# DEME V3 Sprint Plan: Multi-Agent Ethics with Rank 4-6 Tensors

**Version**: 2.0
**Date**: January 2026
**Total Sprints**: 28 (2-week sprints)
**Estimated Duration**: 56 weeks

---

## Sprint Overview

| Phase | Sprints | Focus Area | Key Deliverables |
|-------|---------|------------|------------------|
| **Phase 1** | 1-3 | Foundation | MoralTensor core, V2 compatibility |
| **Phase 2** | 4-6 | Rank-2 Distributional | Per-party ethics, fairness metrics |
| **Phase 3** | 7-10 | Rank-3/4 Multi-Agent | Temporal, coalitions, Shapley |
| **Phase 4** | 11-13 | Hardware Acceleration | CUDA, Jetson Nano, TensorRT |
| **Phase 5** | 14-16 | Rank-5/6 Advanced | Uncertainty, full context |
| **Phase 6** | 17-18 | Production Hardening | Testing, docs, migration tools |
| **Phase 7** | 19-21 | Decentralized Infrastructure | DHT, E-Certs, Blockchain ledger |
| **Phase 8** | 22-24 | Enforcement & Auditing | EA, Conflict Resolution, SAIDS |
| **Phase 9** | 25-26 | TCAM & Performance | Hardware veto acceleration |
| **Phase 10** | 27-28 | Stakeholder Tooling | Drift detection, formal verification |

---

## Phase 1: Foundation (Sprints 1-3)

### Sprint 1: MoralTensor Core Data Structure

**Goal**: Implement the fundamental MoralTensor class supporting ranks 1-6

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 1.1 | Design MoralTensor dataclass with rank-aware shape validation | P0 | 8 |
| 1.2 | Implement dense tensor storage with NumPy backend | P0 | 6 |
| 1.3 | Implement sparse tensor storage (COO format) | P0 | 8 |
| 1.4 | Add dimension naming and metadata tracking | P1 | 4 |
| 1.5 | Implement `__repr__`, `__eq__`, serialization | P1 | 4 |
| 1.6 | Add veto_flags and veto_locations for tensor elements | P0 | 6 |
| 1.7 | Write comprehensive unit tests for MoralTensor | P0 | 8 |
| 1.8 | Create type stubs and documentation | P1 | 4 |

**Deliverables**:
- `src/erisml/ethics/moral_tensor.py`
- `tests/test_moral_tensor.py`
- API documentation for MoralTensor

**Dependencies**: None

**Acceptance Criteria**:
- [ ] MoralTensor supports ranks 1-6 with shape validation
- [ ] Sparse and dense representations interconvertible
- [ ] 95% test coverage on core class
- [ ] Serialization round-trip works

---

### Sprint 2: Tensor Operations Library

**Goal**: Implement core tensor operations needed for ethics computation

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 2.1 | Implement `contract()` for weighted axis reduction | P0 | 8 |
| 2.2 | Implement `slice_party()`, `slice_time()` accessors | P0 | 6 |
| 2.3 | Implement element-wise operations (`__add__`, `__mul__`, etc.) | P0 | 6 |
| 2.4 | Implement `to_vector()` collapse with strategies | P0 | 8 |
| 2.5 | Implement `promote_rank()` for dimension expansion | P1 | 6 |
| 2.6 | Implement distance metrics (Euclidean, Wasserstein) | P1 | 8 |
| 2.7 | Implement `dominates()` for Pareto comparison | P0 | 6 |
| 2.8 | Performance benchmarks for all operations | P1 | 4 |
| 2.9 | Unit tests for all operations | P0 | 8 |

**Deliverables**:
- Extended `moral_tensor.py` with operations
- `src/erisml/ethics/tensor_ops.py` (helper functions)
- `tests/test_tensor_ops.py`
- Benchmark results document

**Dependencies**: Sprint 1

**Acceptance Criteria**:
- [ ] All operations work for ranks 1-6
- [ ] Sparse operations maintain sparsity where possible
- [ ] Rank-2 contraction < 200ns (CPU)
- [ ] 90% test coverage

---

### Sprint 3: V2 Compatibility Layer

**Goal**: Ensure seamless interoperability between V2 MoralVector and V3 MoralTensor

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 3.1 | Implement `promote_v2_to_v3()` conversion function | P0 | 6 |
| 3.2 | Implement `collapse_v3_to_v2()` with multiple strategies | P0 | 8 |
| 3.3 | Update MoralVector to inherit from/wrap MoralTensor(rank=1) | P0 | 8 |
| 3.4 | Ensure MoralLandscape works with mixed Vector/Tensor inputs | P1 | 6 |
| 3.5 | Add deprecation warnings for pure V2 usage | P2 | 2 |
| 3.6 | Write V2 ↔ V3 round-trip invariance tests | P0 | 8 |
| 3.7 | Update existing V2 tests to verify V3 compatibility | P0 | 6 |
| 3.8 | Migration guide documentation | P1 | 4 |

**Deliverables**:
- `src/erisml/ethics/compat.py`
- Updated `moral_vector.py` with V3 integration
- `tests/test_v2_v3_compat.py`
- Migration guide document

