instructional-designer

Three-layer AI context framework for project development. Bootstraps docs/architect/ with Product, Project, and Task layers. Auto-commits on plan approval and nudges feature-dev for implementation.

Expectation Architecture for all delivery modes. Routes context to the right mode (strategy, keynote, training), maps expectations, detects mode drift, designs deliverables, evaluates sessions. 16 skills across orchestration, strategy, keynote, and training. Built on UX² = User Expectations × User Experience.

Ingest Claude Code JSONL session transcripts into Supabase for analytics and learning loop closure. Log, batch-ingest, and query session data across all your repos.

Jobs 2B Done — Run JTBD analysis on sales, coaching, and industry call transcripts with UXinator Expectation Mapping. Pulls transcripts from Notion or pasted text, enriches with HubSpot and Clay connections, tracks coaching series with session numbering, saves structured analysis to organized folders, and populates the JTBD Analyses Notion database.

Brand Voice transforms scattered brand materials into enforceable AI guardrails — automatically. It searches across Notion, Google Drive, Confluence, Gong, Slack, and meeting transcripts to distill your strongest brand signals into a single source of truth, then applies them to every piece of AI-generated content. The more your team creates with Claude, the more consistent your brand becomes.