Author: Patrick Foster Published: 2026-09-15T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [Automation](), [Documentation](), [changelog](), [Pull Request](), [Markdown](), [YAML]() Tags: [announcements](), [automation](), [changelog](), [docs](), [documentation](), [execution](), [markdown](), [prompt](), [quality](), [rest]() ### AI overview Mintlify rebuilt its automations around pre-built templates for common use cases, including syncing content with code changes, generating changelogs, and improving documentation from user feedback and support signals. Custom prompts remain available for specialized tasks. ### Source excerpt We redesigned automations for quicker setup with pre-built automations optimized for common use cases. Choose the right automations for your project and you're set. No context engineering required. ## Mintlify introduces fixed, outcome-based pricing for AI actions DevFeed: [Mintlify introduces fixed, outcome-based pricing for AI actions]() Original publisher: [Read original article]() Author: Han Wang Published: 2026-09-08T00:00:00Z Content type: release Language: en Sources: [Mintlify Blog]() Topics: [Artificial Intelligence](), [Automation](), [Documentation](), [Slack]() Tags: [agent](), [ai](), [announcements](), [automation](), [pricing](), [slack](), [updates]() ### AI overview Mintlify announces fixed credit prices for AI actions, charging for assistant answers and automation updates while making unsuccessful answers and automations with nothing to update free. The company says plan allowances and per-credit prices remain unchanged, and reports that most teams will use the same or fewer credits. ### Source excerpt Every AI action in Mintlify now has a fixed credit price, and you only pay when we deliver a result. Assistant answers and automation updates cost credits. Everything else is free. ## Scaling llms.txt with a Hierarchy of Files DevFeed: [Scaling llms.txt with a Hierarchy of Files]() Original publisher: [Read original article]() Author: Kyan Yang Published: 2026-09-01T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [Documentation](), [navigation](), [Website]() Tags: [agents](), [context-window](), [documentation](), [engineering](), [files](), [generation](), [navigation]() ### AI overview Mintlify rebuilt llms.txt generation as a hierarchy of files to keep large documentation sites within the 100,000-character limit while preserving access to pages. In tests across 200 tasks on ten documentation sites, the improved version completed tasks 52.1% faster and used 44.8% fewer tokens. ### Source excerpt Large documentation sites were hitting Mintlify's 100,000-character llms.txt limit and omitting pages. We rebuilt generation as a hierarchy of files so agents can reach every page without loading the entire index. ## Mintlify introduces instant rollbacks for Enterprise deployments DevFeed: [Mintlify introduces instant rollbacks for Enterprise deployments]() Original publisher: [Read original article]() Author: David Isquick Published: 2026-08-31T00:00:00Z Content type: release Language: en Sources: [Mintlify Blog]() Topics: [Deployment](), [audit](), [Pull Request](), [GitHub](), [GitLab](), [bitbucket]() Tags: [access-control](), [announcements](), [audit](), [configuration](), [deployment](), [pull-request](), [rollback]() ### AI overview Mintlify has introduced instant rollbacks for Enterprise customers, allowing them to restore one of their last 10 successful builds from the dashboard in seconds. Rollbacks are recorded in audit logs and currently support non-authenticated pages. ### Source excerpt Instant rollbacks are now live for Mintlify Enterprise customers. You can roll back to a known good deployment in seconds, without waiting on a full rebuild. ## Your agent can sign up for Mintlify fully on its own DevFeed: [Your agent can sign up for Mintlify fully on its own]() Original publisher: [Read original article]() Author: Kyan Yang Published: 2026-08-12T00:00:00Z Content type: release Language: en Sources: [Mintlify Blog]() Topics: [Command-line interface](), [Documentation](), [AI-assisted coding](), [Automation](), [Development]() Tags: [agent](), [announcements](), [automation](), [cli](), [coding-agents](), [deploy](), [documentation](), [setup](), [terminal]() ### AI overview Mintlify's mint signup command lets coding agents create an account and set up a documentation project from the CLI without opening a browser. The article describes a terminal-first workflow covering signup, verification, authentication, project scaffolding, preview, validation, custom domains, and deployment. ### Source excerpt Mintlify's mint signup command creates an account from the CLI so coding agents can set up docs without a browser. Every step from signup to deploy works from the terminal. ## Introducing Mintlify Index DevFeed: [Introducing Mintlify Index]() Original publisher: [Read original article]() Author: Kyan Yang Published: 2026-08-06T00:00:00Z Content type: release Language: en Sources: [Mintlify Blog]() Topics: [Documentation](), [AI-assisted coding](), [API](), [MCP](), [MCP Server]() Tags: [announcements](), [api](), [beta](), [coding-agents](), [documentation](), [experiment](), [mcp](), [mcp-server](), [retrieval]() ### AI overview Mintlify introduces Mintlify Index, a retrieval layer that aggregates documentation from 9,000 Mintlify-powered sites