Controlled Follow-up

Precision editing of steps within the scope of a given question

What is Controlled Follow-up?

Controlled Follow-up (CFU) is a precision-editing feature within Connecty AI that lets users modify a specific part of the answer or its answer preparations steps e.g. metric definition. It does NOT change the question's main intent. It is designed for both technical and non-technical users to make changes within an existing context or intent, saving time and increasing trust in the modeling process.

CFU is available in two environments:

• In Chat: Adjust a specific step in the question-to-answer pipeline, such as the grammar logic or filters.

• In Metricverse: Edit a specific entity (e.g. metric, measure, dimension, subject) and see where the change will propagate.

The key difference between CFU and FU is that in CFU you can only change part of the answer, whereas in FU you can also modify or add additional information to the question

---

Why Use CFU?

• 🚀 Fast Iteration: Make surgical changes without resetting the full logic pipeline.

• 🧠 Context-Preserving: Keeps previous steps intact unless context expansion is explicitly needed.

• 👥 Accessible for All Users: Works with natural language or technical input.

• 📊 Impact-Aware: Highlights cascading effects on downstream metrics and questions.

---

How It Works

1. In Chat

• Step Selection: Choose a step from the answer preparation flow (e.g. context inference, grammar logic, final query) or click into a specific entity inside the grammar.

• Make Adjustments: Use natural language or precise expressions to describe the desired change. For example:

  • "Replace revenue with profit"

  • "Group by product line"

  • "Use 'discounted_price' table instead"

• Context Limitation Reminder: The AI regenerates only the selected step, using the context established in earlier steps. If your change requires new tables or dimensions not previously included, you’ll need to use a standard follow-up (e.g. click “Reply” or switch to the AI SQL Editor).

2. In Metricverse

• Entity Selection: Choose the entity you want to update: metric, measure, dimension, subject, filter, or relationship.

• Describe the Change: Input can be:

  • A precise expression (e.g. SUM(revenue) - SUM(COGS) for a technical user)

  • A natural language definition (e.g. “profit should exclude all promotional and logistics costs” for a business user)

• Regeneration & Impact Analysis: AI updates the entity definition and performs cascading impact analysis, identifying:

  • Which downstream metrics will be affected

  • Which saved questions, dashboards, or charts may change

  • Whether the logic remains valid

---

CFU vs Follow-up

Feature	Controlled Follow-up (CFU)	Standard Follow-up (Reply / Editor)
Scope	Edits within existing intent & context	New or expanded context / intent
Usage	Step-by-step precision edits	Full regeneration of logic
Risk of Breakage	Higher if edit requires new tables not in context	Safer for broader changes
Best For	Quick refinements, deep dives, surgical edits	Starting over, branching logic, new questions

---

Real-World Examples

• In Chat:

  "Change the filter to only include last quarter." Connecty AI adjusts the grammar step without altering your grouping or selected metrics.

• In Metricverse:

  You select a metric called Gross Margin and enter: "It should exclude affiliate fees and partner rebates." Connecty AI regenerates the metric logic, highlights affected KPIs and dashboards, and explains the cascading changes.