FAQ
Frequently asked questions
Clear answers about wallet credit, usage, subscriptions, and how Tycoon charges for work.
How does it avoid writing 'we shipped bug fixes' for actual bug fixes?
Bug fixes are their own category — they go into the changelog page with specific descriptions ('Fixed: CSV export would fail when dataset exceeded 10,000 rows') but not in the monthly email or social media unless a customer specifically requested the fix. The distinction matters: customers want to know their reported bugs got fixed (high trust), but they don't want a marketing email about bug fixes (feels like noise). Tycoon splits them appropriately — changelog = complete, email = feature-forward.
What about breaking changes or deprecations? Those need more careful communication.
Yes, and they follow a different path. Breaking API changes trigger a 30-day advance notice workflow: email to affected customers (identified by API usage in your telemetry), docs update highlighting the migration, Slack/Discord announcement, in-app warning banner for users who use the deprecated path. The timeline is enforced — the code can't merge to main until the deprecation notice is scheduled. AI Head of Content drafts all the copy; AI CTO enforces the merge gate.
Our product has 3 surfaces (web app, API, CLI). Each has different audiences. How does this handle that?
Three separate changelog feeds, one pipeline. Every PR gets tagged by surface (web/api/cli) via label or file-path detection. The changelog page has filters so customers can subscribe to only the surfaces they care about. Emails/social/in-app all target the right audience — API customers get API updates, CLI users get CLI updates, web users get web updates. Shared features (like 'this is now in all 3 places') publish to all feeds.
How accurate is the 'user-facing vs internal' classification? We don't want internal refactors announced.
After 30 days of training on your codebase patterns, accuracy is 95%+. The AI reads file paths (changes in src/pages/dashboard → user-facing, changes in scripts/migrations → internal), PR descriptions, and linked Linear tickets. Misclassifications surface in the review queue before publishing — you can tag 'internal only' to skip. Over time the AI learns your specific conventions. Most misclassifications err toward over-publishing (surfacing internal work as user-facing), which is caught in review, not under-publishing.
We're B2B with enterprise customers. They hate surprise feature announcements — they want managed rollouts.
The pipeline supports this. Features tagged 'enterprise-sensitive' go into a separate workflow: enterprise account managers get a preview 1 week before launch with talking points, customers with active tickets on the affected area get a personal note from their account rep, and the public announcement holds until all priority accounts have been briefed. The automation handles the coordination; humans handle the relationships. Typical workflow: 5-10 day staggered rollout for big features, same-day for small ones.