**Dependencies**: Sprints 1-2

**Acceptance Criteria**:
- [ ] All existing V2 tests pass unchanged
- [ ] V2 → V3 → V2 round-trip preserves values
- [ ] No breaking API changes for V2 consumers
- [ ] Performance within 10% of V2 baseline

---

## Phase 2: Rank-2 Distributional Ethics (Sprints 4-6)

### Sprint 4: EthicalFactsV3 with Per-Party Tracking

**Goal**: Extend EthicalFacts to track impacts on individual parties

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 4.1 | Design ConsequencesV3 with per-party distributions | P0 | 6 |
| 4.2 | Design RightsAndDutiesV3 with per-party tracking | P0 | 6 |
| 4.3 | Design JusticeAndFairnessV3 with distributional metrics | P0 | 6 |
| 4.4 | Implement EthicalFactsV3 dataclass | P0 | 8 |
| 4.5 | Implement V2 → V3 facts promotion (single party default) | P0 | 4 |
| 4.6 | Implement V3 → V2 facts collapse | P1 | 4 |
| 4.7 | Update JSON schema for V3 facts | P1 | 6 |
| 4.8 | Write unit tests | P0 | 6 |
| 4.9 | Update domain interface protocols | P1 | 4 |

**Deliverables**:
- `src/erisml/ethics/facts_v3.py`
- Updated `schemas/ethical_facts_v3.json`
- `tests/test_facts_v3.py`

**Dependencies**: Sprint 3

**Acceptance Criteria**:
- [ ] EthicalFactsV3 supports 1-N parties
- [ ] V2 facts auto-promote to V3
- [ ] JSON serialization complete
- [ ] Type validation enforced

---

### Sprint 5: Distributional Fairness Metrics

**Goal**: Implement fairness and distributional justice metrics on tensors

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 5.1 | Implement Gini coefficient for harm/benefit distribution | P0 | 6 |
| 5.2 | Implement Rawlsian maximin (worst-off identification) | P0 | 6 |
| 5.3 | Implement utilitarian aggregation (sum/average) | P0 | 4 |
| 5.4 | Implement prioritarian weighting (vulnerability-adjusted) | P0 | 6 |
| 5.5 | Implement Atkinson inequality index | P1 | 6 |
| 5.6 | Implement Theil index for multi-dimension inequality | P1 | 6 |
| 5.7 | Create FairnessMetrics class aggregating all metrics | P0 | 6 |
| 5.8 | Unit tests with edge cases | P0 | 8 |
| 5.9 | Documentation with examples | P1 | 4 |

**Deliverables**:
- `src/erisml/ethics/fairness_metrics.py`
- `tests/test_fairness_metrics.py`
- Fairness metrics documentation

**Dependencies**: Sprint 4

**Acceptance Criteria**:
- [ ] All metrics implemented and tested
- [ ] Edge cases handled (empty, single party)
- [ ] Numerical stability verified
- [ ] Documentation with usage examples

---

### Sprint 6: EthicsModuleV3 and JudgementV3

**Goal**: Define V3 EM protocol and judgement format with tensor output

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 6.1 | Design EthicsModuleV3 protocol with tensor output | P0 | 6 |
| 6.2 | Design EthicalJudgementV3 dataclass | P0 | 6 |
| 6.3 | Implement BaseEthicsModuleV3 with template methods | P0 | 8 |
| 6.4 | Implement `judge_distributed()` method | P0 | 6 |
| 6.5 | Update GenevaEMV2 → GenevaEMV3 | P1 | 6 |
| 6.6 | Update CaseStudy1TriageEM → TriageEMV3 | P1 | 6 |
| 6.7 | Implement judgement V2 ↔ V3 conversion | P0 | 4 |
| 6.8 | Unit tests for V3 EMs | P0 | 8 |

**Deliverables**:
- `src/erisml/ethics/modules/base_v3.py`
- `src/erisml/ethics/judgement_v3.py`
- Updated example EMs
- `tests/test_em_v3.py`

**Dependencies**: Sprints 4-5

**Acceptance Criteria**:
- [ ] V3 protocol defined and documented
- [ ] At least 2 reference V3 EMs implemented
- [ ] V2 EMs still work via compatibility layer
- [ ] Judgement conversion round-trips correctly

---

## Phase 3: Rank-3/4 Multi-Agent Ethics (Sprints 7-10)

### Sprint 7: Temporal Tensor Support (Rank-3)

**Goal**: Enable time-evolving ethical assessment

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 7.1 | Extend MoralTensor with temporal axis support | P0 | 6 |
| 7.2 | Implement time_steps metadata and duration tracking | P0 | 4 |
| 7.3 | Implement temporal discounting operations | P0 | 6 |
| 7.4 | Implement irreversibility detection across time | P0 | 8 |
| 7.5 | Implement trajectory comparison (DTW distance) | P1 | 8 |
| 7.6 | Update EthicalFactsV3 with harm/benefit trajectories | P0 | 6 |
| 7.7 | Implement `slice_time()` and `window()` operations | P0 | 6 |
| 7.8 | Unit tests for temporal operations | P0 | 8 |

