Work hides in individual chats
Important context and decisions stay on one person's screen.
Raydo for team leads
See what AI is doing, where people should step in and what is ready next.
Raydo gives small-team leads a clearer operating surface for AI work that crosses people, browser tasks, local files, approvals and delivery.
Where teams lose control
More AI activity does not automatically create more visibility.
Leads need to know what is running, where judgment is required and whether the output is ready to use.
Approval arrives too late
Risky or client-facing actions happen before the right person sees them.
Handoffs restart the task
The next teammate receives an output without the run state and supporting context.
Team lead workflows
Use Raydo to make AI work visible and handoff-ready.
The goal is clearer coordination around real work, not more automated activity for its own sake.
01
Review work before external impact
- Input
- A task, selected context and a defined approval boundary
- Process
- Let the work proceed until a consequential action or judgment point
- Output
- A review request with enough context to make the decision
02
Track a multi-step delivery
- Input
- A desired artifact, contributors, tools and acceptance criteria
- Process
- Keep execution state visible and surface failures or missing inputs
- Output
- A completed package with status, checks and ownership
03
Hand work to the next teammate
- Input
- Current files, browser state, decisions and remaining steps
- Process
- Preserve the run record and explain the next required action
- Output
- A continuation-ready handoff instead of a fresh briefing
How Raydo works
The team can see the same path from goal to output.
Execution stays useful because responsibility and judgment remain visible.
1
Goal
Define the outcome, owner and acceptance criteria.
2
Context
Select the files, pages and prior work the team authorizes.
3
Execution
Run the work while status and tool activity remain inspectable.
4
Approval
Route consequential decisions to the right person before action.
5
Output
Store the artifact, run record and next step for handoff.
Product fit
A shared operating view is more useful than another isolated AI chat.
Raydo keeps work state and review boundaries close to the task.
Visible status
See what is running, waiting, completed or blocked.
Approval boundaries
Decide where a person must review before work continues.
Local operating context
Keep selected work materials in the environment the team already manages.
Saved handoff record
Give the next person the result and enough context to continue.
Team memory
Good work becomes a team method instead of private history.
Repeated tasks can retain their inputs, checks and approval points.
Make the operating pattern explicit
Define how a recurring task starts, runs and finishes.
Keep responsibility visible
Owners and approval points remain part of the workflow.
Improve the next run
The team can review what worked and update the reusable process.
Team lead FAQ
Questions team leads ask about Raydo
No. Raydo focuses on the execution, review and artifacts of AI-assisted work and can sit alongside your current planning system.
Approval is most useful at consequential steps. Routine read-only work can continue while publishing, writing or other impactful actions stop for review.
A saved task is designed to keep its context, run state and artifacts available for a clearer handoff.
The desktop remains the operating surface while selected status, artifacts and handoffs can still support team coordination.
Explore related use cases
Make the next team workflow visible before you automate more of it.
Start with one recurring task, clear approval boundaries and an artifact the next person can use.
