initiative delivery

APEX Framework Implementation

Robert Matsuoka Updated 2026-03-11 apex apex-framework
apex tooling process q1-2026

Initiative: APEX Framework Implementation

The Bet

We believe that by providing Product Managers with AI-assisted Git-based workflows through Cursor IDE, we can: - Reduce the time from initiative to approved PRD by 50% - Increase PRD quality and completeness - Eliminate document sprawl across tools (Confluence, Google Docs, etc.) - Enable auto-generation of JIRA Epics and Stories from approved PRDs

Background

The current product development process suffers from: - Document sprawl across Confluence, Google Docs, and emails - No single source of truth for product specifications - Manual translation of PRDs to JIRA tickets - Lack of traceability from feature to original initiative - No systematic experiment-driven validation

Pilot Projects

Project Domain Description Status
Project Searchlight Analytics Lighthouse data integration, alerts Selected for greenfield stack
Demand360 Forecasting Demand analytics dashboard Data model changes needed
Tour Operator Apps B2B partner portal Active development

Key Decisions

Repository Architecture (2026-02-11)

Decision: Domain-centered product repositories with initiatives as directories.

Rationale: Customer-facing product surfaces (Pricing, Forecasting, Reporting) provide natural boundaries. Each initiative is a directory containing all related artifacts.

Branching Strategy (2026-02-11)

Decision: Start without PR workflow for simplicity. Use branch-per-initiative when collaboration needed.

Rationale: Reduce friction for PM adoption. Git handles merging well when work is in separate directories. Add PR workflow later if conflicts arise.

Technology Stack (2026-02-11)

Component Choice Rationale
Frontend Platform Vercel Fast deployment, composable stack
Authentication Clerk Plug-and-play auth with SSO support
Editing Cursor AI-assisted, developer-friendly
Knowledge Work Obsidian Local-first, Git-compatible
Backend Existing APIs GraphQL via monolith initially

PRD Auto-Generation (2026-02-11)

Decision: PRDs are auto-generated from initiative context (meetings, discovery, experiments).

Rationale: Reduces manual work, ensures consistency, provides input for engineering AI agents.

Success Metrics

Metric Baseline Target Measurement
PM Git adoption 0% 100% Active commits
Time: Initiative to PRD Unknown -50% Git timestamps
PRD completeness ~60% >90% Automated validation
Document sprawl High Zero Confluence audit

Timeline

Phase Dates Focus
Phase 1 Feb 11-18 POC with Cursor skills, test with Searchlight
Phase 2 Feb 19-28 Pilot with 2-3 PMs on selected projects
Phase 3 Mar 1-15 Iterate based on feedback, add JIRA integration
Phase 4 Mar 16-31 Full rollout, training, documentation