Build competitive intelligence briefs following the CI cycle — Plan, Collect, Analyze, Disseminate. Profile competitors, create feature comparison matrices, analyze pricing, build positioning maps, and identify win/loss patterns. Use when preparing for product launches, sales enablement, or strategic reviews.
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For each competitor, build a profile:
| Feature | Us | Competitor A | Competitor B | Competitor C |
|---|---|---|---|---|
| Feature 1 | ✅ | ✅ | ❌ | ✅ |
| Feature 2 | ✅ | ❌ | ✅ | ❌ |
| Pricing | $$$ | $$ | $$$$ | $ |
Plot competitors on a 2×2 perceptual map using two key dimensions:
| Scenario | We Won | We Lost | Pattern |
|---|---|---|---|
| vs Competitor A | 60% | 40% | We win on features, lose on price |
| vs Competitor B | 45% | 55% | They win on brand, we win on support |
For each competitor, define:
| Input | Required | Format |
|---|---|---|
| Competitor list | Yes | Names and categories |
| Dimensions to track | Yes | List of comparison areas |
| Internal product data | Yes | Features, pricing, positioning |
| Win/loss data | Recommended | Deal outcomes by competitor |
## Competitive Intelligence Brief — [Market] — [Period]
### Competitor Profiles
[Summary per competitor]
### Feature Comparison Matrix
[Table with feature-by-feature comparison]
### Positioning Map
Enterprise │ Competitor B
│ ★ US
│
───────────┼────────────────────
│ Competitor C
Basic │ Competitor A
└──Low Price──High Price──
### Win/Loss Summary
[Table with win rates and patterns]
### Battle Cards
[Per-competitor: positioning, talking points, counter-strategies]
### Early Warning Signals
1. Competitor A raised Series C — expect aggressive expansion
2. Competitor B hired ex-Google VP Product — product pivot likely
Build a competitive intelligence brief for our project management SaaS.
Direct competitors: Monday.com, Asana, ClickUp.
Indirect: Notion, Linear.
Compare on: features, pricing, target market, integrations.
Include battle cards for sales team.
| Check | Question |
|---|---|
| Correctness | Do referenced frameworks and standards match their official definitions? |
| Completeness | Are all key concepts covered without significant gaps for the stated audience? |
| Context-fit | Would this be useful for someone new to this domain, or is it too advanced/too basic? |
| Consequence | If a stakeholder acted on this immediately, what could they misinterpret? |
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Design rigorous A/B test plans with hypothesis, sample size calculation, Minimum Detectable Effect (MDE), randomization strategy, and decision rules. Includes guardrail metrics and rollout playbook. Use when planning product experiments, conversion optimization, or data-driven feature decisions.
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Review REST and GraphQL API designs for consistency, usability, and best practices. Covers naming conventions, versioning strategy, error format, pagination, authentication patterns, and breaking change detection. Use when reviewing API specs, designing new APIs, or auditing existing endpoints.
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Write Architecture Decision Records (ADRs) following the Michael Nygard format. Captures context, options considered, decision rationale, and consequences. Use when making technology choices, framework selections, or any architectural decision that future developers need to understand.
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Assess organizational readiness for financial audits (internal or external). Map assertions to account balances, check evidence completeness, score readiness using a Red/Amber/Green framework, and generate a remediation timeline. Aligned with SOX, IFRS, and GAAP audit standards. Use before scheduled audits or when preparing for first-time compliance.
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Design safe recurring Codex automations with clear prompts, outputs, schedules, and gating rules.
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Refine Product Backlog Items to meet INVEST criteria. Write User Stories with Acceptance Criteria in Given/When/Then format, estimate with Story Points, and flag dependencies. Use before sprint planning when backlog items need grooming. Do not use to prioritize the backlog — that is the Product Owner's decision.
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