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Mintlify Blog

22 UX improvements to the web editor Introducing the Mintlify Help Center Starter Kit Introducing the collaborative editor built for teams and agents Workflows, rebuilt Is your documentation agent-ready? Mintlify raises $45M Series B led by Andreessen Horowitz and Salesforce Ventures 5 things you didn't know you could do in the Mintlify web editor The improved Mintlify CLI Docs on autopilot: From zero to self-maintaining with Mintlify The state of agent traffic in documentation (March 2026) How we built a virtual filesystem for our Assistant We Replaced Our Internal Wiki With a Slack Bot. You Should Too. 8 ways teams use Mintlify to keep docs updated automatically Documentation is your AI interface What three years of watching AI in production taught us Bridging two JSX runtimes: How we solved Astro's React children problem AI agents are shipping faster than anyone can document Knowledge management systems for technical teams Workflows: Automate documentation maintenance Mintlify acquires Helicone to redefine AI knowledge infrastructure Why more product managers are switching to Mintlify Auto-generating documentation sites from GitHub repos Your docs, your frontend, our content engine Take control of your documentation system Almost half your docs traffic is AI, time to understand the agent experience @mintlify for better docs, faster Mintlify for Enterprise Real llms.txt examples from leading tech companies (and what they got right) Mintlify + Claude Opus 4.6: Powering AI-native knowledge management Declaring Clankruptcy: An experiment in agent orchestration
Closing the loop between user questions and documentation
Han Wang · 2026-01-07 · via Mintlify Blog

Keeping documentation accurate gets harder as your product moves faster. The signals for docs updates exist, but they're scattered across multiple platforms, and gathering them manually takes time.

Mintlify's agent suggestions help automate those signals by letting you know exactly what changes should be made in your docs.

A few weeks ago we released the ability to monitor pull requests for suggested docs updates, and today we are expanding that system. Your dashboard now highlights suggestions based on real user conversations with your docs assistant.

Every question asked by users to your docs assistant is an indicator of confusion or missing context. Mintlify analyzes these conversations to identify patterns and suggest updates that address real user needs.

1. Users visit your documentation and use your product

Your documentation is the face of your product. As adoption grows, more users and potential customers will land there to discover what’s possible.

2. Users interact with the docs assistant

When users ask questions to your built-in docs assistant, they reveal exactly where the documentation is unclear. These questions capture intent in a way analytics and support tickets often cannot.

3. Mintlify surfaces suggestions based on these conversations

Your dashboard highlights patterns in the questions your users ask. Instead of reviewing raw logs, you receive focused recommendations such as clarifying a concept, adding an example, or restructuring a section.

4. You improve your docs with targeted updates

With clear suggestions grounded in real usage, your team can update documentation with confidence. As the documentation becomes more accurate and clearer, users find what they need faster, the assistant performs better, and the number and quality of interactions improve.

Agent suggestions turn documentation into a living system that reacts to both how your product changes and how users interact with it. Instead of guessing what needs to be updated, you get direct, continuous insight. This makes it easier to keep your documentation aligned with reality and ensures that both humans and AI agents have accurate information when they need it.

Try it out today and let us know what you think.