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docs: add AI-first self-improvement philosophy and architecture principles #36

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Summary

Establishes comprehensive framework for how Amplifier improves itself through AI-first development with 44 core principles organized into People, Process, Technology, and Governance & Operations categories.

Key Changes

New Documentation

  • AMPLIFIER_SELF_IMPROVEMENT_PHILOSOPHY.md: Complete 44-principle framework establishing how AI agents work on Amplifier's own codebase

Integration Updates

  • CLAUDE.md: Added as first import so Claude Code sessions load this philosophy immediately
  • AGENTS.md: Added prominent "Foundation" section directing all AI agents to read philosophy first
  • README.md: Added reference in Vision section highlighting self-improvement capability
  • ai_context/IMPLEMENTATION_PHILOSOPHY.md: Added context linking to broader self-improvement principles
  • ai_context/MODULAR_DESIGN_PHILOSOPHY.md: Added context connecting "bricks and studs" to self-improvement system

Principles Overview

People (6 principles)

  • Small AI-first working groups
  • Strategic human touchpoints only
  • Prompt engineering as core skill
  • Test-based verification over code review
  • Conversation-driven development
  • Human escape hatches always available

Process (13 principles)

  • Regenerate, don't edit
  • Contract-first everything
  • Tests as quality gate
  • Git as safety net
  • Continuous validation with fast feedback
  • Incremental processing as default
  • Parallel exploration by default
  • Context management as discipline
  • Git-based everything
  • Docs define, not describe
  • Prompt versioning and testing
  • Contract evolution with migration paths
  • Cost and token budgeting

Technology (18 principles)

  • Self-modifying AI-first codebase
  • Limited and domain-specific by design
  • Separation of concerns through layered virtualization
  • Protected self-healing kernel
  • Long-running agent processes
  • Simple interfaces by design
  • Stateless by default
  • Disposable components everywhere
  • CLI-first design
  • Tool ecosystems as extensions
  • Observability baked in
  • Idempotency by design
  • Error recovery patterns built in
  • Graceful degradation by design
  • Feature flags as deployment strategy
  • Least-privilege automation with scoped permissions
  • Dependency pinning and security scanning
  • Declarative over imperative

Governance & Operations (7 principles)

  • Access control and compliance as first-class
  • Metrics and evaluation everywhere
  • Knowledge stewardship and institutional memory
  • Adaptive sandboxing with explicit approvals
  • Data governance and privacy controls
  • Model lifecycle management
  • Self-serve recovery with known-good snapshots

Documentation Structure

Creates coherent hierarchy:

AMPLIFIER_SELF_IMPROVEMENT_PHILOSOPHY.md (WHY - 44 core principles)
├─ IMPLEMENTATION_PHILOSOPHY.md (HOW - ruthless simplicity)
├─ MODULAR_DESIGN_PHILOSOPHY.md (HOW - bricks and studs)
├─ AGENTS.md (WHAT - tactical agent guidelines)
└─ DISCOVERIES.md (LEARNED - operational lessons)

Impact

This framework:

  • Ensures consistent self-improvement practices across all AI agents
  • Guides architecture decisions for a self-modifying system
  • Establishes governance and operational requirements
  • Provides strategic context for tactical implementation decisions
  • Makes Amplifier's self-improvement capability explicit and documented

Testing

  • All documentation files render correctly
  • Cross-references are accurate
  • Philosophy integrates with existing documentation structure
  • No code changes, documentation only

🤖 Generated with Claude Code

michaeljabbour and others added 8 commits September 12, 2025 04:17
@michaeljabbour
feat: Add global Amplifier access system
ca1cf68 
🌍 Enable Amplifier's powerful AI agents and tools on any codebase, anywhere

This major enhancement allows developers to harness Amplifier's 20+ specialized
agents (zen-architect, bug-hunter, security-guardian, etc.) on any project
without copying files or modifying existing repositories.

✨ New Features:
- Global 'amplifier' command for system-wide access
- Smart auto-detection of Amplifier installation location
- Enhanced startup scripts with comprehensive error handling
- Seamless integration with existing Claude workflows
- Cross-platform compatibility (macOS, Linux, WSL)

🚀 Usage:
  make install-global    # Install global command
  amplifier ~/my-project # Use Amplifier on any project
  amplifier --help       # Show usage examples

📈 Benefits:
- All 20+ specialized agents available on any codebase
- Shared knowledge base across all projects
- Same powerful automation and quality tools
- Project isolation - changes only affect target project
- No need to modify or copy files to existing projects

🔧 Implementation:
- Enhanced amplifier-anywhere.sh with robust error handling
- New bin/amplifier wrapper for global installation
- Updated Makefile with install-global targets
- Comprehensive documentation in README
- Fixed Claude settings path resolution

This democratizes access to Amplifier's AI development superpowers,
making every codebase instantly compatible with the full Amplifier toolkit.
@michaeljabbour
fix: Improve argument parsing in amplifier-anywhere.sh
2124f5b 
- Fix handling of Claude flags when no directory specified
- Ensure --version flag works correctly without triggering full startup
- Improve argument parsing logic to handle edge cases
- Maintain backward compatibility with all usage patterns

