|
| 1 | +--- |
| 2 | +sidebar_label: For Team Leads |
| 3 | +--- |
| 4 | + |
| 5 | +# AI Adoption Dashboard for Team Leads |
| 6 | + |
| 7 | +This guide covers how engineering managers and team leads can use the AI Adoption Dashboard to drive AI integration, identify gaps, and communicate progress to stakeholders. |
| 8 | + |
| 9 | +## Reading Team-Wide Metrics |
| 10 | + |
| 11 | +### The Organization View |
| 12 | + |
| 13 | +Disable the **"Only my usage"** toggle to see aggregated metrics across your entire team. This view shows: |
| 14 | + |
| 15 | +- **Overall AI Adoption Score** — Your single benchmark number |
| 16 | +- **Dimension breakdown** — Frequency, Depth, and Coverage contributions |
| 17 | +- **Week-over-week trends** — Direction and magnitude of change |
| 18 | +- **Historical timeline** — Score progression over days, weeks, or months |
| 19 | + |
| 20 | +### Dimension Detail Panels |
| 21 | + |
| 22 | +Click on any dimension card (Frequency, Depth, or Coverage) to open its detail panel. Each panel provides: |
| 23 | + |
| 24 | +- A focused timeline for that dimension |
| 25 | +- The goal statement for that dimension |
| 26 | +- Three actionable improvement suggestions tailored to what that dimension measures |
| 27 | + |
| 28 | +Use these panels to diagnose specific issues and identify targeted actions. |
| 29 | + |
| 30 | +### Comparing Time Periods |
| 31 | + |
| 32 | +Switch between time filters to understand different patterns: |
| 33 | + |
| 34 | +| Filter | Best For | |
| 35 | +| -------------- | ------------------------------------------------ | |
| 36 | +| **Past Week** | Recent changes, sprint-level trends | |
| 37 | +| **Past Month** | Adoption initiative tracking, onboarding results | |
| 38 | +| **Past Year** | Long-term trends, seasonal patterns | |
| 39 | +| **All** | Historical baseline, major milestones | |
| 40 | + |
| 41 | +--- |
| 42 | + |
| 43 | +## Identifying Adoption Gaps |
| 44 | + |
| 45 | +### Low Coverage Signals |
| 46 | + |
| 47 | +A low Coverage score often indicates adoption gaps—pockets of your team that aren't using AI. |
| 48 | + |
| 49 | +**Questions to investigate:** |
| 50 | + |
| 51 | +- Are all team members logged in and active? |
| 52 | +- Are certain roles or squads under-represented? |
| 53 | +- Is usage concentrated on specific days (spiky pattern)? |
| 54 | + |
| 55 | +**Actions:** |
| 56 | + |
| 57 | +1. Check your Organization Dashboard for inactive seats |
| 58 | +2. Look for patterns in who's not using AI (new hires? certain roles?) |
| 59 | +3. Consider targeted onboarding or pairing sessions |
| 60 | + |
| 61 | +### Low Depth Signals |
| 62 | + |
| 63 | +Low Depth indicates that developers may be trying AI but not trusting or shipping its output. |
| 64 | + |
| 65 | +**Questions to investigate:** |
| 66 | + |
| 67 | +- Are acceptance rates low? (Developers rejecting suggestions) |
| 68 | +- Is AI-generated code being merged? |
| 69 | +- Are developers using AI across multiple stages (plan → build → review)? |
| 70 | + |
| 71 | +**Actions:** |
| 72 | + |
| 73 | +1. Enable [Managed Indexing](/advanced-usage/managed-indexing) to improve context quality |
| 74 | +2. Review whether suggestions are relevant to your codebase |
| 75 | +3. Introduce chained workflows to increase multi-stage usage |
| 76 | + |
| 77 | +### Low Frequency Signals |
| 78 | + |
| 79 | +Low Frequency suggests AI hasn't become a daily habit. |
| 80 | + |
| 81 | +**Questions to investigate:** |
| 82 | + |
| 83 | +- Are developers aware of all available AI surfaces (IDE, CLI, Cloud)? |
| 84 | +- Is AI usage triggered only by specific, infrequent problems? |
| 85 | +- Have developers built AI into routine tasks? |
| 86 | + |
| 87 | +**Actions:** |
| 88 | + |
| 89 | +1. Map AI to existing daily tasks (stand-ups, PRs, documentation) |
| 90 | +2. Ensure the CLI is installed for terminal workflows |
| 91 | +3. Run a "try autocomplete for a week" challenge |
| 92 | + |
| 93 | +--- |
| 94 | + |
| 95 | +## Running Adoption Initiatives |
| 96 | + |
| 97 | +### Setting Goals |
| 98 | + |
| 99 | +Use the score tiers as milestones: |
| 100 | + |
| 101 | +| Current Tier | Reasonable Next Goal | |
| 102 | +| --------------- | ---------------------------- | |
| 103 | +| 0–20 (Minimal) | Reach 30–40 within 4–6 weeks | |
| 104 | +| 21–50 (Early) | Reach 55–65 within 4–6 weeks | |
| 105 | +| 51–75 (Growing) | Reach 75–80 within 6–8 weeks | |
| 106 | +| 76–90 (Strong) | Maintain and optimize | |
| 107 | + |
| 108 | +**Tip:** Focus on one dimension at a time rather than trying to improve everything at once. |
| 109 | + |
| 110 | +### Initiative Ideas |
| 111 | + |
| 112 | +**For Frequency:** |
| 113 | + |
| 114 | +- "Autocomplete Week" — Everyone commits to using autocomplete daily |
| 115 | +- CLI onboarding session — 30-minute walkthrough of terminal AI |
| 116 | +- Daily AI tip in Slack — Share one use case per day |
| 117 | + |
| 118 | +**For Depth:** |
| 119 | + |
| 120 | +- "Chain Challenge" — Complete one feature using plan → build → review |
