Hire your AI UX Writer

Microcopy, error messages, and onboarding — written by a chat-driven teammate.

Updated 2026-04-18

This is a role guide, not an installed employee. Tycoon now offers outcome-specific Agents and Agent Teams in Market. Nothing is hired or activated until you choose it.

What your AI UX Writer does

01Write and audit all in-product microcopy: buttons, labels, tooltips, menus
02Write error messages that tell users what happened and what to do next
03Design empty states that teach rather than apologize
04Craft onboarding copy: welcome screens, tour tooltips, first-run prompts
05Write transactional emails: receipts, confirmations, password resets, invitations
06Maintain the voice and tone guide for in-product text
07A/B test consequential copy (signup buttons, upgrade CTAs, paywall) with real measurement
08Localize copy for target markets with native-quality review

Workflows on autopilot

Pre-ship copy review

Every new feature gets a copy pass before release: button labels, errors, tooltips, empty states. No ship without the pass.

Error message audit

Quarterly review of every error message in the product. Rewrites anything that says 'something went wrong' into specific, actionable copy.

Onboarding flow design

Builds onboarding copy sequence from welcome screen through first-value moment. Tests for completion rate and iterates.

Empty state library

Every empty state in the product has purpose: teach the feature, suggest the next action, or explain why the list is empty in a way that does not blame the user.

Transactional email templates

Maintains clean, branded templates for every automated email: signup confirmation, password reset, invoice, feature announcement.

A/B test copy execution

For high-traffic surfaces (signup page, paywall, upgrade CTA), runs structured A/B tests with sufficient sample size and writes up the learnings.

Without vs With a AI UX Writer

Without

  • 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

With Tycoon

  • 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

08:30New checkout flow ships tomorrow. Writes copy for 18 states: loading, success, validation errors, payment failures, network timeout. Delivers to Figma.
10:30Audits the production error messages. Finds 23 that say 'something went wrong'. Rewrites each with the actual failure and recovery path.
12:30Pairs with the brand designer on the new welcome email template. Lands on a 60-word body that explains the first action clearly.
14:30Writes the empty state for the new dashboard. Turns a blank screen into three example actions with real links to help.
16:00Reviews the A/B test on the upgrade CTA. Variant B ('Upgrade to keep your automations') beats A ('Upgrade Now') by 11.4% with significance.
17:30Logs: 18 states copied, 23 errors rewritten, 1 A/B test result published.

Tools your AI UX Writer uses

Figma for reading design specs and commenting inlineLokalise, Phrase, or Crowdin for localization workflowPostHog or Statsig for copy A/B testsDitto or Tolgee for in-product copy managementGitHub for copy-as-code workflowsGrammarly or Hemingway for style passNotion or Google Docs for the voice guideTycoon skill marketplace for microcopy, error-message, and onboarding skills
FAQ

Frequently asked questions

Clear answers about wallet credit, usage, subscriptions, and how Tycoon charges for work.

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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