| name | product-intelligence |
| description | Automated competitor feature tracking, user feedback clustering, and feature validation for the Product department. Monitors competitor launches, aggregates user feedback signals, clusters by theme, and feeds the product self-improvement loop. Use when tracking competitor features, analyzing user feedback, validating feature hypotheses, or running the product UAOP pipeline. |
| risk | low |
| tags | ["product","research","competitive-intel","feedback"] |
| created | 2026-03-23T00:00:00.000Z |
| updated | 2026-03-23T00:00:00.000Z |
Product Intelligence — Product Department Intelligence Engine
Automated competitor feature tracking and user feedback synthesis. UAOP Stage 1 + Stage 5 for Product.
When to use
- Tracking competitor product launches and feature changes
- Synthesizing user feedback from multiple channels
- Validating feature hypotheses before building
- Quarterly product roadmap planning
- Sprint prioritization — "what should we build next?"
Pipeline
Step 1: Competitor Feature Scan
- Monitor competitor changelogs, release notes, Product Hunt launches
- Track feature additions/removals across LangChain, CrewAI, AutoGen
- Identify feature gaps (they have it, we don't) and advantages (we have it, they don't)
Step 2: User Feedback Aggregation
- Collect signals: support tickets, app reviews, community posts, NPS comments, sales call notes
- Cluster by theme using frequency + sentiment analysis
- Rank by impact: revenue-tied requests > nice-to-haves
Step 3: Feature Validation
- For each proposed feature: hypothesis, success metric, estimated effort (RICE score)
- Cross-reference against competitor data — are we filling a gap or innovating?
- Check ICP alignment — does the target user actually want this?
Step 4: Product Intel Report
- Top feature requests (by cluster frequency)
- Competitor moves (new features, pricing changes, positioning shifts)
- Recommended priorities (RICE-ranked)
- Experiment proposals (hypothesis + metric + sample size)
Step 5: Self-Improvement Loop
- Track feature adoption rates post-launch
- Measure experiment win rates
- Reinforce: features with high adoption → invest more; low adoption → investigate why
- Feed outcomes into next cycle's prioritization
Cadence
WEEKLY: Competitor changelog scan + feedback triage
MONTHLY: Full product intel report + RICE re-ranking
QUARTERLY: Roadmap review informed by cumulative intelligence
Agents
| Agent | Role |
|---|
| pm-agent (L0) | Owns product strategy, approves priorities |
| feedback-synthesizer (L4) | Clusters and themes user feedback |
| trend-researcher (L4) | Tracks competitor movements |
| experiment-tracker (L4) | Monitors experiment results |
| requirements-analyst (L4) | Validates feature specs |
