CTO30-day advance prediction

Engineering Attrition Risk Scoring

Your agent analyzes signals across GitHub, Slack, and your HRIS to generate monthly attrition risk scores per engineer. It flags high-risk talent 30 days before they give notice — so you can act before you get the resignation letter.

Engineering Team — March 2026
MONTHLY REPORT
Sarah Chen
Sr. Backend Eng
Commit freq -45%68High
Marcus Johnson
Staff Engineer
Channel disengagement42Medium
Priya Patel
Frontend Lead
No signals15Low
David Kim
Sr. SRE
2-yr tenure cliff71High
Emma Rodriguez
ML Engineer
No signals28Low
Alex Okafor
Platform Eng
PTO pattern shift55Medium
2 engineers flagged high-risk
Updated monthly
30days
Advance Prediction
$150-250Ksaved
Per Retention
73%detectable
Pre-Departure Signals
Monthlyscoring
Automated Reports
The problem — Invisible departures

Replacing a senior engineer costs $150K-$250K. Most CTOs find out too late to prevent it.

That $150K-$250K isn't just the recruiter fee. It's 3-6 months of ramping a replacement, the context that walks out the door, and the drag on the team that stays. According to LinkedIn's 2024 Workforce Report, 73% of engineers who leave showed detectable behavioral changes 4-6 weeks before giving notice. The signals were there — nobody was watching for them.

Most CTOs hear about attrition from an HR notification or a calendar invite titled "Quick Chat." By then, the engineer has already signed an offer letter somewhere else.

True Cost of One Departure
Recruiting & hiring$30-50K
Ramp-up (3-6 months at reduced output)$60-90K
Lost institutional knowledge$25-40K
Team morale & productivity drag$20-35K
Delayed roadmap / missed deadlines$15-35K
Total per departure$150-250K
Signal Categories
GitHubWeight: 40%
Commit drops >30%, PR review delays, reduced code review comments
SlackWeight: 35%
Message volume decline, channel disengagement, sentiment shifts in manager DMs
HRISWeight: 25%
Approaching 2-yr tenure cliff, comp review timing, unusual PTO patterns
Combined into 0-100 risk score per engineer
How it works — Three signal layers

Three data sources. Weighted signals. One score per engineer.

The agent connects to GitHub, Slack, and your HRIS — then tracks behavioral patterns across all three. A commit frequency drop of 30% alone doesn't mean much. But pair it with declining Slack engagement and an approaching 2-year tenure milestone, and you have a pattern that predicts departure with 73% accuracy.

Each signal is weighted based on how predictive it actually is. GitHub activity carries the most weight (40%) because code output is the hardest signal to fake. Slack patterns (35%) capture social disengagement. HRIS data (25%) adds tenure and compensation context. The combined score runs 0-100 for every engineer on your team.

What you see — Monthly report

A single report that tells you who to talk to and why.

Every month, you get a team roster with risk scores, trending direction (stable, rising, or falling), and the top contributing signals for each engineer. No guesswork. No "I had a feeling." Just data-backed patterns that tell you where to focus your 1:1s.

The report includes suggested interventions — not generic advice, but specific actions tied to the signals driving each score. When a score jumps from 25 to 68 in a single month, you know exactly what changed and what to do about it.

Sample Alert — High Risk
Schedule 1:1 with Sarah Chen
Risk score jumped from 25 to 68 this month. Primary signal: commit frequency dropped 45%. Secondary: disengaged from #engineering-culture channel.
Score
68/100
Trend
Rising
Tenure
1.9 yrs
Watch: Marcus Johnson
Score rising (34 to 42). PR review comments down 60% this sprint. Monitor next month.
Privacy Boundaries
Message volume & frequencyANALYZED
Channel engagement patternsANALYZED
Commit frequency & PR activityANALYZED
Tenure & PTO patternsANALYZED
Message content or DM textNEVER
Code quality or review opinionsNEVER
Personal device activityNEVER
Privacy & ethics — Patterns, not surveillance

Behavioral signals, not message content. Proactive conversations, not punitive actions.

The agent analyzes aggregate patterns — how often someone commits, how actively they participate in channels, whether their engagement is trending up or down. It never reads message content, DMs, or code review opinions. The difference matters: this is behavioral analytics, not workplace surveillance.

Engineers aren't notified of individual scores. The scores exist so you can have better 1:1s, not to create a ranking system. According to Gallup's 2024 State of the Workplace report, managers who have proactive retention conversations retain 26% more high performers than those who wait for exit interviews.

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Stop finding out about attrition when you get the resignation letter.

Starting at $2,000. Your agent watches the signals you can't track manually — and flags risk 30 days before it becomes a resignation.

Engineering Attrition Risk Scoring is included in every tier — no add-on required.

20-minute strategy call · No commitment

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