**Deliverables**:
- Extended `moral_tensor.py` with temporal support
- `src/erisml/ethics/temporal_ops.py`
- `tests/test_temporal_tensor.py`

**Dependencies**: Sprint 6

**Acceptance Criteria**:
- [ ] Rank-3 tensors work end-to-end
- [ ] Discounting configurable per-party
- [ ] Irreversibility veto triggers appropriately
- [ ] Trajectory distance metrics implemented

---

### Sprint 8: Coalition Context (Rank-4 Foundation)

**Goal**: Support multi-agent action coordination in tensors

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 8.1 | Design CoalitionContext dataclass | P0 | 6 |
| 8.2 | Extend MoralTensor with action and coalition axes | P0 | 8 |
| 8.3 | Implement coalition configuration enumeration | P0 | 6 |
| 8.4 | Implement sparse coalition representation | P0 | 8 |
| 8.5 | Add coalition stability constraints | P1 | 6 |
| 8.6 | Update EthicalFactsV3 with coalition context | P0 | 4 |
| 8.7 | Implement action-conditioned slicing | P0 | 6 |
| 8.8 | Unit tests for rank-4 tensors | P0 | 8 |

**Deliverables**:
- `src/erisml/ethics/coalition.py`
- Extended tensor support
- `tests/test_coalition_tensor.py`

**Dependencies**: Sprint 7

**Acceptance Criteria**:
- [ ] Rank-4 tensors functional
- [ ] Sparse representation efficient for large coalition spaces
- [ ] Coalition enumeration correct
- [ ] Action-conditioned operations work

---

### Sprint 9: Shapley Values and Fair Credit Assignment

**Goal**: Implement game-theoretic fair attribution for multi-agent ethics

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 9.1 | Implement exact Shapley value computation | P0 | 10 |
| 9.2 | Implement Monte Carlo Shapley approximation | P0 | 8 |
| 9.3 | Implement contribution margin per agent | P0 | 6 |
| 9.4 | Implement core stability check | P1 | 8 |
| 9.5 | Implement nucleolus computation | P2 | 8 |
| 9.6 | Add Shapley to EthicalJudgementV3 metadata | P1 | 4 |
| 9.7 | Benchmark exact vs approximate for various sizes | P1 | 4 |
| 9.8 | Unit tests with known game theory examples | P0 | 8 |

**Deliverables**:
- `src/erisml/ethics/game_theory.py`
- Shapley integration in judgements
- `tests/test_shapley.py`
- Performance analysis document

**Dependencies**: Sprint 8

**Acceptance Criteria**:
- [ ] Exact Shapley correct for n ≤ 10 agents
- [ ] Monte Carlo within 5% for n ≤ 100
- [ ] Core stability detection works
- [ ] Integration with decision proofs

---

### Sprint 10: Strategic Layer Implementation

**Goal**: Complete the Strategic layer of the three-layer pipeline

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 10.1 | Design StrategicLayer interface | P0 | 6 |
| 10.2 | Implement coalition stability analysis | P0 | 8 |
| 10.3 | Implement Nash equilibrium detection | P1 | 10 |
| 10.4 | Implement policy recommendation generation | P1 | 8 |
| 10.5 | Integrate strategic layer into DEMEPipeline | P0 | 6 |
| 10.6 | Add strategic layer to decision proofs | P0 | 6 |
| 10.7 | End-to-end integration tests | P0 | 8 |
| 10.8 | Documentation and examples | P1 | 4 |

**Deliverables**:
- `src/erisml/ethics/layers/strategic.py` (completed)
- Updated `pipeline.py`
- `tests/test_strategic_layer.py`
- Multi-agent example scenario

**Dependencies**: Sprint 9

**Acceptance Criteria**:
- [ ] Strategic layer functional
- [ ] Pipeline executes all three layers
- [ ] Decision proofs include strategic analysis
- [ ] Example demonstrates full multi-agent decision

---

## Phase 4: Hardware Acceleration (Sprints 11-13)

### Sprint 11: Acceleration Framework and CPU Optimization

**Goal**: Build acceleration abstraction layer with optimized CPU backend

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 11.1 | Design AccelerationBackend abstract interface | P0 | 6 |
| 11.2 | Implement CPUBackend with NumPy/SciPy | P0 | 8 |
| 11.3 | Implement SIMD-optimized tensor operations | P1 | 10 |
| 11.4 | Implement sparse tensor optimization (SciPy) | P0 | 8 |
| 11.5 | Create AccelerationDispatcher for backend selection | P0 | 6 |
| 11.6 | Add device hints to MoralTensor | P1 | 4 |
| 11.7 | Benchmark suite for acceleration backends | P0 | 6 |
| 11.8 | Unit tests for dispatcher and CPU backend | P0 | 6 |

**Deliverables**:
- `src/erisml/ethics/acceleration/__init__.py`
- `src/erisml/ethics/acceleration/backend.py`
- `src/erisml/ethics/acceleration/cpu.py`
- `tests/test_acceleration.py`
- Benchmark results

**Dependencies**: Sprint 10

**Acceptance Criteria**:
- [ ] Backend abstraction clean and extensible
- [ ] CPU backend ≥ baseline NumPy performance
- [ ] Sparse operations 10x faster for sparse tensors
- [ ] Dispatcher correctly selects backend

