The current commit graph visualization in Monolex provides branch-level views through a comprehensive TypeScript module. However, this implementation lacks commit-level granularity that would expose the true Git DAG structure to users.The Work-Wiki system requires complete transparency of AI development work. For git operations, this means showing not just which branches exist, but the precise commit relationships that form the development history.
WHAT HUMAN NEEDS TO SEE | WHAT CURRENT SYSTEM SHOWS(For effective feedback) | (Branch-level only)---------------------------------+-------------------------X Individual AI commits | V Branch namesX Commit messages | V Branch tips onlyX Parent-child relationships | V Merge/diverge indicatorsX Parallel development paths | X Hidden between branchesX Commit timestamp ordering | X Not shownX Merge commit complexity | X Single connection shown
THE CENTER REQUIREMENT:Human sees AI work → Human understands → Human provides feedbackCURRENT SYSTEM BREAKS THIS LOOP:Step 1: AI creates 50 commits across 3 branches │Step 2: Current system shows: 3 branch nodes, 2 connections │Step 3: Human sees: "There are 3 branches" │Step 4: Human cannot provide specific feedback because: ├── Cannot see which commits did what ├── Cannot see commit order ├── Cannot see merge decisions └── Cannot see parallel work streamsRESULT: Feedback loop efficiency < 10% (Human can only comment on branch names, not actual work)
CURRENT STATE (Branch-Level):AI Work ────────────────────────────────────────> Transparency100 commits 3 branches shown │ v Human Understanding: ~3% (Can see: 3 branch names) │ v Feedback Quality: ~3% ("Maybe merge feature branch?")────────────────────────────────────────────────────────────────TARGET STATE (Commit-Level DAG):AI Work ────────────────────────────────────────> Transparency100 commits 100 commits shown + parent links + lanes │ v Human Understanding: ~80% (Can see: all decisions) │ v Feedback Quality: ~80% ("Commit 47 approach is wrong")
CURRENT PERFORMANCE:Data Volume:├── Branches per repo: 5-50 (typical)├── Connections: 5-100├── SVG nodes: 10-150└── Render time: <100msScalability:├── Large repos (1000+ branches): May lag├── No virtualization└── Full SVG re-render on update
How This Analysis Serves the Human ◈ AI Feedback Loop
This chapter contributes by:1. TRANSPARENCY ├── Documents current implementation completely ├── Identifies exactly what is visible vs hidden └── Establishes baseline for improvement measurement2. VISUALIZATION ├── Shows current architecture in diagrams ├── Compares branch-level vs commit-level approaches └── Illustrates gap between current and target3. FEEDBACK ENABLEMENT ├── Quantifies feedback loop efficiency (~3% current) ├── Defines target efficiency (~80%) └── Establishes upgrade criteriaCONNECTION TO MONOKINETICS:This analysis enables Human to understand current system limitations,so Human can provide effective feedback on upgrade requirements.This IS the feedback loop in action.
Next: Upgrade Requirements
Documenting all requirements for the Git Commit Graph upgrade