Expand README with AILint overview and features

Added detailed information about AILint, its purpose, approach, components, and roadmap.

README.md

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 # AILint
-AI lint set of extensions
+
+**Code provenance tracking for the AI era**
+
+AILint is an open-source toolkit that brings transparency to AI-assisted development through automated detection and standardized marking of AI-generated content in your codebase.
+
+## The Problem
+
+We're building the highways of AI-assisted development without laying the pipes underneath. As AI coding assistants become ubiquitous:
+
+- **Model collapse looms**: AI systems increasingly train on AI-generated code, creating degradation loops
+- **Attribution is lost**: No way to trace which code came from humans vs. AI vs. which AI
+- **Debugging becomes harder**: Understanding provenance matters when investigating bugs or security issues
+- **Compliance is unclear**: Regulations are coming, but we have no infrastructure for them
+
+Like Ireland's motorway system that had to be re-trenched for fiber optic cables, retrofitting AI transparency will cost far more than building it in from the start.
+
+## Our Approach
+
+AILint tackles this from two angles:
+
+### 1. Forensic Detection
+Since developers may hide or forget AI assistance, AILint analyzes commits for AI influence indicators:
+- Behavioral patterns (typing speed, paste events, commit timing)
+- Code fingerprints (structure, naming, documentation patterns)
+- Metadata correlation (tool telemetry when available)
+
+Results are classified as "potentially AI influenced" with confidence scores - non-accusatory, auditable, forward-compatible.
+
+### 2. Standardized Markers
+For those who want explicit marking, AILint implements embedded markers using:
+- Unicode steganography (zero-width characters in text/code)
+- Comment annotations in source files
+- Git metadata and commit attributes
+
+These markers encode: model type, version, timestamp, confidence - while remaining invisible to humans and non-breaking for existing tools.
+
+## Components
+
+### Extensions
+- **VS Code Extension**: Real-time analysis during development
+- **Visual Studio Extension**: Integration for .NET developers
+- **Git Hooks**: Pre-commit analysis and metadata injection
+- **Azure DevOps Plugin**: Branch policies and PR integration
+- **GitHub Action**: Automated provenance checking in CI/CD
+
+### Analysis Engine
+- Local processing (privacy-first, no code leaves your machine)
+- Pluggable heuristics for different AI patterns
+- Machine learning on aggregated anonymized patterns
+- Configurable thresholds for your risk tolerance
+
+### Reporting
+- Developer dashboard showing AI influence trends
+- Compliance report generation
+- Code review prioritization based on AI likelihood
+- Historical analysis for debugging
+
+## Why Open Source?
+
+This problem requires **coordination**, not competition. We're open sourcing AILint because:
+
+1. **Standards need adoption**: One company's internal tool doesn't create an industry standard
+2. **Network effects**: More users = better detection algorithms
+3. **Trust matters**: Transparency tools must themselves be transparent
+4. **Time is short**: The window to "lay the pipes" is closing
+
+## Getting Started
+```bash
+# Install VS Code extension (coming soon)
+code --install-extension evosoft.ailint
+
+# Or use Git hooks directly
+git clone https://github.com/evosoftie/AILint
+cd AILint
+./install-hooks.sh
+```
+
+**Status**: Early development. We're building the MVP for VS Code + Git integration first.
+
+## Roadmap
+
+### Phase 1 (Current)
+- [x] Core detection heuristics
+- [ ] VS Code extension (basic)
+- [ ] Git pre-commit hook
+- [ ] JSON output format
+- [ ] Documentation
+
+### Phase 2
+- [ ] Pattern library for known AI signatures
+- [ ] Dashboard visualization
+- [ ] Azure DevOps integration
+- [ ] GitHub Action
+- [ ] Configurable policies
+
+### Phase 3
+- [ ] Machine learning on accumulated patterns
+- [ ] Visual Studio extension
+- [ ] JetBrains plugin support
+- [ ] API for custom integrations
+- [ ] Compliance templates (SOC2, ISO, etc.)
+
+## Privacy Guarantees
+
+AILint is built privacy-first:
+
+- ✅ All analysis happens **locally** on your machine
+- ✅ No code content is sent anywhere
+- ✅ Only anonymized patterns shared (opt-in for ML improvement)
+- ✅ Clear data retention policies
+- ✅ Opt-out for personal projects
+
+This is a **transparency tool**, not a surveillance system.
+
+## Contributing
+
+We need help across:
+- **Detection algorithms**: New heuristics for identifying AI patterns
+- **IDE integrations**: Extending beyond VS Code
+- **Documentation**: Clear guides for setup and calibration
+- **Testing**: Real-world validation and false positive reduction
+- **Standards**: Help define the metadata format
+
+See [CONTRIBUTING.md](CONTRIBUTING.md) for details.
+
+## Philosophy
+
+We believe:
+- **Transparency > Prohibition**: AI assistance isn't inherently bad, but opacity is dangerous
+- **Standards > Surveillance**: Industry coordination beats individual monitoring
+- **Prevention > Cure**: Building infrastructure now is cheaper than retrofitting later
+- **Collaboration > Competition**: This problem requires collective action
+
+## License
+
+MIT License - we want maximum adoption and ecosystem growth.
+
+## Supported By
+
+Evo-Soft is implementing standardization techniques to improve AI integrity across text, code, and imaging. AILint is our contribution to preventing model collapse and maintaining code provenance in the AI era.
+
+---
+
+**"We're not in the Stone Age because we ran out of stones. We're in the AI Stone Age because we haven't yet built the Bronze."**
+
+Let's build it together.