Research

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Identify target audience, map the topic landscape, analyze competitive content

Hats
2
Review Agents
1
Review
Auto
Unit Types
Research
Inputs
None

Hat Sequence

1

Audience Analyst

Focus: Map the developer audience — skill levels, technology stacks, pain points, learning preferences, and where they consume technical content. Transform community signals into targetable audience segments.

Produces: Developer audience segments with technical profiles, content format preferences, and community presence mapping.

Reads: Intent problem statement, any existing analytics or community data.

Anti-patterns (RFC 2119):

  • The agent MUST NOT define developer segments solely by job title without considering skill level and technology context
  • The agent MUST NOT assume content preferences without evidence from community behavior
  • The agent MUST NOT conflate beginner and advanced audiences into a single "developers" segment
  • The agent MUST NOT ignore platform-specific audience differences (e.g., Twitter/X vs. Reddit vs. Hacker News)
  • The agent MUST distinguish between developers who build with the technology and those who evaluate it
2

Topic Scout

Focus: Scan the technical landscape for trending topics, underserved content areas, and opportunities where the team's expertise can fill a gap. Analyze conference programs, blog ecosystems, and community discussions to identify high-value content topics.

Produces: Topic landscape with trending themes, competitive content analysis, content gap map, and recommended topic shortlist ranked by audience demand and team credibility.

Reads: Audience analyst's segment profiles from the unit's ## References section.

Anti-patterns (RFC 2119):

  • The agent MUST NOT recommend topics where the team lacks genuine technical credibility
  • The agent MUST NOT chase trends without validating sustained developer interest
  • The agent MUST NOT ignore existing content saturation when recommending topics
  • The agent MUST NOT limit scanning to a single platform or content format
  • The agent MUST assess whether a topic is still timely or already past peak interest

Review Agents

Relevance

Mandate: The agent MUST verify research targets genuine developer needs and credible topic opportunities.

Check:

  • The agent MUST verify that audience segments are based on observable signals, not assumptions about developer behavior
  • The agent MUST verify that topic recommendations align with both audience demand and team expertise
  • The agent MUST verify that competitive content analysis covers current materials, not outdated references
  • The agent MUST verify that content gaps are genuine opportunities, not areas competitors wisely avoided

Research

Criteria Guidance

Good criteria examples:

  • "Audience landscape identifies at least 3 developer segments with skill levels, pain points, and preferred content formats"
  • "Topic scan surfaces at least 5 trending or underserved topics with competitive content analysis for each"
  • "Research brief maps existing content gaps where the team has unique expertise to contribute"

Bad criteria examples:

  • "Research is done"
  • "Audience is understood"
  • "Topics are identified"

Completion Signal (RFC 2119)

Research brief MUST exist with developer audience segments defined, topic landscape mapped, and content gaps identified. All claims reference specific sources (community forums, conference programs, analytics, surveys). Topic scout MUST have validated that selected topics align with audience needs and the team's technical credibility.