Evolving Your Software
Your workspace should keep changing as your needs change.
That might mean adding a new view, replacing a workflow, tightening approvals, connecting a new service, or exposing part of the workspace to a wider audience. The workspace should be able to grow without turning into a confusing rebuild every time.
The kinds of changes people usually make
Most changes fall into a few familiar groups:
- add a new view
- change what the main view focuses on
- connect a new service
- replace or split an AI team member role
- add a hook for a hand-off that has become too important to leave flexible
- tighten approvals for sensitive actions
- expose part of the workspace through a shared view
Sometimes one request touches several of those at once.
How to ask for a change
When you ask Worka to change an existing workspace, make the change concrete.
Good examples:
- “Add a customer-facing status view.”
- “Split intake and review into two AI team members.”
- “Keep the current main view, but add a second view for approvals.”
- “Connect our shared Google Calendar and automatically add confirmed bookings.”
That helps Worka distinguish between:
- a local change to one part of the workspace
- a broader redesign of how the workspace works
What Worka should preserve
When the workspace changes, Worka should try to preserve:
- the parts that already work well
- the connection history and approvals already in place
- the visible reason for the change
- the usability of the main workspace while the change is in progress
Changing a workspace should feel like extending a real system, not discarding it and starting from scratch.
What to review when a change is proposed
Review change requests the same way you review the first plan, but with extra attention to impact.
Check:
- what is being added
- what existing behaviour will change
- whether a new service or pack is required
- whether the main view is still the right main view
- whether approvals or hooks need to change as well
This is where Worka either proves it can evolve a workspace cleanly or shows that it only knows how to generate a first draft.
Small changes versus structural changes
Not every change needs the same level of caution.
Small changes
Examples:
- adjust copy
- improve one view
- add one low-risk service connection
- refine a hand-off rule
These should usually feel straightforward.
Structural changes
Examples:
- change the main view
- replace the workflow structure
- introduce browser control
- expose the workspace externally
- split one broad AI team member into several roles
These deserve a more careful review because they change how the workspace behaves, not just how it looks.
How to keep the workspace understandable as it grows
The more the workspace evolves, the more important it becomes to keep the model clear.
After a change, you should still be able to explain:
- what the workspace is for
- which view people should open first
- which AI team members do what
- which services are connected
- which actions still require approval
If a change makes those answers harder instead of clearer, it is probably the wrong change or the wrong time for it.