Multi-Phase Plan to Increase AI Effectiveness

Synthesized from: CC /insights report (3,336 messages, 439 sessions), Optimizing AI Benefits strategy, Dynalist AI notes (1,233 lines of captured ideas), and current KB review. Focused on Claude Code as primary tool, with SMART DEBT Mission alignment.

Executive Summary

You are already a power user — 439 sessions, 276 commits, 11,444 Bash calls in one month. But the CC /insights report reveals a consistent pattern: Claude gets you 80-90% of the way but rarely nails the last mile. The three root causes are: (1) no persistent CLAUDE.md guardrails, (2) no verification-before-done protocol, and (3) underuse of skills, hooks, and automation features.

This plan addresses those gaps in four phases: Environment (WSL vs Windows clarity), Foundation (eliminate friction), Amplify (compound capabilities via skills and workflow), and Accelerate (autonomous pipelines and scaling).

Phase 1: Environment — WSL vs Windows (Priority: Decide First)

Running CC from the right environment eliminates an entire class of friction. Your files live on Windows (D:\), your AI config SSoT lives in WSL (~/config-ai/), and Obsidian watches Windows paths. Choosing wrong means path translation headaches, cross-filesystem I/O penalties, and split configuration.

The Rule: Launch CC Where Your Files Live

Your task	Launch CC from	Why
KB work (this repo)	Windows	Files on `D:\`. Obsidian watches Windows paths. No build tools needed — just Read/Write/Edit/Grep. Zero benefit from WSL.
Monorepo dev	WSL (if code moves to WSL filesystem) or Windows (if code stays on `D:\`)	Dev tooling (npm, pnpm, astro, vite, playwright) runs better on native Linux. BUT accessing `D:\` from WSL via `/mnt/d/` adds I/O overhead and makes git slower. Only worth it if you move the repo into WSL filesystem.
Python utilities	WSL	Python ecosystem is Linux-native. Scripts likely already in `~/`.
Quick research / writing	Either	No filesystem dependency.

Why NOT Always WSL

Cross-filesystem penalty: Accessing /mnt/d/ from WSL is significantly slower than native Windows access to D:\ — especially for git operations and file-heavy tasks like your KB (2,431 Markdown file operations in one month per /insights).
Path mismatch: WSL CC uses /mnt/d/FSS/KB/Business/... but Obsidian sees D:\FSS\KB\Business\.... Slash commands, CLAUDE.md references, and file paths in notes all need translation.
Obsidian won’t see WSL changes instantly: File watchers across the WSL/Windows boundary are unreliable. Edits made via WSL CC to /mnt/d/ files may have delayed visibility in Obsidian.
No dev tooling needed for KB: Your KB work is markdown files — Read, Write, Edit, Glob, Grep. These work identically on both platforms. WSL adds complexity for zero benefit.

Why WSL For Dev Work (When Code Is On WSL Filesystem)

Native bash, better tool compatibility
npm/pnpm/node run faster on native Linux filesystem
Your AI config SSoT (~/config-ai/) is there
Playwright, astro, vite — all Linux-first
Better sandboxing support

Decision: Current Recommendation

For now: stay on Windows for KB work. This is correct.

Consider moving the monorepo INTO the WSL filesystem (e.g., ~/projects/monorepo/) when you’re ready to invest in that migration. Until then, running CC from Windows for code on D:\ is more effective than running WSL CC against /mnt/d/.

1.0 Environment Setup (Done / In Progress)

Windows settings.json created at C:\Users\Admin\.claude\settings.json matching WSL permissions
Slash commands created in both C:\Users\Admin\.claude\commands\ (Windows paths) and \\wsl$\Ubuntu-24.04\home\ta\.claude\commands\ (WSL paths)
Consider: move monorepo to WSL filesystem for dev sessions (Later)
Consider: when creating project-level .claude/settings.json for the KB repo, use Windows paths

Phase 2: Foundation — Eliminate Friction (Priority: Immediate)

These actions directly address the top friction points identified in your CC /insights report.

2.1 Create and Maintain CLAUDE.md Files

Problem: No CLAUDE.md means Claude has no guardrails about deployment architecture, testing requirements, or project conventions. Same mistakes recur across sessions.

