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Reviewing the Plan

Reviewing the plan is one of the most important parts of using Worka well.

You do not need to review every technical detail. You do need to catch the moments where Worka has misunderstood the job, chosen the wrong systems, or asked for more reach than the workspace should have.

What the plan should show you​

A useful plan should make five things visible:

  • what Worka thinks the workspace is for
  • which views it plans to create
  • which services and packs it expects to use
  • which AI team members or workflow roles it expects to rely on
  • which approvals, connections, or sensitive capabilities may be required

If you cannot see those things, the plan is too vague to trust.

Check the views first​

The first thing to review is the view set.

Ask:

  • is the main view the one people will actually open first
  • does each supporting view have a clear job
  • is anything important missing
  • is anything unnecessary being added

This matters because a workspace can be technically clever and still be awkward if the view structure is wrong.

Check the sources and connections​

Next, check what Worka wants to connect to.

Ask:

  • are these the right systems
  • are any unnecessary systems included
  • is browser control being proposed where a normal API should be enough
  • does the requested access level feel proportionate

Connections and capabilities change what the workspace can do, so this is where you catch silent scope creep.

Check the AI team and workflow​

A workspace is easier to trust when the AI team makes sense.

Ask:

  • do the proposed AI team members have clear jobs
  • is any role too broad
  • is a human approval needed before any high-risk actions
  • does the hand-off logic look sensible

If the workflow feels vague at the plan stage, it usually becomes harder to debug later.

Check for overbuilding​

One of the easiest ways for Worka to drift is by building too much.

Warning signs include:

  • too many views for a simple job
  • too many services for an early version
  • AI team members with overlapping roles
  • high-risk capabilities introduced before the workspace proves it needs them

You do not need the perfect architecture on day one. You need the first useful shape of the workspace.

Useful kinds of feedback​

Good plan feedback is usually specific and direct.

Examples:

  • “The main view should focus on approvals, not reporting.”
  • “Use our Google Calendar, not Salesforce, as the main source.”
  • “Do not add browser control for this workflow.”
  • “We need a shared external view for customers.”
  • “Split this AI role into intake and review.”

That kind of feedback is enough to change the direction without forcing you to redesign the entire system yourself.

When to stop the plan​

Stop and redirect the plan if:

  • the workspace is solving the wrong problem
  • the proposed view structure would confuse the real users
  • the services or capabilities are broader than necessary
  • the AI team is hard to understand
  • you cannot tell what will require approval

The earlier you correct direction, the cheaper it is to fix.