Tested scenarios:
✅ amplifier --version (shows version only)
✅ amplifier --print 'command' (uses current dir + Claude args)
✅ amplifier /path/to/project --model sonnet (explicit dir + args)
✅ amplifier /nonexistent/path (proper error handling)
✅ amplifier --help (shows help text)
@michaeljabbour
fix: Allow bin/ directory in git for global command
3090225 
- Modify .gitignore to permit bin/amplifier global command
- Maintain exclusion of other build artifacts
- Enable proper version control of global installation script
@michaeljabbour
fix: Preserve original working directory in global amplifier command
bf03e27 
- Modified bin/amplifier to capture and pass the original PWD
- Updated amplifier-anywhere.sh to use ORIGINAL_PWD when available
- Fixes issue where 'amplifier' from any directory would default to amplifier repo instead of current dir
@michaeljabbour
Merge remote-tracking branch 'upstream/main' into feature/global-ampl…
5a4c821 
…ifier-access
@michaeljabbour
Merge feature/global-amplifier-access into main
1f6734b
@michaeljabbour
Merge remote-tracking branch 'upstream/main'
446bef2
@michaeljabbour @claude
docs: add AI-first self-improvement philosophy and architecture princ…
7f5b77e 
…iples

Establishes comprehensive framework for how Amplifier improves itself through
AI-first development with 44 core principles organized into People, Process,
Technology, and Governance & Operations categories.

Key additions:
- AMPLIFIER_SELF_IMPROVEMENT_PHILOSOPHY.md: Complete 44-principle framework
- Integrated philosophy into CLAUDE.md, AGENTS.md, and README.md
- Added cross-references in IMPLEMENTATION_PHILOSOPHY.md and MODULAR_DESIGN_PHILOSOPHY.md

Principles cover:
- Regeneration-first development (vs editing)
- Contract-driven architecture with disposable components
- Self-modifying codebase with 95%+ AI-written code
- Test-based verification and git as safety net
- Self-healing kernel and adaptive sandboxing
- Knowledge stewardship and institutional memory

This framework guides all AI agents working on Amplifier's codebase to ensure
consistent self-improvement practices.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
michaeljabbour added a commit to michaeljabbour/amplifier that referenced this pull request Sep 30, 2025
@michaeljabbour @claude
feat: complete all 44 AI-first principles specifications
8ead3a7 
Complete comprehensive technical specification library with all 44 principles:

**People (6 specs)**
- #1 Small AI-first working groups
- #2 Strategic human touchpoints only
- #3 Prompt engineering as core skill
- microsoft#4 Test-based verification over code review
- microsoft#5 Conversation-driven development
- microsoft#6 Human escape hatches always available

**Process (13 specs)**
- microsoft#7 Regenerate, don't edit
- microsoft#8 Contract-first everything
- microsoft#9 Tests as the quality gate
- microsoft#10 Git as safety net
- microsoft#11 Continuous validation with fast feedback
- microsoft#12 Incremental processing as default
- microsoft#13 Parallel exploration by default
- microsoft#14 Context management as discipline
- microsoft#15 Git-based everything
- microsoft#16 Docs define, not describe
- microsoft#17 Prompt versioning and testing
- microsoft#18 Contract evolution with migration paths
- microsoft#19 Cost and token budgeting

**Technology (18 specs)**
- microsoft#20 Self-modifying AI-first codebase
- microsoft#21 Limited and domain-specific by design
- microsoft#22 Layered virtualization
- microsoft#23 Protected self-healing kernel
- microsoft#24 Long-running agent processes
- microsoft#25 Simple interfaces by design
- microsoft#26 Stateless by default
- microsoft#27 Disposable components everywhere
- microsoft#28 CLI-first design
- microsoft#29 Tool ecosystems as extensions
- microsoft#30 Observability baked in
- microsoft#31 Idempotency by design (reference)
- microsoft#32 Error recovery patterns built in
- microsoft#33 Graceful degradation by design
- microsoft#34 Feature flags as deployment strategy
- microsoft#35 Least-privilege automation
- microsoft#36 Dependency pinning and security scanning
- microsoft#37 Declarative over imperative

**Governance (7 specs)**
- microsoft#38 Access control and compliance
- microsoft#39 Metrics and evaluation everywhere
- microsoft#40 Knowledge stewardship and institutional memory
- microsoft#41 Adaptive sandboxing with explicit approvals
- microsoft#42 Data governance and privacy controls
- microsoft#43 Model lifecycle management
- microsoft#44 Self-serve recovery with known-good snapshots

Each specification includes:
- Plain-language definition
- AI-first development rationale
- 4-6 implementation approaches
- 5 good/bad example pairs with working code
- 6 related principles with relationships
- 7 common pitfalls with examples
- Tools organized by category
- 12 actionable checklist items

Statistics:
- 44 specifications totaling ~10,000+ lines
- 220+ good/bad code example pairs
- 240+ implementation approaches
- 300+ documented anti-patterns
- 500+ tools and frameworks
- 250+ cross-principle relationships

Created through parallel AI agent execution demonstrating
Principle microsoft#13 (Parallel Exploration by Default).

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
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@michaeljabbour