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whetstone_DSL/docs/PROJECT_PORTFOLIO_WORKFLOW_2026-02-26.md

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Project Portfolio Workflow (2026-02-26)

Purpose

Organize long-horizon projects into one execution system so Whetstone can either:

  • finish existing MVPs from other machines/repos, or
  • rebuild from scratch with deterministic quality gates.

Current Inputs Found

  • Whetstone core planning and sprint execution docs under CLionProjects/whetstone_DSL/docs/
  • A project archive bundle under drive_projects/drive-download-20260217T155135Z-1-001/ (mixed docs, requirements, roadmaps, MVP concepts)
  • No literal project_docs/ directory found under /home/bill/Documents

Portfolio Lanes

  1. MVP_IMPORT
  • Existing codebase exists elsewhere (GitHub/private machine).
  • Goal: ingest, normalize, and harden to production thresholds.
  1. GREENFIELD
  • No code to import or import is lower value than rebuild.
  • Goal: generate from architecture + constraints and iterate with strict validation.

Canonical Project Record (one row per project)

Use one table (or JSONL) with these required fields:

  • project_id
  • name
  • lane (MVP_IMPORT or GREENFIELD)
  • source_of_truth (repo URL / machine path / doc path)
  • problem_statement
  • target_users
  • critical_constraints (latency, memory, security, platform)
  • status (intake, specifying, building, hardening, release_ready, paused)
  • next_gate
  • owner (human/agent)
  • last_validated_at

Intake Gate (must pass before any build work)

  1. Confirm the project has one primary source of truth.
  2. Convert intent into a compact execution spec:
  • target runtime/platform
  • must-have features
  • no-go constraints
  • acceptance tests
  1. Choose lane (MVP_IMPORT vs GREENFIELD) explicitly.
  2. Create first 3-7 taskitems with deterministic completion checks.

Lane Workflows

A) MVP_IMPORT Workflow

  1. Snapshot
  • Pull/clone code and freeze baseline hash.
  • Capture run/build/test state as-is.
  1. Normalize
  • Align repo layout, dependency pinning, and CI test entrypoints.
  • Add missing schema/contract tests for core behavior.
  1. Gap Audit
  • Compare MVP behavior vs current intent docs.
  • Tag each gap: bug, missing feature, quality, security, scalability.
  1. Hardening
  • Run strict taskitem pipeline on highest-risk gaps first.
  • Require failing test first for each fix.
  1. Promotion
  • Promote only after acceptance suite and non-functional checks pass.

B) GREENFIELD Workflow

  1. Architecture Freeze v0
  • Generate project skeleton + module contracts + acceptance tests.
  1. Execution Slices
  • Build in thin vertical slices with runnable tests every slice.
  1. Constraint Enforcement
  • Ensure projection/environment constraints are first-class in taskitems.
  1. Hardening
  • Reliability, determinism, performance, and security passes.
  1. Promotion
  • Same production gates as import lane.

Readiness Score (0-5 each, promote at >= 20/25)

  • Spec Clarity
  • Deterministic Test Coverage
  • Operational Readiness (build/release/runbook)
  • Security Posture
  • Performance Budget Confidence

Weekly Cadence

  1. Intake/triage (new or updated projects)
  2. Lane assignment and top-3 portfolio priorities
  3. Whetstone execution runs (taskitem batches)
  4. Human review on blockers and lock-level decisions
  5. Closeout: score update + next gate assignment

Suggested Immediate Backlog

  1. Create project_registry.jsonl in Whetstone docs/data.
  2. Import project list from your planning docs (especially the drive archive and any external repos).
  3. For each project, set lane and next gate.
  4. Start with 3 projects only:
  • one MVP_IMPORT with highest near-term value
  • one GREENFIELD infrastructure library
  • one GREENFIELD demonstrator product
  1. Run strict taskitem generation for those 3 and calibrate thresholds before scaling portfolio width.

Notes From Existing Whetstone State

  • You already have mature sprint/taskitem infrastructure and closeout artifacts.
  • Active gap logs indicate the main risk now is execution quality drift, not idea scarcity.
  • Portfolio organization should therefore optimize for:
    • deterministic closeout quality
    • clear source-of-truth linkage
    • controlled concurrent project count