Actions:

Run /init in your monorepo to bootstrap CLAUDE.md
Add verification rules (see below)
Add deployment architecture context (local vs Cloudflare, etc.)
Add coding standards, naming conventions, file organization rules
Create ~/.claude/CLAUDE.md for personal cross-project preferences
Schedule monthly CLAUDE.md audits (1st of each month)

Template for Monorepo CLAUDE.md:

## Workflow Rules
- After implementing changes, verify by running deployment/build scripts and checking output. Never claim "done" without testing.
- When working from task list, do final grep pass for remaining old/replaced values across ALL file types.
- Work through tasks one at a time: implement -> verify -> next. Do NOT batch.

## Deployment and Config
- For config changes (YAML, JSON, shell), diff final files after editing.
- Check for: domain names, provider names, URLs, environment values.
- [ADD YOUR SPECIFIC DEPLOYMENT ARCHITECTURE HERE]

## Stack
- [ADD YOUR TECH STACK DETAILS]

## Testing
- [ADD YOUR TEST COMMANDS AND EXPECTATIONS]

2.2 Implement Verify-Before-Done Protocol

Problem: Claude claims completion while bugs linger (50% dissatisfaction rate in insights). Biggest friction is premature “done” on deployment configs.

Actions:

Add the verification rules above to every project CLAUDE.md

At start of task sessions, paste the atomic workflow prompt:

Work through TASKS.md one item at a time. For each item:
implement the fix, then immediately verify it works.
Do NOT move to the next item until current one is confirmed working.
Show status update after each item.

After changes, require: grep for stale refs -> run build -> cat modified files -> then report

2.3 Set Up Hooks

Problem: Manual verification is inconsistent. Automate the checks.

Actions:

Create .claude/settings.json with postEdit hook:

{
  "hooks": {
    "postEdit": {
      "command": "grep -rn 'TODO_REPLACE\\|FIXME\\|old-domain' --include='*.yaml' --include='*.json' --include='*.py' . || true",
      "description": "Check for stale references after every file edit"
    }
  }
}

Add pre-commit hook for deployment config validation
Test hooks across a few sessions, refine patterns

2.4 Run CC /insights Monthly

Problem: No systematic feedback loop on AI usage patterns.

Actions:

Run /insights on the 1st of each month
Review report, extract action items
Update CLAUDE.md and this plan based on findings
Track: friction reduction, satisfaction improvement

Phase 3: Amplify — Compound Capabilities via Skills (Priority: Next 2-4 Weeks)

Skills are the highest-leverage investment. Each skill you build compounds future productivity.

3.1 Install Priority Community Skills

Actions:

Install Anthropic official skills: /plugin marketplace add anthropics/skills
Install Superpowers (Obra): /plugin marketplace add obra/superpowers-marketplace
- Adds /brainstorm and /write-plan — directly supports planning-first workflow
Install Playwright Skill for E2E testing
Evaluate frontend-design skill for UI work
Browse https://awesomeclaude.ai/ and https://skillsmp.com/ for relevant skills

3.2 Build Custom Skills for Your Workflow

Based on your most common session patterns (fix-from-task-list, confirm-then-implement):

Skill 1: /taskfix — Task List Fix Workflow

## Task Fix Workflow
1. Read the task file specified by the user
2. For each issue, implement the fix across all relevant files
3. After ALL changes, grep for old/replaced values across codebase
4. Run the deployment or build script to verify
5. Cat final version of each modified file to confirm
6. Report checklist summary of what was done and verified
Never report completion without steps 3-5.