---

### Sprint 12: CUDA Backend

**Goal**: Implement GPU acceleration for tensor operations

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 12.1 | Implement CUDABackend using CuPy | P0 | 10 |
| 12.2 | Implement GPU memory management | P0 | 8 |
| 12.3 | Implement async data transfer (pinned memory) | P1 | 6 |
| 12.4 | Optimize contraction kernels | P1 | 8 |
| 12.5 | Implement batched operations | P0 | 6 |
| 12.6 | Add CUDA stream support for pipelining | P2 | 6 |
| 12.7 | Benchmark CPU vs CUDA across tensor sizes | P0 | 4 |
| 12.8 | Fallback handling when CUDA unavailable | P0 | 4 |
| 12.9 | Unit tests (requires CUDA hardware) | P0 | 6 |

**Deliverables**:
- `src/erisml/ethics/acceleration/cuda.py`
- Updated dispatcher with CUDA support
- `tests/test_cuda_backend.py`
- CUDA vs CPU benchmark report

**Dependencies**: Sprint 11

**Acceptance Criteria**:
- [ ] CUDA backend functional on NVIDIA GPUs
- [ ] 10x+ speedup for rank-4+ tensors
- [ ] Graceful fallback on non-CUDA systems
- [ ] Memory usage reasonable

---

### Sprint 13: Jetson Nano Integration

**Goal**: Enable edge deployment on NVIDIA Jetson Nano with optimizations

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 13.1 | Implement JetsonBackend with device detection | P0 | 8 |
| 13.2 | Implement TensorRT optimization for tensor ops | P0 | 12 |
| 13.3 | Implement DLA support for Orin devices | P1 | 8 |
| 13.4 | Add power mode configuration | P1 | 4 |
| 13.5 | Implement unified memory optimization | P0 | 6 |
| 13.6 | Create pre-compiled TensorRT engine caching | P1 | 6 |
| 13.7 | Implement EPU placeholder for future devices | P2 | 4 |
| 13.8 | Benchmark on Jetson Nano 4GB | P0 | 6 |
| 13.9 | Benchmark on Jetson Orin (if available) | P1 | 4 |
| 13.10 | Integration tests on Jetson hardware | P0 | 6 |

**Deliverables**:
- `src/erisml/ethics/acceleration/jetson.py`
- `src/erisml/ethics/acceleration/tensorrt_utils.py`
- JetsonConfig dataclass
- Jetson deployment guide
- Benchmark results

**Dependencies**: Sprint 12

**Acceptance Criteria**:
- [ ] Jetson Nano 4GB fully supported
- [ ] TensorRT provides 3x+ speedup over CPU
- [ ] DLA works on Orin (if hardware available)
- [ ] Power modes configurable
- [ ] Engine caching reduces startup time

---

## Phase 5: Rank-5/6 Advanced Features (Sprints 14-16)

### Sprint 14: Uncertainty Quantification (Rank-5)

**Goal**: Enable Monte Carlo uncertainty propagation in ethics

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 14.1 | Extend MoralTensor with sample axis | P0 | 6 |
| 14.2 | Implement sample generation from distributions | P0 | 8 |
| 14.3 | Implement expected value and variance computation | P0 | 6 |
| 14.4 | Implement Conditional Value at Risk (CVaR) | P0 | 8 |
| 14.5 | Implement worst-case (robust) aggregation | P0 | 6 |
| 14.6 | Implement confidence interval computation | P1 | 6 |
| 14.7 | Update EthicalFactsV3 with uncertainty bounds | P0 | 6 |
| 14.8 | Unit tests for uncertainty propagation | P0 | 8 |

**Deliverables**:
- `src/erisml/ethics/uncertainty.py`
- Extended tensor support
- `tests/test_uncertainty.py`

**Dependencies**: Sprint 13

**Acceptance Criteria**:
- [ ] Rank-5 tensors functional
- [ ] Monte Carlo sampling efficient
- [ ] CVaR and robust methods implemented
- [ ] Confidence intervals correct

---

### Sprint 15: Full Context Tensors (Rank-6)

**Goal**: Support complete ethical state space representation

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 15.1 | Implement rank-6 tensor support | P0 | 8 |
| 15.2 | Implement Tucker decomposition for compression | P0 | 10 |
| 15.3 | Implement Tensor Train decomposition | P1 | 10 |
| 15.4 | Implement hierarchical sparse storage | P0 | 8 |
| 15.5 | Optimize memory layout for access patterns | P1 | 6 |
| 15.6 | Benchmark rank-6 operations | P0 | 6 |
| 15.7 | Integration with acceleration backends | P0 | 6 |
| 15.8 | Unit tests for rank-6 tensors | P0 | 8 |

**Deliverables**:
- Full rank-6 tensor support
- `src/erisml/ethics/tensor_decomposition.py`
- `tests/test_rank6_tensor.py`
- Memory optimization guide

**Dependencies**: Sprint 14

**Acceptance Criteria**:
- [ ] Rank-6 tensors work end-to-end
- [ ] Decomposition reduces memory >10x
- [ ] Operations on decomposed tensors efficient
- [ ] All acceleration backends support rank-6