| 121 | +- Managed Indexing rollout — Enable better context for the whole team |
| 122 | +- Deploy previews — Validate AI output before merging |
| 123 | + |
| 124 | +**For Coverage:** |
| 125 | + |
| 126 | +- New hire onboarding includes Kilo setup |
| 127 | +- Weekly "AI wins" sharing in stand-ups |
| 128 | +- Pair low-usage developers with enthusiastic adopters |
| 129 | + |
| 130 | +### Tracking Progress |
| 131 | + |
| 132 | +1. **Set a baseline** — Note your score at the start of an initiative |
| 133 | +2. **Check weekly** — Watch for trend changes, not absolute numbers |
| 134 | +3. **Adjust tactics** — If a dimension isn't moving, try a different approach |
| 135 | +4. **Celebrate wins** — Acknowledge when the team hits a milestone |
| 136 | + |
| 137 | +--- |
| 138 | + |
| 139 | +## Benchmarking Against Goals |
| 140 | + |
| 141 | +### Internal Benchmarking |
| 142 | + |
| 143 | +Use the score to compare: |
| 144 | + |
| 145 | +- **Teams within your organization** — Which teams are leading adoption? |
| 146 | +- **Before vs. after** — Did a specific initiative move the needle? |
| 147 | +- **This quarter vs. last** — Are you trending up or down? |
| 148 | + |
| 149 | +### Communicating to Stakeholders |
| 150 | + |
| 151 | +The AI Adoption Score is designed to be quotable: |
| 152 | + |
| 153 | +> "Last quarter we were at 38. This quarter we're at 57. Our goal is to reach 70 by Q2." |
| 154 | +
|
| 155 | +**When presenting scores:** |
| 156 | + |
| 157 | +- Lead with the trend, not just the number |
| 158 | +- Explain the tier and what it means |
| 159 | +- Connect to business outcomes ("Higher adoption → faster development cycles") |
| 160 | +- Share specific actions you're taking |
| 161 | + |
| 162 | +### Sample Stakeholder Update |
| 163 | + |
| 164 | +> **AI Adoption Update — January 2025** |
| 165 | +> |
| 166 | +> - **Current Score:** 57 (Growing adoption tier) |
| 167 | +> - **Last Month:** 48 |
| 168 | +> - **Change:** +9 points, driven by improved Depth scores |
| 169 | +> |
| 170 | +> **Key Actions Taken:** |
| 171 | +> |
| 172 | +> - Enabled Managed Indexing for better AI context |
| 173 | +> - Introduced Code Reviews for all PRs |
| 174 | +> - Onboarded 3 inactive team members |
| 175 | +> |
| 176 | +> **Next Steps:** |
| 177 | +> |
| 178 | +> - Target 65 by end of February |
| 179 | +> - Focus on Coverage—spread usage across the full week |
| 180 | +
|
| 181 | +--- |
| 182 | + |
| 183 | +## Privacy and Data Considerations |
| 184 | + |
| 185 | +### Anonymous Data |
| 186 | + |
| 187 | +Individual usage data is anonymized in the dashboard. While you can see aggregate metrics, the dashboard does not expose individual developer activity to managers. |
| 188 | + |
| 189 | +### Focus on Teams, Not Individuals |
| 190 | + |
| 191 | +The Dashboard is designed for: |
| 192 | + |
| 193 | +- Team-level insights |
| 194 | +- Organizational trends |
| 195 | +- Comparative benchmarking |
| 196 | + |
| 197 | +It is **not** designed for: |
| 198 | + |
| 199 | +- Individual performance evaluation |
| 200 | +- Identifying specific low performers |
| 201 | +- Surveillance of developer activity |
| 202 | + |
| 203 | +Use the score to identify adoption **gaps**, not to judge individual developers. |
| 204 | + |
| 205 | +--- |
| 206 | + |
| 207 | +## Future Enhancements |
| 208 | + |
| 209 | +### Code Contribution Tracking |
| 210 | + |
| 211 | +A future enhancement will track AI-contributed code from feature branch to main branch: |
| 212 | + |
| 213 | +- What percentage of AI-suggested code actually ships? |
| 214 | +- How much of the codebase was AI-assisted? |
| 215 | + |
| 216 | +This metric is separate from the Adoption Score but valuable for measuring AI impact on output. |
| 217 | + |
| 218 | +### Team Comparison Views |
| 219 | + |
| 220 | +Additional views for comparing multiple teams within an organization are planned, enabling leadership to identify best practices from high-performing teams. |
| 221 | + |
| 222 | +--- |
| 223 | + |
| 224 | +## Quick Reference: Dashboard Actions |
| 225 | + |
| 226 | +| What You Want to Know | Where to Look | |
| 227 | +| ---------------------------- | ------------------------------------------- | |
| 228 | +| Overall adoption level | Main score display | |
| 229 | +| Which dimension needs work | Trend indicators (look for negative trends) | |
| 230 | +| Specific improvement actions | Click dimension → detail panel | |
| 231 | +| Historical patterns | Timeline chart with time filter | |
| 232 | +| Your personal usage | Toggle "Only my usage" | |
| 233 | +| Week-over-week change | Metric cards at bottom | |
| 234 | + |
| 235 | +## Next Steps |
| 236 | + |
| 237 | +- [Understand what each dimension measures](/plans/adoption-dashboard/understanding-your-score) |
| 238 | +- [Learn strategies to improve your score](/plans/adoption-dashboard/improving-your-score) |
| 239 | +- [Return to the dashboard overview](/plans/adoption-dashboard/overview) |
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