Skill 3: /codebase-audit — Proactive Health Check

## Codebase Health Audit
1. Glob deployment configs, check for inconsistencies
2. Run existing test suites, capture warnings/errors
3. Scan for TODO/FIXME/HACK comments, assess staleness
4. Check JSON configs are valid and schemas haven't drifted
5. Write prioritized task list with severity ratings

Actions:

Use /skill-creator to build each skill with proper structure
Test each skill across 3-5 sessions
Iterate based on results (use skill-creator iterate mode)
Document what works in your skills knowledge

3.3 Establish Multi-Tool Workflow

Actions:

Document your standard workflow: CC for terminal tasks + Cursor for visual editing
Set up shared context via CLAUDE.md and .cursorrules in same project
Use Gemini free tier for prototyping and scaffolding
Use GLM-4.7 ($3-6/mn) via OpenRouter for routine coding
Reserve Claude Pro for: complex architecture, security, business logic

3.4 Improve Context Engineering

Actions:

Restructure CLAUDE.md as roadmap (keep <100 lines, import external docs via @)
Create .claude/rules/ with modular rules:
- code-style.md — coding standards
- testing.md — test requirements
- deployment.md — infrastructure rules
- security.md — security requirements
Set up Claude web projects for different contexts (dev, writing, research)
Use # shortcut to add insights during sessions

Phase 4: Accelerate — Autonomous Pipelines (Priority: Month 2+)

Move from reactive fix-it cycles to proactive, autonomous workflows.

4.1 Headless Mode for Automated Tasks

Problem: 73 sessions were “fix issues from task list” — this is automatable.

Actions:

Set up headless CC runs for routine task-list processing:

claude -p "Read TASKS.md and fix all listed issues. After fixing, grep entire repo for stale references. Run build and report results." --allowedTools "Edit,Read,Bash,Write,Glob"

Integrate into CI/CD pipeline for config validation
Start with low-risk tasks, expand as confidence grows

4.2 Parallel Agent Workflows

Problem: Sequential multi-file refactors are slow and miss cross-file drift.

Actions:

For large refactors, use TaskCreate to spawn sub-agents per language domain:
- Python agent for backend logic
- TypeScript agent for frontend types
- Config agent for YAML/JSON consistency
Parent agent coordinates and runs integration tests after all complete
Use tmux for parallel CC sessions

4.3 Proactive Issue Detection

Problem: Issues accumulate in task lists; better to catch them early.

Actions:

Run /codebase-audit skill at start of each week
Set up scheduled headless runs for:
- Config drift detection
- Stale reference scanning
- Dependency mismatch checking
Feed audit results into TASKS.md for systematic resolution

4.4 Async/Overnight Development

Actions:

Define features clearly before ending work session
Run headless CC with task file overnight
Review results in morning
Best candidates: local models for cost, well-defined tasks with clear completion criteria

Phase 5: SMART DEBT Mission Acceleration (Ongoing)

5.1 Build Mission-Specific Skills

SvelteKit component generators for debt calculators
Content generation skill for financial education
Smart debt coach automated service prototype skill
Strategic planning skill (from Rick Moretti YT)

5.2 Use Claude Artifacts

Explore for creating micro apps (debt calculators, interactive tools)
Interactive AI-driven courses for financial education
https://kotrotsos.medium.com/claude-artifacts-the-features-that-replace-500-month-in-software-a44388375280

5.3 Leverage AI for Content and Marketing

Use NotebookLM for research synthesis and podcast generation
Use Napkin AI for visual content from text
Use perspective prompting for strategic decisions
Multi-prompt important strategic questions across 3 models

Tracking and Review

Monthly Review Checklist (1st of each month)

Run CC /insights and review report
Update CLAUDE.md files based on insights
Review and iterate on custom skills
Audit this plan: what’s done, what’s blocked, what’s changed
Review subscription ROI

Success Metrics

Metric	Current (from /insights)	Target
Satisfaction rate	~50%	>80%
“Premature done” incidents	Frequent	Rare (hooks catch them)
Sessions with CLAUDE.md	0%	100%
Custom skills in use	0	5+
Monthly /insights runs	0	1/month

Quick Wins (Do This Week)

Run /init in monorepo and add verification rules to CLAUDE.md
Install Superpowers plugin
Set up one postEdit hook for stale reference detection
Use verify-before-done prompt at start of next 3 sessions
Run /insights next month to measure improvement

Appendix: Key Resources Referenced

CC /insights report: \\wsl$\Ubuntu-24.04\home\ta\.claude\usage-data\report.html
Optimizing AI Benefits: Optimizing AI Benefits
Skills ecosystem: 02_Skills
AI Dev Workflow: 03_AI Dev Workflow
CC Best Practices (Anthropic)
Skills Best Practices
Free CC Course