for coding agents. It routes documentation-related queries to optimized retrieval and other queries to an external web search provider, with fallback between sources. The article reports an experiment in which Index was preferred in 96 of 150 implementation-planning tasks and completed tasks 48% faster end-to-end, with higher factual correctness and citation support and fewer critical errors. Mintlify launched Index as a free beta with an API and MCP server. ### Source excerpt Mintlify Index aggregates the docs of 9000 Mintlify-powered documentation sites into a natural language retrieval layer for coding agents. ## The state of docs traffic: a 2026 midyear report DevFeed: [The state of docs traffic: a 2026 midyear report]() Original publisher: [Read original article]() Author: Kyan Yang Published: 2026-07-29T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [Documentation](), [Model Context Protocol](), [Logging](), [Server]() Tags: [2026](), [agent](), [ai-trends](), [clients](), [docs](), [mcp](), [report](), [retrieval](), [search](), [servers](), [tool]() ### AI overview Mintlify's 2026 midyear report examines how agents access documentation. It reports that agents represented 66% of measured web traffic in July, with direct machine routes becoming more common, and separately analyzes MCP assistant responses and tool calls. ### Source excerpt Agents now account for 66% of measured web-traffic across docs powered by Mintlify, with July logging over 213 million agent web requests and 105 million human page loads as the month comes to a close. ## Docs URL Benchmark: Markdown & llms.txt \> HTML DevFeed: [Docs URL Benchmark: Markdown & llms.txt \> HTML]() Original publisher: [Read original article]() Author: Aadit Shah Published: 2026-07-17T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [Documentation](), [Benchmark](), [Artificial Intelligence](), [Claude](), [codex]() Tags: [ai-agents](), [benchmark](), [claude](), [codex](), [docs](), [engineering](), [html](), [markdown]() ### AI overview Mintlify benchmarked HTML, plain markdown, markdown linking to llms.txt, and markdown with llms.txt inlined across 2,400 runs on 20 documentation sites. The results found that linking to llms.txt eliminated most agent 404s without added cost. ### Source excerpt We benchmarked four ways to serve documentation to AI agents (HTML, plain markdown, markdown linking to llms.txt, and markdown with llms.txt inlined) across 2,400 runs on 20 Mintlify docs sites, and found that a single link to llms.txt eliminates most agent 404s at no added cost. ## How Claude Code's documentation team makes feedback actionable with Mintlify DevFeed: [How Claude Code's documentation team makes feedback actionable with Mintlify]() Original publisher: [Read original article]() Author: Ethan Palm Published: 2026-06-25T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [Claude Code](), [Documentation](), [anthropic](), [Claude]() Tags: [agents](), [anthropic](), [automate](), [best-practices](), [claude-code](), [documentation](), [observability]() ### AI overview Anthropic's Claude Code documentation team uses Mintlify and Claude to turn quantitative and qualitative user feedback into actionable documentation improvements. The article also discusses observability challenges and the value of user comments as a feedback signal. ### Source excerpt Anthropic's Technical Content Engineer for Claude Code shares how she uses Mintlify and Claude to automate documentation improvements from user feedback. ## Docs as an abstraction layer for coding agents DevFeed: [Docs as an abstraction layer for coding agents]() Original publisher: [Read original article]() Author: Han Wang Published: 2026-06-08T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [Documentation](), [AI-assisted coding](), [Claude Code](), [Model Context Protocol (MCP)](), [Development]() Tags: [ai-coding-agents](), [ai-trends](), [claude](), [claude-code](), [coding-agents](), [docs](), [mcp](), [performance](), [tokens]() ### AI overview The article describes controlled experiments testing structured Mintlify documentation as an abstraction layer for coding agents working in large codebases. It reports more precise answers, better discoverability, lower token consumption, and faster task completion than a no-docs baseline. ### Source excerpt A large engineering org ran controlled experiments to measure how structured Mintlify docs affect agent performance on massive codebases. The results: 64% more precise, 39% more discoverable, half the tokens, 1.5x faster. ## Your documentation is a demand channel DevFeed: [Your documentation is a demand channel]() Original publisher: [Read original article]() Author: Lauren Volpi Published: 2026-06-04T00:00:00Z Content type: opinion Language: en Sources: [Mintlify Blog]() Topics: [Documentation](), [Search engine optimization (SEO)](), [Software as a service]() Tags: [article](), [best-practices](), [developer](), [documentation](), [marketing](), [seo]() ### AI overview This article argues that public, well-structured documentation can function as a high-intent demand channel for developer-facing and B2B companies. It recommends tracking documentation traffic and maintaining resources such as quickstarts, API references, pricing pages, changelogs, comparison guides, and migration guides. ### Source excerpt Documentation is often