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GuideMode

Creating Guide Rails

GuideMode offers two ways to create guide rails: a manual step-by-step wizard for full control, or AI-assisted creation that recommends guide rails based on your goals in natural language.

Creating Guide Rails Manually

Section titled “Creating Guide Rails Manually”

The guide rail creation wizard guides you through four steps to configure a guide rail.

Step 1: Select Metric

Section titled “Step 1: Select Metric”

Choose the metric you want to track:

  1. Search or Browse - Use the search box to find metrics by name, or browse by category
  2. Select a Cube - Metrics are organized by analytics cube (Discovery Flow, Delivery Flow, Deployment Flow, etc.)
  3. Choose a Measure - Select the specific metric to track (e.g., “Average Cycle Time”, “PR Merge Rate”)
  4. Select Time Dimension - Choose how the data is aggregated over time (e.g., by completion date, by creation date)

The measure picker shows:

  • Metric name and description
  • Category (which cube it belongs to)
  • Type indicator (number, percentage, duration)

Step 1: Select a metric from the measure picker with search and category filters

Step 2: Set Guide Rail Value

Section titled “Step 2: Set Guide Rail Value”

Configure the guide rail type and value:

Guide Rail Types

Section titled “Guide Rail Types”
Type Description Example
Minimum Value should be at least this (higher is better) Code coverage >= 80%
Maximum Value should be at most this (lower is better) Cycle time <= 5 days
Exact Value should be close to this goal SLA = 95%
Range Value should be between min and max PR size 50-200 lines

Using Historical Data

Section titled “Using Historical Data”

The wizard displays your historical performance to help set realistic guide rails:

  • Min / Max - The lowest and highest values observed
  • Median - The middle value (50th percentile)
  • Average - The mean value across all periods
  • P90 - The 90th percentile value

The wizard suggests three guide rail levels:

  • Conservative (Median) - Achievable based on current performance
  • Moderate (P75) - Requires improvement from current baseline
  • Aggressive (P90) - Stretch goal for top performance

Click any suggested value to use it as your guide rail.

Step 2: Configure guide rail type and value with historical data markers

Step 3: Set Granularity & Format

Section titled “Step 3: Set Granularity & Format”

Configure how the guide rail is measured and displayed:

Granularity Options

Section titled “Granularity Options”
Option Description Best For
Daily Measures progress every day High-frequency operational metrics
Weekly Measures progress every week Most team performance metrics
Monthly Measures progress every month Strategic and capacity metrics
Quarterly Measures progress every quarter Long-term objectives and OKRs

Display Format

Section titled “Display Format”

Choose how values are formatted:

Format Example Use For
Number 42.5 Counts, scores, raw values
Percent 75% Rates, coverage, completion
Duration 3.5 days Cycle times, lead times
Currency $1,234 Cost-related metrics

Description (Optional)

Section titled “Description (Optional)”

Add context about why this guide rail matters or what actions the team should take to achieve it.

Step 3: Choose granularity and display format options

Step 4: Review

Section titled “Step 4: Review”

Confirm your guide rail configuration:

  • Metric - Name, cube, and time dimension
  • Guide Rail - Type and value(s)
  • Tracking - Granularity and format
  • Description - Any notes you added

Click Create Guide Rail to save, or go back to adjust any settings.

AI-Assisted Creation with Ask Giulia

Section titled “AI-Assisted Creation with Ask Giulia”

Let GuideMode’s AI assistant recommend guide rails based on your goals.

How It Works

Section titled “How It Works”
  1. Click Ask Giulia on the team guides page
  2. Enter your goal in natural language
  3. Giulia analyzes available metrics and your historical data
  4. Review and apply the recommended guide rails

Step 1: Enter Your Goal

Section titled “Step 1: Enter Your Goal”

Describe what you want to achieve in plain language. Examples:

  • “Improve team delivery velocity and reduce cycle time”
  • “Increase code review quality and reduce time to merge”
  • “Better discovery-to-delivery conversion rate”
  • “Reduce deployment failures and improve DORA metrics”
  • “Increase AI-assisted code generation adoption”

Click an example goal to use it as a starting point, then customize as needed.

Ask Giulia modal with goal input and example suggestions

Step 2: Review AI Analysis

Section titled “Step 2: Review AI Analysis”

Giulia processes your goal in three stages:

  1. Analyzing Goal - Understanding your intent and enriching the goal
  2. Gathering Data - Fetching historical performance for relevant metrics
  3. Generating Guide Rails - Calculating recommended guide rail values

Once complete, you’ll see:

  • Enriched Goal - How Giulia understood your request
  • Recommended Metrics - 3-5 metrics that best measure progress toward your goal

Step 3: Review Recommendations

Section titled “Step 3: Review Recommendations”

Each recommendation includes:

Element Description
Metric Name The measure being recommended
Guide Rail Value The suggested value based on historical data
Guide Rail Type Whether higher or lower is better
Granularity Recommended measurement frequency
Confidence High, Medium, or Low confidence in the recommendation
Reasoning Why this metric and value were chosen

Confidence Levels

Section titled “Confidence Levels”
Level Meaning
High Strong data signal and clear relevance to your goal
Medium Good relevance but limited historical data
Low Relevant but may need adjustment based on context

AI recommendations showing metrics with confidence badges and reasoning

Step 4: Apply Selected Guide Rails

Section titled “Step 4: Apply Selected Guide Rails”
  • Toggle individual recommendations on or off
  • Review all selected guide rails before applying
  • Click Apply Guide Rails to create all selected guide rails at once

All AI-created guide rails are marked as “AI Suggested” for reference.

Best Practices

Section titled “Best Practices”

Setting Effective Guide Rails

Section titled “Setting Effective Guide Rails”
  1. Start with historical data - Use your actual performance as a baseline
  2. Choose appropriate granularity - Match the frequency to how often the metric can meaningfully change
  3. Be specific - Clear guide rails are easier to act on than vague goals
  4. Review regularly - Adjust guide rails as your team improves or priorities change

Using AI Recommendations

Section titled “Using AI Recommendations”
  1. Be descriptive - More context in your goal leads to better recommendations
  2. Review confidence levels - Consider adjusting low-confidence guide rails
  3. Don’t accept blindly - AI recommendations are starting points, not final answers
  4. Combine with manual - Use AI for initial setup, then fine-tune manually

Managing Multiple Guide Rails

Section titled “Managing Multiple Guide Rails”
  • Focus on 3-5 key guide rails - Too many guide rails dilute attention
  • Balance leading and lagging indicators - Track both inputs and outcomes
  • Align with team goals - Guide rails should support broader objectives
  • Copy successful guide rails - Share configurations across teams when relevant

Next Steps

Section titled “Next Steps”