Hire your AI UX Writer
Microcopy, error messages, and onboarding — written by a chat-driven teammate.
Your AI UX Writer writes the words inside your product — button labels, error messages, empty states, onboarding tooltips, email receipts. The copy that nobody notices when it is good and everyone notices when it is bad. It matches your brand voice, reduces friction, and replaces the dozens of tiny writing decisions that otherwise rot in a backlog.
What your AI UX Writer does
Workflows on autopilot
Without vs With a AI UX Writer
- —Error messages say 'Something went wrong, please try again'
- —Empty states apologize instead of teaching
- —Onboarding is a skipped 3-step tour that teaches nothing
- —Transactional emails look like they're from a 2012 phpBB forum
- —A human UX writer is a $140K+ hire most small teams cannot justify
- ✓Errors say exactly what failed and what the user should do
- ✓Empty states turn a blank screen into a first action
- ✓Onboarding copy runs alongside action, not in front of it
- ✓Every email is branded, clear, and useful
- ✓AI UX Writer covers the work at the quality of a senior writer
A day in the life of your AI UX Writer
Tools your AI UX Writer uses
Frequently asked questions
How is this different from a technical writer?
Technical writer writes docs outside the product (API reference, tutorials, help center). UX writer writes the words inside the product (button labels, errors, onboarding tooltips). The skills overlap but the surface is different — technical writing is explanatory, UX writing is functional. On small teams you often want both because the work is large; on very small teams the AI Technical Writer role can cover UX writing at a lower depth, and you upgrade to a dedicated UX writer when in-product copy volume grows.
Can it match my brand voice?
Yes, and this is where most AI writing tools fail today. The AI UX Writer reads your existing product copy, your landing page voice, your brand guidelines, and your CEO's past writing to build a voice profile. Every new piece of copy passes through a voice check. When you correct it ("too corporate, be more casual") the voice profile updates. Over three to four weeks the drift flattens. The tell of generic AI copy — the 'leverage-powerful-seamless' cluster — is trained out specifically and does not appear in output.
Does it work with Figma?
Yes, first-class. The AI UX Writer reads Figma files directly, understands components and variants, and leaves comments inline with copy suggestions that designers can accept or reject. For teams using Ditto or Tolgee for copy management, it integrates with the copy-as-code workflow and ships through the existing pipeline. For teams without formal copy infrastructure, it works in plain documents or Slack — the friction is kept low.
How does it handle localization?
The AI UX Writer works in your source language (usually English) and hands off to a localization workflow (Lokalise, Phrase, Crowdin, or Tycoon's built-in translation). For strong languages (Spanish, Japanese, French, German, Portuguese, Chinese simplified/traditional, Korean) it reviews the translated output for tone match and flags anything that reads off. For weak languages or regulatory-sensitive copy (financial disclosures, health claims in EU markets) it recommends a human native-speaker review. The goal is quality that matches the source language, not mechanical translation.
What about A/B testing copy?
For high-traffic surfaces (signup button, pricing page CTA, paywall headline) the AI UX Writer designs and runs A/B tests through your existing experimentation tool (PostHog, Statsig, Optimizely). It calculates the required sample size, sets up variants, reads the results at statistical significance, and writes up the learning for the voice guide. For low-traffic surfaces, A/B testing is rarely worth the sample size; the AI is honest about that and recommends judgment-based decisions. Most in-product copy does not deserve a test; the places that do are tested rigorously.
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