Talent Grid — Engineering
Click an engineer for AI analysisPotential Gem
0 engineers
High Potential
20%1 engineer
Star
20%1 engineer
Inconsistent
0 engineers
Core Player
20%1 engineer
Key Player
40%2 engineers
Risk
0 engineers
Average
0 engineers
Solid Performer
0 engineers
Performance
Alex is a Key Player trending upward. His scores are still dampened by February disengagement (sparse standups, skipped pulse survey). Since the intervention on March 4, he has completely turned around — shipping a flawless ES module migration and now mentoring Priya.
Key Observation
The root cause of Alex's disengagement was isolation, not dissatisfaction — collaboration restored his motivation
Suggested Action
Leverage his momentum by scoping Q2 module system improvements and consider him for a tech talk on the ES migration
Recovery is confirmed but rolling metrics still include February silence period — scores will improve next cycle
- •ES module migration cutover — zero production issues, 18% bundle size reduction
- •Complete turnaround from disengagement in February to team leadership in March
- •Rolling metrics still dampened by February silence period — expect scores to improve next cycle
Key Attributes
Click any engineer on the grid to see AI-powered analysis, performance scores, and suggested actions
What is the 9 Box Grid?
The 9 box grid (also called the 9 box talent matrix or McKinsey 9 box) is a talent management framework that evaluates employees on two dimensions: current performance and future potential.
Originally developed by McKinsey in the 1970s for GE's succession planning, the 9 box grid remains one of the most widely used tools in HR and talent management. It helps leaders visualize their talent landscape and make strategic decisions about development, promotion, and retention.
For engineering managers, the 9 box grid answers critical questions: Who are your future tech leads? Which engineers need performance support? Who's at risk of leaving if not challenged?
Why Use a 9 Box Grid for Engineering Teams?
Succession Planning
Identify future leaders and build your leadership pipeline. See who's ready for promotion and who needs development.
Talent Reviews
Calibrate performance across your team objectively. Compare engineers side-by-side with clear visual placement.
Development Planning
Create targeted development plans based on each engineer's position. Different boxes need different interventions.
AI-Powered Insights
Vereda AI suggests box placements based on standup data, goal progress, 1:1 notes, and engagement signals.
Reduce Bias
Data-driven placement recommendations help reduce unconscious bias in talent assessments.
On-Demand Calibration
Run your 9-box calibration whenever you need it — no waiting for annual review cycles. Stay current with your team's growth trajectory.
Understanding Each Box
Each position in the 9 box grid calls for different management actions. Here's how to interpret and act on each placement.
Enigma
Investigate barriers. High potential but something is blocking performance. Consider role fit, manager relationship, or personal challenges.
Growth Employee
Accelerate development. Ready for stretch assignments and leadership opportunities with targeted skill building.
Star
Retain and promote. Your future leaders. Give challenging projects, visibility, and clear advancement path.
Dilemma
Performance improvement plan. Potential exists but performance must improve. Set clear expectations and timeline.
Core Player
Maintain and develop. Backbone of your team. Recognize contributions and offer growth opportunities.
High Performer
Recognize and challenge. Excellent in current role. May not want management track—explore technical leadership.
Risk
Address directly. Have honest conversation about fit. Consider role change or exit if no improvement.
Average Performer
Maintain performance. Reliable contributor in current role. Focus on engagement and job satisfaction.
Workhorse
Appreciate and retain. Exceptional at current level. May not advance but invaluable in role. Recognize publicly.
How Vereda AI Modernizes the 9 Box Grid
1AI-Suggested Placements Tied to Your Competency Matrix
Placements are scored against your company's competency matrix — not generic criteria. Vera analyzes standup participation, goal completion, 1:1 sentiment, and engagement patterns against the expectations defined for each level. You get placement suggestions with the reasoning behind them — then decide whether to accept.
2On-Demand Calibration
Traditional 9-box reviews happen once a year — way too slow for engineering teams. Run calibration whenever you need it with AI-suggested placements based on the latest data. Stay current without waiting for a review cycle.
3Connected to Your Workflow
The 9 box grid doesn't exist in isolation. Click on any engineer to see their goals, recent 1:1 notes, standup history, and AI signals. Use the grid as your jumping-off point for talent conversations.
4Calibration Tools
Running a calibration session? Vereda AI highlights potential inconsistencies across managers and surfaces discussion points. Ensure your "high performer" in one team matches another team's standards.
Data That Powers Your 9 Box Grid
Vereda AI doesn't ask you to manually assess performance and potential. It gathers signals from your existing workflow:
- Standups: Participation rates, blocker frequency, collaboration mentions
- Goals: Completion rates, goal ambition level, progress velocity
- 1:1s: Sentiment trends, growth discussions, feedback themes
- AI Check-ins: Engagement levels, proactive communication, wellbeing signals
- Integrations: GitHub PR velocity, Jira ticket completion (with Integration Pack)
Frequently Asked Questions
What is a 9 box grid in talent management?
The 9 box grid is a talent management framework that plots employees on two axes: current performance (x-axis) and future potential (y-axis). Each of the 9 boxes represents a different talent profile, from 'Stars' (high performance, high potential) to 'Risk' employees (low performance, low potential). It helps managers make data-driven decisions about development, succession planning, and resource allocation.
How does Vereda AI populate the 9 box grid automatically?
Vereda AI analyzes multiple data sources to suggest placements: standup participation and quality, goal completion rates, 1:1 feedback trends, peer collaboration signals, and engagement patterns from AI check-ins. You can accept suggestions or override them—final placement is always your decision as the manager.
How often should I update my 9 box talent grid?
Traditional 9-box reviews happen annually, but that's too slow for engineering teams. Vereda AI lets you run calibration on demand — whenever you need it. AI suggestions are always based on the latest data, so your grid is current every time you open it.
Is the 9 box grid still relevant in 2026?
Yes, but it needs modernization. The core framework remains valuable for visualizing talent. However, static annual snapshots are outdated. Vereda AI's approach combines the proven 9-box structure with real-time data, signal detection, and continuous calibration—addressing the traditional criticisms of subjectivity and staleness.
How do I reduce bias in 9 box talent reviews?
Vereda AI helps reduce bias in three ways: (1) Data-driven suggestions based on objective signals, not gut feelings; (2) Historical tracking that shows patterns over time, not point-in-time impressions; (3) Calibration tools that highlight discrepancies across managers. You make the final call, but with better information.