the highest-traffic, highest-intent surface in your entire funnel. It's the first place a buyer visits before trying your product. It's where agents surface and push your product to prospects. ## Why content infrastructure involves more than rendering Markdown DevFeed: [Why content infrastructure involves more than rendering Markdown]() Original publisher: [Read original article]() Author: Han Wang Published: 2026-06-03T00:00:00Z Content type: opinion Language: en Sources: [Mintlify Blog]() Topics: [Markdown](), [Documentation](), [hosting](), [Command-line interface](), [ci]() Tags: [ai-trends](), [ci](), [cli](), [docs](), [hosting](), [markdown]() ### AI overview This opinion article argues that rendering Markdown is only a small part of building content infrastructure. It describes the additional work involved in keeping documentation current, providing useful search, and supporting web, API, CLI, and CI-based workflows, while presenting Mintlify as a hosted alternative. ### Source excerpt Mintlify might look like a Markdown hosting service from the outside. But the build versus buy question for content infrastructure goes much deeper than rendering Markdown. ## Tokenmaxxing: one AI budget, four jobs DevFeed: [Tokenmaxxing: one AI budget, four jobs]() Original publisher: [Read original article]() Author: Shawn Lestage Published: 2026-05-25T00:00:00Z Content type: opinion Language: en Sources: [Mintlify Blog]() Topics: [Artificial Intelligence](), [Claude Code](), [cursor](), [pull-requests]() Tags: [ai](), [ai-trends](), [claude](), [claude-code](), [cost](), [cursor](), [product](), [pull-requests]() ### AI overview The article presents a framework for evaluating AI token spending by mapping Credits to familiar P&L categories such as R&D, COGS, sales and marketing, and retention. It argues that separating these costs helps companies assess their relationship to engineering output, support costs, customer retention, and revenue. ### Source excerpt Every company is now paying for AI tokens, but few can draw a clean line from that spend to business outcomes. Here's a framework that maps AI Credits to the P&L categories finance teams already understand. ## 22 UX improvements to the web editor DevFeed: [22 UX improvements to the web editor]() Original publisher: [Read original article]() Author: Dmytro Tovstokoryi Published: 2026-05-04T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [User experience (UX)](), [Web](), [Documentation]() Tags: [docs](), [editor](), [ux](), [ux-improvements](), [web]() ### AI overview Mintlify describes 22 UX improvements to its web editor, including visual diffs, PR title and description generation, improved drag-and-drop editing, grouped block operations, block conversion, a redesigned slash menu, and inline emoji suggestions. ### Source excerpt A round-up of the UX improvements coming to Mintlify's web editor. ## Introducing the Mintlify Help Center Starter Kit DevFeed: [Introducing the Mintlify Help Center Starter Kit]() Original publisher: [Read original article]() Author: Hahnbee Lee Published: 2026-05-01T00:00:00Z Content type: release Language: en Sources: [Mintlify Blog]() Topics: [Support](), [Artificial Intelligence](), [Documentation](), [Slack]() Tags: [ai](), [announcements](), [documentation](), [slack](), [support]() ### AI overview Mintlify introduces a Help Center starter kit with an AI assistant that answers questions from published documentation, provides citations and source links, accepts additional context such as files and code, and routes unanswered questions to support email. The release also highlights a web editor and Slack-based knowledge capture. ### Source excerpt Help centers are the first line of defense for customer support. The new Mintlify Help Center starter kit and AI ticket deflection make it faster than ever to launch one. ## Introducing the collaborative editor built for teams and agents DevFeed: [Introducing the collaborative editor built for teams and agents]() Original publisher: [Read original article]() Author: Hahnbee Lee Published: 2026-04-29T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [Documentation](), [Git](), [GitHub](), [developer tooling]() Tags: [announcements](), [browser](), [collaboration](), [editor](), [git](), [teams](), [workflow]() ### AI overview Mintlify introduces a collaborative editor that combines browser-based WYSIWYG editing, live collaboration, and git synchronization. It supports contributors beyond engineering while preserving a git-native workflow for developer users. ### Source excerpt A new editing experience that brings live collaboration, git sync, and WYSIWYG editing into one workflow for your whole team. ## Agent Score evaluates whether documentation is ready for AI agents DevFeed: [Agent Score evaluates whether documentation is ready for AI agents]() Original publisher: [Read original article]() Author: Ethan Palm Published: 2026-04-27T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [AI Agent](), [Documentation](), [Developer experience](), [AI-assisted coding](), [observability](), [Authentication]() Tags: [agent](), [ai-agent](), [announcements](), [coding-agents](), [documentation](), [observability](), [technical-writing]() ### AI overview Mintlify introduces Agent Score, a free tool that evaluates documentation against 29 checks for agent readiness. It assesses