---

### Sprint 16: Advanced Decision Proofs

**Goal**: Extend audit trail for full tensor and multi-agent scenarios

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 16.1 | Extend DecisionProof for tensor hashing | P0 | 6 |
| 16.2 | Implement coalition stability certificates | P0 | 8 |
| 16.3 | Implement Shapley value audit records | P0 | 6 |
| 16.4 | Implement distributional fairness attestations | P0 | 6 |
| 16.5 | Implement temporal trajectory proofs | P1 | 6 |
| 16.6 | Implement uncertainty bound certificates | P1 | 6 |
| 16.7 | Update MCP server for V3 proofs | P1 | 6 |
| 16.8 | Unit tests for extended proofs | P0 | 8 |
| 16.9 | Documentation | P1 | 4 |

**Deliverables**:
- Updated `decision_proof.py` → `decision_proof_v3.py`
- Coalition certificates
- Fairness attestations
- `tests/test_decision_proof_v3.py`

**Dependencies**: Sprint 15

**Acceptance Criteria**:
- [ ] All V3 features auditable
- [ ] Proof verification works
- [ ] MCP server exposes V3 proofs
- [ ] Documentation complete

---

## Phase 6: Production Hardening (Sprints 17-18)

### Sprint 17: Comprehensive Testing and Bond Index

**Goal**: Achieve production-quality test coverage and representational coherence

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 17.1 | Extend Bond Index tests for tensor transforms | P0 | 10 |
| 17.2 | Add multi-agent invariance transforms | P0 | 8 |
| 17.3 | Full integration test suite | P0 | 10 |
| 17.4 | Hardware matrix testing (CPU/CUDA/Jetson) | P0 | 8 |
| 17.5 | Performance regression test suite | P0 | 6 |
| 17.6 | Fuzz testing for edge cases | P1 | 8 |
| 17.7 | Security audit of tensor operations | P1 | 6 |
| 17.8 | Coverage report and gap analysis | P0 | 4 |

**Deliverables**:
- Extended Bond Index tests
- Full integration test suite
- Hardware test matrix
- Coverage report (target: 90%+)

**Dependencies**: Sprint 16

**Acceptance Criteria**:
- [ ] 90%+ code coverage
- [ ] Bond Index < 0.1 for all V3 EMs
- [ ] All hardware backends tested
- [ ] No critical security issues

---

### Sprint 18: Documentation and Migration Tools

**Goal**: Enable production adoption with complete documentation and tooling

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 18.1 | Complete API documentation | P0 | 10 |
| 18.2 | Write V2 → V3 migration guide | P0 | 8 |
| 18.3 | Create migration CLI tool | P1 | 8 |
| 18.4 | Update README for V3 | P0 | 4 |
| 18.5 | Create V3 tutorial notebooks | P1 | 8 |
| 18.6 | Update JSON schemas to V05 | P0 | 4 |
| 18.7 | Release notes and changelog | P0 | 4 |
| 18.8 | Jetson deployment guide | P1 | 6 |
| 18.9 | Final review and cleanup | P0 | 8 |

**Deliverables**:
- Complete API documentation
- Migration guide
- `deme-migrate` CLI tool
- Updated README
- Tutorial notebooks
- V05 schemas
- Release notes

**Dependencies**: Sprint 17

**Acceptance Criteria**:
- [ ] All public APIs documented
- [ ] Migration guide tested on real projects
- [ ] CLI tool functional
- [ ] Tutorials work end-to-end
- [ ] Ready for release

---

## Phase 7: Decentralized Infrastructure (Sprints 19-21)

### Sprint 19: DHT Integration and Shadow Copies

**Goal**: Implement decentralized Ethics Module distribution

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 19.1 | Design DHT node architecture (Kademlia-based) | P0 | 10 |
| 19.2 | Implement KademliaNode class for EM indexing | P0 | 12 |
| 19.3 | Implement ShadowCopyManager for local EM caching | P0 | 8 |
| 19.4 | Design EM Service API for DHT queries | P0 | 6 |
| 19.5 | Implement offline capability with shadow copies | P1 | 8 |
| 19.6 | Add DHT health monitoring and replication | P1 | 6 |
| 19.7 | Unit tests for DHT operations | P0 | 8 |
| 19.8 | Integration tests for shadow copy sync | P0 | 6 |

**Deliverables**:
- `src/erisml/ethics/distribution/dht.py`
- `src/erisml/ethics/distribution/shadow_cache.py`
- `src/erisml/ethics/distribution/em_service.py`
- `tests/test_dht_distribution.py`

**Dependencies**: Sprint 18

**Acceptance Criteria**:
- [ ] DHT node joins and leaves network correctly
- [ ] Shadow copies sync with cryptographic verification
- [ ] EM retrieval works offline from cache
- [ ] API returns last verified EM version

