@@ -41,8 +41,6 @@ weeks or months earlier than traditional approaches.
4141> ⚠️ ** Note** : The use of AI agents does ** not eliminate the need for human review** . Human oversight remains essential
4242> to ensure correctness, context awareness, ethical compliance, and alignment with business goals.
4343
44- ---
45-
4644## 📊 Measurable Impact from Real-World Pilots
4745
4846HVE pilots have demonstrated:
@@ -54,8 +52,6 @@ HVE pilots have demonstrated:
5452
5553These results reflect the power of combining AI tooling, engineering fundamentals, and structured planning.
5654
57- ---
58-
5955## 🧪 Testing Framework for HVE
6056
6157A proposed testing framework for HVE includes:
@@ -67,8 +63,6 @@ A proposed testing framework for HVE includes:
6763
6864This ensures HVE-generated content meets enterprise standards without manual bottlenecks.
6965
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71-
7266## 🔐 Security in HVE Workflows
7367
7468Security guidance for HVE includes:
@@ -78,8 +72,6 @@ Security guidance for HVE includes:
7872- Preferring secure infrastructure and prompt engineering best practices
7973- Aligning with policy-as-code and secure defaults from day one
8074
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8375## 📈 HVE in Data Science
8476
8577HVE principles are being applied to machine learning workflows, enabling:
@@ -88,8 +80,6 @@ HVE principles are being applied to machine learning workflows, enabling:
8880- Integration of CRISP-DM and hypothesis-driven development
8981- Use of LLMs as coding agents for iterative feedback and rapid prototyping
9082
91- ---
92-
9383## 🧰 Implementation Checklist
9484
9585| Practice | Description |
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