mCloud field notes
Practical perspectives on AI infrastructure, retrieval systems, MLOps, healthcare technology, and production engineering.
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A multi-agent orchestration system routes diverse incoming requests to the right specialist and then executes each as a multi-step agentic task. The mistake most teams make is using one framework for both jobs and getting the worst of each. This is Part 4 of The Token Scarcity Playbook — assembling routing (Part 1), model-agnostic design (Part 2), and the…
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An agent framework is the harness that orchestrates a model's reasoning, tool calls, state, and multi-agent coordination. This is Part 3 of The Token Scarcity Playbook — a technical comparison of the major frameworks built so you can score them against your own needs. It centers on a decision matrix rated on the criteria that actually drive selection — ease…
Read articleA model-agnostic application is one you can move from one model to another — to capture a cheaper option or route per task — without rewriting logic or shipping silent regressions. Routing (Part 1) only pays off if your system survives the swaps. This is Part 2 of The Token Scarcity Playbook.
Read articleModel routing is the practice of sending each request to the cheapest model that can actually handle it, instead of defaulting every task to the flagship. It is the single largest cost lever in the token scarcity era — and, done well, it improves quality and cost at the same time. This is Part 1 of The Token Scarcity Playbook.
Read articleThe token scarcity era is the moment the economics of building with AI inverted — when "use the biggest model for everything" stopped being clever and started being expensive. This is Part 0 of The Token Scarcity Playbook: why every team shipping AI in 2026 is suddenly counting tokens, and the tactics that follow.
Read articleAI is often described as “software,” but that framing hides the most important truth about this moment: modern AI behaves like an industrial system, not a digital product. Intelligence is no longer compiled once and distributed cheaply forever. It is manufactured continuously, in real time, using enormous amounts of electricity, silicon, memory, and…
Read articleGraph RAG - The RAG technique that uses knowledge graphs to enable multi-hop reasoning across entity relationships. This article explores how Graph RAG solves relational queries that traditional vector search cannot handle, when to use it, and how to implement it with Neo4j and other graph databases. For a comprehensive comparison of RAG frameworks…
Read articleContextual RAG - Anthropic's breakthrough technique that reduces retrieval failures by 67% through LLM-generated context augmentation. This article explores how Contextual RAG solves the ambiguous chunk problem, when to use it for high-stakes applications, and how to implement it for legal, medical, and financial use cases. For a comprehensive comparison of…
Read articleHybrid RAG - The production-standard RAG technique that combines keyword search (BM25) with vector similarity search. This article explores why Hybrid RAG has become the de facto standard for enterprise deployments, how it works, and when it delivers the best results. For a comprehensive comparison of RAG frameworks including Hybrid RAG, see this research…
Read articleNaive RAG - The foundational RAG technique that combines vector similarity search with LLM generation. This article explores how Naive RAG works, when to use it, real-world applications, and why it remains the starting point for most RAG implementations despite its limitations. For a comprehensive comparison of RAG frameworks including Naive RAG, see this…
Read articleWhat Is RAG? - A comprehensive introduction to Retrieval-Augmented Generation (RAG) for technical practitioners new to the concept. This article explains why RAG exists, how it solves fundamental LLM limitations, and why it's become essential for production AI applications.
Read articleEvery few decades, technology reshapes the foundation of healthcare. We saw it when electronic medical records replaced paper charts and again when mRNA redefined how we think about vaccines. Today, that seismic shift is being driven by artificial intelligence. Across clinics, labs, and trial sites, AI isn’t just crunching data — it’s rewiring how medicine…
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Read articleThe $50 Million Jupyter Notebook
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