[Feature] Intelligence Loop / Analytics Engine #65

New Issue

2026-02-10T16:00:50Z

chihlasm commented

2026-02-10 16:00:50 +00:00

(Migrated from github.com)

Summary

Build an analytics engine that mines session data to: surface trending issues, identify dead-end tree branches, recommend tree improvements, detect when custom steps should become permanent branches, and provide manager dashboards with ROI metrics.

Why

This is THE compounding moat. Every session makes the product smarter. No competitor can replicate accumulated operational intelligence. This transforms ResolutionFlow from a static playbook into a learning system.

The Data Flywheel

More sessions → better analytics → smarter trees → faster resolutions → more adoption → more sessions

Components

Tree Health Scores

Custom step frequency: engineers keep adding steps → tree missing a branch
Abandonment rate: started but not completed → tree isn't leading to resolutions
Staleness: no updates in X months for fast-changing technology
Health badge (green/yellow/red) on tree library cards

Path Analytics ("The Road Most Traveled")

Badge on decision nodes: "78% of engineers chose Option B here"
Solution node stats: "Resolved the issue 92% of the time"
Stuck points: "Engineers often add a custom step here"
Needs 10+ sessions per tree to be statistically meaningful

Manager Dashboard

Team-wide metrics: sessions/day, avg resolution time, tree usage
Engineer efficiency comparison
ROI calculator: time saved vs manual troubleshooting
Trending issues over time

Auto-Suggest Tree Improvements

"35% of engineers add 'Check MFA Token' after 'Auth Failed' — suggest new branch?"
One-click for tree author to review and approve
Tree evolves from real usage data

Depends On

#56 Step-Level Time Tracking + Session Outcomes
Sufficient session volume (suggest: start collecting data now, build analytics when volume is meaningful)

Sources

.claude/docs/ai/resolutionflow/10x/session-1.md — Massive Opportunity #1 (THE moat)
docs/plans/2026-02-04-feature-ideas-brainstorm.md — Ideas 5, 9, 10

Priority

Explore — the ultimate differentiator, build incrementally as data accumulates

## Summary Build an analytics engine that mines session data to: surface trending issues, identify dead-end tree branches, recommend tree improvements, detect when custom steps should become permanent branches, and provide manager dashboards with ROI metrics. ## Why This is **THE compounding moat**. Every session makes the product smarter. No competitor can replicate accumulated operational intelligence. This transforms ResolutionFlow from a static playbook into a learning system. ## The Data Flywheel ``` More sessions → better analytics → smarter trees → faster resolutions → more adoption → more sessions ``` ## Components ### Tree Health Scores - Custom step frequency: engineers keep adding steps → tree missing a branch - Abandonment rate: started but not completed → tree isn't leading to resolutions - Staleness: no updates in X months for fast-changing technology - Health badge (green/yellow/red) on tree library cards ### Path Analytics ("The Road Most Traveled") - Badge on decision nodes: "78% of engineers chose Option B here" - Solution node stats: "Resolved the issue 92% of the time" - Stuck points: "Engineers often add a custom step here" - Needs 10+ sessions per tree to be statistically meaningful ### Manager Dashboard - Team-wide metrics: sessions/day, avg resolution time, tree usage - Engineer efficiency comparison - ROI calculator: time saved vs manual troubleshooting - Trending issues over time ### Auto-Suggest Tree Improvements - "35% of engineers add 'Check MFA Token' after 'Auth Failed' — suggest new branch?" - One-click for tree author to review and approve - Tree evolves from real usage data ## Depends On - #56 Step-Level Time Tracking + Session Outcomes - Sufficient session volume (suggest: start collecting data now, build analytics when volume is meaningful) ## Sources - `.claude/docs/ai/resolutionflow/10x/session-1.md` — Massive Opportunity #1 (THE moat) - `docs/plans/2026-02-04-feature-ideas-brainstorm.md` — Ideas 5, 9, 10 ## Priority **Explore** — the ultimate differentiator, build incrementally as data accumulates

chihlasm commented

2026-03-21 15:24:39 +00:00

(Migrated from github.com)

Completed — Knowledge Flywheel (Phase 3) implements this: AI session analysis → flow proposals, knowledge gap detection, FlowPilot analytics dashboard.

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Reference: chihlasm/resolutionflow#65