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Technical Writings & Research

Architectural & Analytics Writings

Reflections, empirical benchmarks, and system design takeaways from building data pipelines, valuation engines, and machine learning architectures.

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12 min read

Scripts, Services, and Agents: What Six Months in QA Pre-Sales Taught Me About Unbundling Testing

A pre-sales engineer's field notes on how agentic AI is splitting enterprise QA into managed services and embeddable tools — and what the research says about where full autonomy still breaks.

From discovery calls with US engineering leaders to the empirical failure modes of autonomous repair loops, here is why enterprise testing is bifurcating into black-box SLAs and CI/CD-native agentic tools.

Agentic AISoftware TestingQAEnterprise SoftwareAI Architecture
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8 min read

RAG vs. Long Context: The Architecture Debate Every AI Builder Faces

What I learned building retrieval pipelines during my MBA in Data Science & Finance, and what the 2026 research actually says

Every large language model carries an expiration date baked into it. Should you build complex retrieval pipelines (RAG) or simply dump millions of tokens into massive context windows? Here's what the empirical research actually says about costs, 'Lost in the Middle', and adaptive routers.

AILLMsRAGMachine LearningData Science
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