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aitbc/docs/ROADMAP.md
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refactor: move version to separate module and improve logging
- Created aitbc/_version.py with centralized version definition
- Updated aitbc/__init__.py to import __version__ from _version module
- Updated constants.py to use __version__ for PACKAGE_VERSION
- Replaced print() calls with logger in decorators.py, events.py, queue_manager.py, and state.py
- Added logger initialization using get_logger(__name__) in config.py, decorators.py, events.py, queue_manager.py, and state.py
- Added cli/commands
2026-05-11 20:12:01 +02:00

2.7 KiB

AITBC Development Roadmap

Current Focus: v0.1 Release Preparation

Distribution & Binaries

  • Debian stable miner binary (build workflow exists, binary built but distribution mechanism pending)
  • Binary distribution via GitHub Releases (deferred until v1 release - policy: no GitHub Releases before v1)

Quality Assurance

  • Cross-platform compatibility validation
  • Security penetration testing

Codebase Quality & Technical Debt

CRITICAL (Short-term, 0-2 weeks)

  • Replace print() statements with proper logging in aitbc/decorators.py, aitbc/events.py, aitbc/queue_manager.py, aitbc/state.py
  • Fix bare except: in config.py line 79 - add logger assignment at top of file
  • Coordinator-API service exports - either expand all 101 services to init.py or document lazy import pattern

HIGH (Medium-term, 2-6 weeks)

  • Split massive service classes (advanced_reinforcement_learning.py 2,000 lines, certification_service.py 1,368 lines, multi_modal_fusion.py 1,324 lines)
  • Consolidate CLI monolith (aitbc_cli.py 3,256 lines into existing commands/ directory structure - 19 files in aitbc_cli/commands/, 78 files in commands/)
  • Improve test coverage - currently ~6% (55 test files / 21K lines for 351K-line codebase)

MEDIUM (Long-term, 1-3 months)

  • Remove aitbc-core package (duplicates constants, logging, middleware from main repo - old version 0.3.0)

LOW (Nice to Have)

  • Consolidate scattered documentation (100+ docs files across 40+ directories - deferred due to potential link breakage)

Upcoming Improvements

All "Upcoming Improvements" items have been completed and removed from this section.


Competitive Differentiators

Advanced Privacy & Cryptography

  • zkML + FHE Integration (Q3 2026)

    • Zero-knowledge machine learning for private model inference
    • Fully homomorphic encryption for private prompts and model weights
    • Confidential AI computations without revealing sensitive data
  • Hybrid TEE/ZK Verification (Q4 2026)

    • Combine Trusted Execution Environments with zero-knowledge proofs
    • Dual-layer verification for enhanced security guarantees
    • Support for Intel SGX, AMD SEV, and ARM TrustZone

Decentralized AI Economy

  • On-Chain Model Marketplace (Q3 2026)

    • Smart contracts for AI model trading and licensing
    • Automated royalty distribution for model creators
    • Model versioning and provenance tracking on blockchain
  • Verifiable AI Agent Orchestration (Q4 2026)

    • Decentralized AI agent coordination protocols
    • Agent reputation and performance tracking
    • Cross-agent collaboration with cryptographic guarantees

This roadmap continues to evolve as we implement new features and improvements.