Don’t Just “Throw Adam at It”: Misunderstanding Adam Will Cost You
You "vibe coded" the import. Understand Adam's optimization dynamics, why it fails spectacularly, and how to fix it.
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Backpropagation Explained for Beginners (Part 2): There Has to Be a Better Way
The idea that makes backpropagation possible.
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“Los Movimientos”: The Routing Problem That Nearly Broke My Spirit
Using mathematical optimization to solve a pickup-and-delivery problem with time windows.
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In a world where human time is expensive, learn how to use it only when really necessary
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The Most Beautiful Statistic: The History and the Science of the Humble Mean
The mean keeps making its usefulness felt in all sorts of situations, often in truly non-obvious ways
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How I Reproduced BM25, Dense Retrieval, and SPLADE on a 16GB MacBook
A practical reproduction of three retrieval baselines, including the crashes, fixes, and score checks that matter for RAG systems.
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Building a browser-use agent with OpenAI Agents SDK and Playwright MCP
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How to Optimize Vector Search When RAM Gets Too Expensive: On-Disk vs. In-Memory ANN Indexes
Architecting cost-effective infrastructure by navigating the latency and storage trade-offs of HNSW, SPANN, and DiskANN
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When Data Science Makes Us Sad: The Story of an Overbooked Flight
$8 million vs $5k + Potentially Going Viral
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The hidden cost of asynchronous systems, how tiny CPU tasks quietly became our biggest bottleneck while scaling hundreds of LLM agents.
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Loop Engineering for RAG Generation: iterate top-k one at a time
Enterprise Document Intelligence [Vol.1 #8bis] - Two regimes for sending retrieved candidates to the generation brick, the sufficiency signal that picks between them, and the per-question type dispatch that makes it cheap
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If you have ever wanted to actually build an LLM inference runtime yourself — pack your own weights, own every barrier, capture your own CUDA graphs — this is what that journey looks like on an H100. A step-by-step tour of a small runtime called annotated-llm-runtime, and the three bugs that produce...
Prompt Engineering Isn’t Enough: How Four Bricks of Context Engineering Stop RAG Hallucinations
Enterprise Document Intelligence [Vol.1 #9bis] - Your RAG isn’t hallucinating, it’s answering the wrong context faithfully. On real NIST and World Bank documents, watch each of the four bricks break, and the contract that closes it
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How Much of a Data Science Workflow Can Run on a GPU Today? Part 1: Accelerating Data Preparation
Exploring GPU acceleration with cuDF, cudf.pandas, and the Polars GPU Engine
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Apply long-running coding agents to become a more productive engineer
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Water Cooler Small Talk, Ep. 12: Byzantine Fault Tolerance
How do you make decisions when you can't trust anyone in the room?
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Automatically Assign a Category to Uncategorized Rows in Power Query and DAX
Having categorized data is everything in reporting. Uncategorized data cannot be grouped and aggregated. But sometimes we must assign a category to uncategorized data according to certain rules. Let’s see how I solved this in a facility management project.
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Many Companies Use AI. Few Know How to Build an AI-Native Enterprise Data Platform.
A practical enterprise AI architecture with data agents, AI-powered QA, and AI governance.
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Loop Engineering with Adaptive PDF Parsing: Start Cheap, Pay for a Heavier Parser Only When the Page Needs It
Enterprise Document Intelligence [Vol.1 #10A] - The escalation cascade and the free, deterministic checks that flag a failed parse before you pay for a deeper one
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A practical guide to combining pre-churn scoring with uplift modelling for smarter retention.
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Analog AI Is Back, But Can It Survive Its Own Noise?
AI's energy crisis is reviving an old idea: computing with physics instead of digital logic. Here's how analog chips actually work, why noise nearly killed the idea once already, and what happens when you simulate that noise yourself.
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