FAQ
Frequently asked questions
Clear answers about wallet credit, usage, subscriptions, and how Tycoon charges for work.
Will my team actually use this or will they keep doing standups on the side?
Adoption depends on whether the AI PM makes their life easier. Most teams keep daily standups for the first 2 weeks while the AI learns their workflow. By week 3, the AI's status summaries are more accurate than what people report in standup (because it reads actual PR/commit activity, not memory), and the standup starts feeling redundant. The key adoption trigger: when someone realizes they don't have to update tickets anymore because the AI does it. That's usually week 2-3. The PM should be introduced as a team augmentation, not a replacement — it handles the tracking so humans handle the decisions.
How does this work with remote/async teams across time zones?
This is the ideal use case. Async teams suffer most from status communication overhead — the 'did Priya ship that?' Slack message that takes 6 hours to get answered because she's asleep. AI PM eliminates that: task status is always current (synced from actual tool activity), so anyone in any time zone can self-serve the project state. The daily summary posts at whatever time works for each team member. Remote teams that adopt this typically see the biggest meeting reduction because they were spending proportionally more time on status coordination.
Does this work for non-engineering teams — marketing, sales, ops?
Yes. AI PM works with any team using a project tool for task tracking. Marketing teams using Asana for campaign calendars: AI PM tracks content production pipeline, flags when a blog post is late, surfaces that the landing page needs design review before copy can start. Sales ops using Monday for deal desk: AI PM tracks contract review stages, flags deals stalled in legal review >5 days. The concept is the same across functions — track tasks, infer status from tool activity, flag blockers — it just maps to different tools and workflows per team.
How does the AI PM handle priority conflicts — when everything is 'P0'?
AI PM uses velocity data, not stated priority. If your CTO says task A is P0 but the team historically ships 4 tasks per sprint and task A is the 7th in the sprint, the AI flags the reality: 'Task A is P0 but won't ship this sprint at current velocity. Options: move 3 tasks to next sprint, or accept that A ships next sprint.' It doesn't resolve the conflict — that's the human PM's job — but it surfaces the mathematical reality that too many 'P0' tasks is a capacity problem, not a prioritization problem.
Can it handle client-facing project management — agency work with external deadlines?
Yes, with a client-layer model. AI PM can maintain both internal and client-facing views: internal view tracks actual status, risks, and velocity; client-facing view generates status reports and timeline updates in client-appropriate language. For agencies managing 15+ clients where every client wants a weekly status update, AI PM generates those updates from live project data — not from account managers spending 3 hours per client writing status emails. This workflow alone saves agencies 15-20 hours per week in status communication.