---

### Sprint 20: E-Cert Schema and Governance CA

**Goal**: Establish cryptographic trust infrastructure

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 20.1 | Design ECertificate dataclass schema | P0 | 6 |
| 20.2 | Implement Governance CA key management | P0 | 10 |
| 20.3 | Implement E-Cert signing and verification | P0 | 8 |
| 20.4 | Design Certificate Revocation List (CRL) system | P0 | 8 |
| 20.5 | Implement secure EM loading protocol | P0 | 10 |
| 20.6 | Add Policy OID registry | P1 | 6 |
| 20.7 | Unit tests for cryptographic operations | P0 | 8 |
| 20.8 | Security audit of CA implementation | P0 | 8 |

**Deliverables**:
- `src/erisml/ethics/security/e_cert.py`
- `src/erisml/ethics/security/governance_ca.py`
- `src/erisml/ethics/security/secure_loader.py`
- `tests/test_e_cert.py`

**Dependencies**: Sprint 19

**Acceptance Criteria**:
- [ ] E-Certs sign and verify correctly
- [ ] CRL checks block revoked certificates
- [ ] Secure loading sequence enforced
- [ ] No security vulnerabilities in audit

---

### Sprint 21: Blockchain Ledger and Trustless Execution

**Goal**: Implement immutable audit trail and sandboxed execution

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 21.1 | Design blockchain ledger interface | P0 | 8 |
| 21.2 | Implement Stakeholder Consensus Event recording | P0 | 10 |
| 21.3 | Integrate with external blockchain (Ethereum/Polygon) | P1 | 12 |
| 21.4 | Research and select sandbox technology (WASM/SGX) | P0 | 8 |
| 21.5 | Implement sandboxed EM execution environment | P0 | 12 |
| 21.6 | Design trusted data oracle for EthicalFacts | P1 | 8 |
| 21.7 | Integration tests for full trust chain | P0 | 8 |
| 21.8 | Documentation for trust architecture | P1 | 4 |

**Deliverables**:
- `src/erisml/ethics/security/blockchain_ledger.py`
- `src/erisml/ethics/security/sandbox.py`
- `src/erisml/ethics/security/data_oracle.py`
- `tests/test_blockchain_integration.py`

**Dependencies**: Sprint 20

**Acceptance Criteria**:
- [ ] EM approvals recorded on blockchain
- [ ] Sandbox isolates untrusted EM code
- [ ] Oracle validates off-chain EthicalFacts
- [ ] Full trust chain verifiable end-to-end

---

## Phase 8: Enforcement & Auditing (Sprints 22-24)

### Sprint 22: Ethics Enforcement Agent

**Goal**: Implement dedicated agent for compliance monitoring

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 22.1 | Design EthicsEnforcementAgent architecture | P0 | 8 |
| 22.2 | Implement action monitoring against DecisionOutcome | P0 | 10 |
| 22.3 | Define InterventionType enum and protocols | P0 | 6 |
| 22.4 | Implement LOG, PAUSE, THROTTLE interventions | P0 | 10 |
| 22.5 | Implement action queue OVERRIDE | P1 | 8 |
| 22.6 | Add real-time audit trail integration | P0 | 8 |
| 22.7 | Unit tests for enforcement logic | P0 | 8 |
| 22.8 | Integration tests with governed agents | P0 | 8 |

**Deliverables**:
- `src/erisml/ethics/enforcement/agent.py`
- `src/erisml/ethics/enforcement/intervention.py`
- `src/erisml/ethics/enforcement/audit_integration.py`
- `tests/test_enforcement_agent.py`

**Dependencies**: Sprint 21

**Acceptance Criteria**:
- [ ] EA detects action divergence from expected outcome
- [ ] All intervention types functional
- [ ] Every action cryptographically signed in audit
- [ ] No false positives in compliance checks

---

### Sprint 23: Conflict Resolution and Metrics

**Goal**: Multi-agent conflict mediation and compliance dashboard

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 23.1 | Design ConflictResolutionModule | P0 | 8 |
| 23.2 | Implement conflict detection between agents | P0 | 10 |
| 23.3 | Implement mediation strategies (utilitarian, Rawlsian) | P0 | 10 |
| 23.4 | Design MetricsReportingAgent | P1 | 6 |
| 23.5 | Implement compliance rate tracking | P1 | 6 |
| 23.6 | Implement Hard Veto frequency metrics | P1 | 4 |
| 23.7 | Implement Epistemic Penalty averages | P1 | 4 |
| 23.8 | Build metrics dashboard API | P1 | 8 |
| 23.9 | Unit tests for conflict resolution | P0 | 8 |

**Deliverables**:
- `src/erisml/ethics/enforcement/conflict_resolution.py`
- `src/erisml/ethics/enforcement/metrics.py`
- `src/erisml/ethics/enforcement/dashboard.py`
- `tests/test_conflict_resolution.py`

**Dependencies**: Sprint 22

**Acceptance Criteria**:
- [ ] Conflicts between agents detected and mediated
- [ ] Metrics aggregated correctly
- [ ] Dashboard API returns accurate statistics
- [ ] Profile effectiveness trackable over time