discoverability, Markdown availability, page size, content structure, URL stability, observability, and authentication using the Agent-Friendly Documentation Spec and additional checks. ### Source excerpt An AI agent is reading your documentation right now. How well is it doing? We built a free tool to check how agent-ready your content is based on the agent-friendly documentation spec. ## Mintlify raises $45M Series B led by Andreessen Horowitz and Salesforce Ventures DevFeed: [Mintlify raises $45M Series B led by Andreessen Horowitz and Salesforce Ventures]() Original publisher: [Read original article]() Author: Han Wang Published: 2026-04-14T00:00:00Z Content type: release Language: en Sources: [Mintlify Blog]() Topics: [Documentation](), [Artificial Intelligence](), [Software]() Tags: [agents](), [ai](), [announce](), [announcements](), [documentation](), [funding](), [investors](), [series-b]() ### AI overview Mintlify announces a $45 million Series B led by Andreessen Horowitz and Salesforce Ventures, bringing its total funding to $67 million. The company says the funding will support its documentation platform and its mission to make product knowledge understandable and discoverable by AI agents. ### Source excerpt We're thrilled to announce our $45M Series B round, led by Andreessen Horowitz and Salesforce Ventures, and joined by existing investors including Bain Capital Ventures, Y Combinator, and others. ## 5 things you didn't know you could do in the Mintlify web editor DevFeed: [5 things you didn't know you could do in the Mintlify web editor]() Original publisher: [Read original article]() Author: Peri Langlois Published: 2026-04-13T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [Documentation](), [Visual Studio Code](), [MDX](), [Artificial Intelligence](), [browser](), [Git](), [Code]() Tags: [ai](), [best-practices](), [browser](), [code](), [docs](), [editor](), [git](), [how-to](), [markdown](), [web]() ### AI overview This article presents five Mintlify web editor features that help teams create, edit, review, and reorganize documentation in the browser without relying on an IDE, Git commands, or deployment pipelines. It highlights suggesting mode with comments, navigation restructuring, inline AI, live preview, and visual/Markdown switching. ### Source excerpt The Mintlify web editor can do more than you think, here are five features that make it easy for your whole team to contribute to docs. ## The improved Mintlify CLI DevFeed: [The improved Mintlify CLI]() Original publisher: [Read original article]() Author: Han Wang Published: 2026-04-07T00:00:00Z Content type: release Language: en Sources: [Mintlify Blog]() Topics: [Command-line interface](), [Documentation](), [Terminal](), [AI-assisted coding](), [Tooling](), [Claude Code](), [Development](), [cursor]() Tags: [announcements](), [claude-code](), [cli](), [coding-agents](), [cursor](), [documentation](), [terminal](), [tooling]() ### AI overview Mintlify announces an expanded CLI that supports documentation analytics, structured output for piping data into coding agents, and CLI-based authentication. The update also adds search and the AI assistant to local previews. ### Source excerpt A new CLI revamp that brings the Mintlify platform interface closer to the terminal. ## Docs on autopilot: From zero to self-maintaining with Mintlify DevFeed: [Docs on autopilot: From zero to self-maintaining with Mintlify]() Original publisher: [Read original article]() Author: Peri Langlois Published: 2026-04-03T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [Documentation](), [GitHub](), [API]() Tags: [audits](), [best-practices](), [broken-links](), [changelog](), [deprecated](), [docs](), [documentation](), [feature](), [features](), [generate](), [github](), [pull-request]() ### AI overview Mintlify presents auto-generated documentation and Automations that can create a docs site from a GitHub repository and keep documentation updated as code changes. Automations can sync docs after pushes, generate changelogs, audit documentation, and draft pages for new features. ### Source excerpt How Mintlify's auto-generated docs and automations combine to take documentation from nonexistent to self-maintaining. ## The state of agent traffic in documentation (March 2026) DevFeed: [The state of agent traffic in documentation (March 2026)]() Original publisher: [Read original article]() Author: Han Wang Published: 2026-04-03T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [Documentation](), [ai-coding](), [Claude Code](), [cursor](), [Cloudflare](), [browsers]() Tags: [2026](), [agent](), [agents](), [ai](), [ai-agents](), [ai-coding](), [ai-coding-agents](), [ai-trends](), [analysis](), [browsers](), [caveat](), [claude-code](), [cloudflare](), [cursor](), [documentation](), [edge](), [firefox](), [http]() ### AI overview Mintlify analyzes 30 days of Cloudflare traffic across its documentation sites and finds that AI coding agents accounted for 45.3% of requests, nearly matching traditional browser traffic at 45.8%. Claude Code and Cursor generated 95.6% of identified AI-agent traffic, while OpenAI Codex could not be distinguished because it does not provide an identifying user-agent header. ### Source excerpt An analysis of 30 days of Mintlify documentation traffic, broken down by AI agents, browsers, and other sources. [Next page]()