The Problem — Why This Agent Matters
Current Pain (Manual CI Research)
Multi-source search
→
Copy & consolidate
→
Manual compare
→
Late action
Core gap: PMs don't lack information — they lack decision-ready synthesis.
What Reviewers Care About
Traceability — Every claim links to a source
Recency — Signals ≤ 7 days old by default
Actionability — Priority labels + next steps
4h+
Weekly manual baseline
6+
Signal categories
3
Comparable variants
15min
Cross-team explainability
What We Built — How Users Interact
Interaction Flow
PM Input
→
Agent Processing
→
Structured Output
| Capability | Input | Output |
|---|---|---|
| Competitive Search | Competitor + domain | Multi-slice decision package |
| Benchmark Eval | Dataset manifest | Scorecard + comparison |
| Watch Monitor | Priority config | P0/P1/P2 action items |
Output Preview
Full output includes: executive summary, community voice, watch items, and PM recommendations.
How It Works — Architecture
End-to-End Pipeline
PM / Reviewer
→
Web / CLI
→
Agent Orchestration
→
Search + Synthesis
→
Benchmark Artifacts
Evaluation Pipeline
Dataset
→
Manifest
→
Scorecard
→
Markdown / CSV / JSON
Search Output — Three Structured Slices
All three screenshots from a single search output — showing how the agent transforms scattered signals into a reviewable decision package.
1. Key Developments
Chronological facts with impact severity ratings (H/M) and source attribution.
2. Community Voice
KOL + social sentiment aggregation preserving source attribution (X / Reddit).
3. Watch Items
Prioritized actions (P0/P1/P2) with confidence labels (Fact / Rumor / Sentiment).
Together, these give PMs everything to brief leadership in ≤ 5 minutes.
Output Deep Dive — Why This Structure Works
Watch Items — Deep Dive
What Each Slice Answers
Key Developments → "What happened?" — Chronological facts with impact severity.
Community Voice → "What are people saying?" — KOL + social sentiment with attribution.
Watch Items → "What should I do?" — Prioritized actions with confidence tags.
Together, these three slices give a PM everything needed to brief leadership in ≤ 5 minutes — no further research required.
Results & Impact
90
Total Score
88%
Citation Survival
84%
Timeliness Hit
4.3/5
PM Usability
52s
Latency
| Variant | Score Band | Citation | Timeliness | Position |
|---|---|---|---|---|
| CI Agent | 90 Excellent | 88% | 84% | Leading |
| Copilot CLI | 76 Strong | 72% | 68% | Upper-middle |
| General Chat | 62 Mixed | 55% | 50% | Middle |
+13 pts vs prompt-only baseline
Evaluation Framework
Pipeline
Dataset
→
Manifest
→
Scorecard
→
Report
Objective dimensions (72%): Citation accuracy, timeliness, structure compliance
Subjective dimensions (28%): PM usability, actionability, readability
Performance Bands
| Band | Score | Meaning |
|---|---|---|
| Excellent | ≥ 82 | Ship-ready, minimal revision |
| Strong | ≥ 70 | Usable with minor edits |
| Mixed | ≥ 55 | Needs targeted improvements |
| Weak | < 55 | Significant gaps |
PM Expectations & Risks
Sprint 1 Expectations
Met — Structured multi-slice output with source attribution and priority labels.
Partially Met — Real-time monitoring (polling implemented, alerting deferred to Sprint 2).
Verdict: Usable tool exceeding baseline by +13 pts, meets "Excellent" band threshold.
Risk Register
P0 Source freshness decay
Search APIs may lag behind real-time events by 12–48h.
P1 LLM hallucination on niche competitors
Low-frequency entities trigger confabulation in synthesis step.
Mitigation
Citation-survival checks + confidence labels (Fact / Rumor / Sentiment) flag uncertain claims.
Roadmap
Sprint 2
→
Sprint 3
→
Sprint 4
→
Final
| Phase | Deliverable | Success Criteria |
|---|---|---|
| Sprint 2 | Alert pipeline + dashboard MVP | P0 alerts delivered within 1h of detection |
| Sprint 3 | Multi-competitor comparison + trend analysis | ≥ 3 competitors per query, trend accuracy ≥ 80% |
| Sprint 4 | Self-improving eval loop + PM feedback integration | Score ≥ 92, PM satisfaction ≥ 4.5/5 |
| Final | Production deployment + cross-team rollout | 5+ PM teams onboarded, < 30s latency |