Skill UI

A comprehensive reference architecture for deploying meeting intelligence platforms (like Granola) across large organizations. This blueprint details the core data capture pipeline, integration topology using middleware (Zapier), multi-workspace structure (Sales, HR, Engineering), and robust security layers (SSO, AES-256) to ensure automated workflows from meeting to action item across all departments.

This architecture provides a scalable, production-ready framework for integrating AI candidate analysis with Juicebox. It manages automated data ingestion from job descriptions, ranks candidates using intelligent scoring, handles result caching, and facilitates seamless data export to major ATS platforms like Greenhouse and Lever. Designed for high-volume, complex hiring pipelines requiring data freshness, deduplication, and robust scaling.

A two-layer memory architecture designed for managing corporate board meeting decisions. It separates raw, unfiltered transcripts (Layer 1) from founder-approved, canonical decisions and action items (Layer 2). This system ensures historical accuracy, tracks overdue tasks via commands like /cs:review, and actively detects topic contradictions and conflicts to maintain governance integrity.

Guides founders on AI positioning, ICP definition, messaging architecture, and quarterly PMF validation so they can translate technical capabilities into the business outcomes buyer-facing teams care about.

A comprehensive framework for structuring meetings, defining metric reporting, and managing decision-making velocity in rapidly scaling companies. It addresses common growth pains like misalignment, ineffective leadership meetings, and slow planning cycles by establishing a five-level meeting architecture and weekly health dashboards. Ideal for companies transitioning from startup to enterprise stage.

This reference architecture outlines a comprehensive financial stack for startups. It centralizes core financial functions—including banking (Mercury), payroll (Gusto), revenue/expense tracking (Stripe/Brex), and advanced bookkeeping/tax services (Fondo)—into a unified data flow. It helps founders and finance teams manage everything from daily transactions to monthly closing, tax filings (like R&D credits), and generating board reports efficiently.

This reference architecture details the design of a multi-tenant integration layer for the MindTickle sales enablement platform. It strictly enforces tenant data isolation across all components (database, cache, queue) to ensure that organizational data remains separate. The system manages user synchronization (via SCIM 2.0), tracks course progress, records quiz results, and aggregates team readiness reports, making it ideal for complex SaaS enterprise deployments.

A specialized AI agent designed to build and audit business models using Alexander Osterwalder’s comprehensive 9-block framework. It moves beyond mere filling of blocks, focusing on establishing the critical logical 'lock' between core components like Value Propositions, Customer Segments, and Cost Structures. This tool is ideal for initial business architecture design, auditing existing models for internal consistency (e.g., ensuring every key activity has a corresponding cost), or re-validating the core logic during a strategic pivot.

This rigorous review simulates an interrogation by a Chief AI Officer (CAIO). It pressure-tests any AI plan across six critical dimensions: evaluation metrics, failure mode handling (SLOs), international regulatory compliance (e.g., EU AI Act), technical architecture (API vs. fine-tuning), cost economics, and necessary team roles. Use this when ensuring AI features are robust, safe, and commercially sound before launch or major investment.

Provides high-level strategic guidance for founders and Chief Data Officers (CDOs) in startups. This skill covers critical decisions such as AI training data rights and consent provenance, selecting optimal data architectures (warehouse, lakehouse, data mesh), valuing customer data as a strategic asset for M&A or fundraising, and planning data team organizational evolution. It focuses exclusively on strategic decision-making, not tactical engineering.

Rex is a foundational agent designed to transform vague, high-level user intent into precise, unambiguous, and structured technical specifications. It acts as a requirements analyst, asking clarifying questions, identifying edge cases, and defining scope using frameworks like MoSCoW and User Stories. It ensures that all subsequent development stages (planning, architecture, implementation) work from a single, agreed-upon artifact, minimizing guesswork and scope creep.