---

### Sprint 24: SAIDS Agent and Internal Affairs

**Goal**: Self-auditing system to protect governance layer

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 24.1 | Design SAIDSAgent architecture | P0 | 8 |
| 24.2 | Implement Reward Firewall isolation | P0 | 10 |
| 24.3 | Implement behavioral drift detection model | P0 | 12 |
| 24.4 | Research and implement ZKP verification | P1 | 14 |
| 24.5 | Design Quarantine Protocol | P0 | 8 |
| 24.6 | Implement immediate EA isolation mechanism | P0 | 8 |
| 24.7 | Add Human-in-the-Loop notification | P1 | 6 |
| 24.8 | Security tests for SAIDS | P0 | 10 |

**Deliverables**:
- `src/erisml/ethics/enforcement/saids.py`
- `src/erisml/ethics/enforcement/reward_firewall.py`
- `src/erisml/ethics/enforcement/zkp_verifier.py`
- `tests/test_saids.py`

**Dependencies**: Sprint 23

**Acceptance Criteria**:
- [ ] SAIDS monitors EA independently
- [ ] Reward manipulation attempts blocked
- [ ] Behavioral anomalies detected statistically
- [ ] Quarantine isolates compromised EA immediately

---

## Phase 9: TCAM & Performance (Sprints 25-26)

### Sprint 25: TCAM Integration

**Goal**: Hardware-accelerated veto checking

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 25.1 | Research TCAM hardware options | P0 | 8 |
| 25.2 | Design TCAM ACL format for Hard Veto rules | P0 | 10 |
| 25.3 | Implement TCAM rule translator | P0 | 12 |
| 25.4 | Design hybrid pipeline (TCAM → Software) | P0 | 10 |
| 25.5 | Implement TCAM veto check integration | P0 | 10 |
| 25.6 | Add TCAM rule management tooling | P1 | 8 |
| 25.7 | Unit tests for rule translation | P0 | 6 |
| 25.8 | Integration tests for hybrid pipeline | P0 | 8 |

**Deliverables**:
- `src/erisml/ethics/acceleration/tcam.py`
- `src/erisml/ethics/acceleration/tcam_translator.py`
- `src/erisml/ethics/acceleration/hybrid_pipeline.py`
- `tests/test_tcam.py`

**Dependencies**: Sprint 24

**Acceptance Criteria**:
- [ ] TCAM rules translate from software config
- [ ] Hybrid pipeline checks TCAM before software
- [ ] Nanosecond-level veto checks achieved
- [ ] Rule management tooling functional

---

### Sprint 26: Performance Benchmarking and Optimization

**Goal**: Comprehensive performance validation

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 26.1 | Benchmark TCAM vs software veto latency | P0 | 8 |
| 26.2 | Benchmark power consumption comparison | P0 | 6 |
| 26.3 | Profile high-frequency decision scenarios | P0 | 8 |
| 26.4 | Optimize critical paths identified | P0 | 12 |
| 26.5 | Document performance characteristics | P0 | 6 |
| 26.6 | Create performance regression tests | P0 | 8 |
| 26.7 | Validate all latency targets met | P0 | 6 |
| 26.8 | Performance tuning guide | P1 | 6 |

**Deliverables**:
- Performance benchmark report
- Optimized critical paths
- Performance regression test suite
- Performance tuning guide

**Dependencies**: Sprint 25

**Acceptance Criteria**:
- [ ] TCAM veto < 100ns achieved
- [ ] Power consumption documented
- [ ] All V3 latency targets met
- [ ] Performance regression tests pass

---

## Phase 10: Stakeholder Tooling (Sprints 27-28)

### Sprint 27: Governance Drift Detection

**Goal**: Tools to detect unintended ethical preference shifts

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 27.1 | Design GovernanceDriftDetector | P0 | 8 |
| 27.2 | Implement baseline decision snapshot | P0 | 6 |
| 27.3 | Implement preference ranking comparison | P0 | 10 |
| 27.4 | Add statistical significance testing | P1 | 8 |
| 27.5 | Implement drift alerting system | P1 | 6 |
| 27.6 | Design FormalVerifier architecture | P0 | 8 |
| 27.7 | Implement ethical invariant specification | P0 | 8 |
| 27.8 | Unit tests for drift detection | P0 | 8 |

**Deliverables**:
- `src/erisml/ethics/tooling/drift_detector.py`
- `src/erisml/ethics/tooling/formal_verifier.py`
- `tests/test_drift_detector.py`

**Dependencies**: Sprint 26

**Acceptance Criteria**:
- [ ] Drift detected when preferences shift
- [ ] False positive rate < 5%
- [ ] Invariants specifiable in DSL
- [ ] Alerts generated on significant drift

---

### Sprint 28: Profile-as-Code and Final Integration

**Goal**: Declarative profile management and V3 completion

**Tasks**:

| ID | Task | Priority | Est. Hours |
|----|------|----------|------------|
| 28.1 | Enhance Ethical Dialogue CLI for Profile-as-Code | P0 | 10 |
| 28.2 | Implement declarative profile YAML/JSON format | P0 | 8 |
| 28.3 | Add version control integration | P1 | 6 |
| 28.4 | Implement profile diff and merge | P1 | 8 |
| 28.5 | Full V3 integration test suite | P0 | 12 |
| 28.6 | Update all documentation for V3 | P0 | 8 |
| 28.7 | Create V3 migration CLI tool | P0 | 8 |
| 28.8 | Final release preparation | P0 | 8 |

