Insights
Concise technical notes for production-oriented AI.
Short notes on architecture, quality, and operational decisions across RAG, AI agents, computer vision, and MLOps.
All articles
All articles

Build or Buy AI: An Operating-Model Decision
The decision is not a feature comparison. Who owns the data, who can change the behaviour, and what exit costs.
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AI Readiness: Five Conditions That Decide the Outcome
Readiness is not a maturity score but five concrete conditions that either hold or do not, and how to test each honestly.
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AI Integration Is Architecture, Not an API Call
Identity, permissions, the data path, invocation pattern, failure behaviour and observability - the endpoint call is the smallest part.
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Seven Questions to Answer Before an AI Project
Which decision it improves, whether the data is reachable, where it must connect, where a human decides, and who owns it after launch.
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Engineering Reliable Backends for Agentic AI Systems
Designing reliable agent workflows with asynchronous jobs, durable state, idempotency, validation, memory, and distributed tracing.
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Silent Failures: Why Production RAG Systems Degrade Without Throwing Errors
Making hallucination amplification, ranking drift, stale context, and retrieval gaps visible through semantic observability.
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Evaluating RAG: From Golden Datasets to LLM-as-Judge
Metrics that separate retrieval and generation quality, living golden datasets, and dependable release gates.
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Beyond Vector Search: Knowledge Graphs, Structured Retrieval, and Intelligent Routing
A production architecture that routes semantic search, exact match, SQL, and knowledge graphs according to the information need.
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The Anatomy of Production-Grade Retrieval
Every layer of the retrieval stack: chunking, embeddings, hybrid search, rank fusion, reranking and evaluation - and exactly what breaks at each step.
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Building a Local-First OCR + LLM Pipeline for Structured Business Documents
Turn confidential PDFs into validated, structured records with OCR and schema-constrained extraction - without sending a single page to an external API.
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RAG vs. Fine-Tuning: Which One Should You Use and When?
A practical comparison across enterprise knowledge, behavior change, freshness, cost, and operations.
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AI Agent Security: Permissions, Human Approval, and Traceability
How to design safe boundaries, approval points, and auditable workflows for tool-using agents.
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Why Do AI Projects Fail in Production?
The data, deployment, monitoring, and ownership problems that matter beyond the model.
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Computer Vision in Manufacturing: Designing a Quality Inspection System
Cameras, lighting, defect definitions, edge inference and threshold policy - the decisions that determine whether a visual inspection system survives the line.
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