**Deliverables**:
- Enhanced Ethical Dialogue CLI
- Profile-as-Code specification
- V3 migration tool
- Complete V3 documentation
- Release package

**Dependencies**: Sprint 27

**Acceptance Criteria**:
- [ ] Profiles manageable via version control
- [ ] CLI supports full Profile-as-Code workflow
- [ ] All V3 features documented
- [ ] Migration tool validates V2 → V3 upgrade
- [ ] V3 ready for production release

---

## Resource Requirements

### Team Composition

| Role | Count | Sprints | Focus |
|------|-------|---------|-------|
| Senior Engineer | 2 | 1-28 | Core tensor, architecture |
| ML Engineer | 1 | 11-16, 25-26 | Acceleration, TensorRT, TCAM |
| Security Engineer | 1 | 19-24 | Cryptography, CA, SAIDS |
| Distributed Systems Engineer | 1 | 19-21 | DHT, Blockchain |
| Test Engineer | 1 | 1-28 | Testing, Bond Index |
| Technical Writer | 0.5 | 17-18, 27-28 | Documentation |

### Hardware Requirements

| Hardware | Quantity | Purpose | When Needed |
|----------|----------|---------|-------------|
| Development workstations | 3 | Development | Sprint 1+ |
| NVIDIA GPU (RTX 3080+) | 2 | CUDA development | Sprint 12+ |
| Jetson Nano 4GB | 2 | Edge testing | Sprint 13+ |
| Jetson Orin (optional) | 1 | DLA testing | Sprint 13+ |
| CI/CD GPU runners | 1 | Automated testing | Sprint 12+ |

### Software Dependencies

| Dependency | Version | Purpose |
|------------|---------|---------|
| Python | 3.10+ | Runtime |
| NumPy | 1.24+ | Tensor operations |
| SciPy | 1.10+ | Sparse tensors |
| CuPy | 12.0+ | CUDA backend |
| TensorRT | 8.6+ | Jetson optimization |
| JetPack | 5.1+ | Jetson SDK |

---

## Risk Mitigation

### Technical Risks

| Risk | Mitigation | Contingency |
|------|------------|-------------|
| Rank-6 memory explosion | Low-rank decomposition | Limit to rank-4 |
| Shapley complexity | Monte Carlo approximation | Limit agents to 20 |
| TensorRT compatibility | Version pinning | CPU fallback |
| Jetson SDK changes | JetPack version lock | Document workarounds |

### Schedule Risks

| Risk | Mitigation | Contingency |
|------|------------|-------------|
| Coalition algorithms complex | Start with 2-agent | Defer to V3.1 |
| Hardware unavailable | Cloud Jetson instances | Skip Orin testing |
| Dependencies delayed | Parallel development paths | Adjust scope |

---

## Success Metrics

### Sprint-Level Metrics

- Sprint velocity: 40-50 story points per sprint
- Bug escape rate: < 5%
- Code review turnaround: < 24 hours

### Release Metrics

- Test coverage: > 90%
- Bond Index: < 0.1 for all EMs
- Performance targets met: 100%
- Documentation complete: 100%
- Zero critical bugs

### Post-Release Metrics

- Migration success rate: > 95%
- Performance improvement: > 3x on GPU
- User satisfaction: > 4.0/5.0

---

## Appendix: Sprint Calendar

| Sprint | Start Date | End Date | Phase |
|--------|------------|----------|-------|
| 1 | Week 1 | Week 2 | Foundation |
| 2 | Week 3 | Week 4 | Foundation |
| 3 | Week 5 | Week 6 | Foundation |
| 4 | Week 7 | Week 8 | Distributional |
| 5 | Week 9 | Week 10 | Distributional |
| 6 | Week 11 | Week 12 | Distributional |
| 7 | Week 13 | Week 14 | Multi-Agent |
| 8 | Week 15 | Week 16 | Multi-Agent |
| 9 | Week 17 | Week 18 | Multi-Agent |
| 10 | Week 19 | Week 20 | Multi-Agent |
| 11 | Week 21 | Week 22 | Acceleration |
| 12 | Week 23 | Week 24 | Acceleration |
| 13 | Week 25 | Week 26 | Acceleration |
| 14 | Week 27 | Week 28 | Advanced |
| 15 | Week 29 | Week 30 | Advanced |
| 16 | Week 31 | Week 32 | Advanced |
| 17 | Week 33 | Week 34 | Hardening |
| 18 | Week 35 | Week 36 | Hardening |
| 19 | Week 37 | Week 38 | Decentralized Infra |
| 20 | Week 39 | Week 40 | Decentralized Infra |
| 21 | Week 41 | Week 42 | Decentralized Infra |
| 22 | Week 43 | Week 44 | Enforcement |
| 23 | Week 45 | Week 46 | Enforcement |
| 24 | Week 47 | Week 48 | Enforcement |
| 25 | Week 49 | Week 50 | TCAM & Performance |
| 26 | Week 51 | Week 52 | TCAM & Performance |
| 27 | Week 53 | Week 54 | Stakeholder Tooling |
| 28 | Week 55 | Week 56 | Stakeholder Tooling |

---

*Sprint plan maintained by the ErisML Core Team*
