Jigsaw Jeeves: Building a Puzzle Assistant using Computer Vision
Conceptual overview and walkthrough of a solution approach in Python
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From Prototype to Production: The Architecture Behind Secure & Governed AI Agents
Building the Responsible AI, security, and governance layers required for enterprise-ready agents
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Building Enterprise Agent Systems that People can Trust, Verify and Improve
5 principles that determine whether an agent system succeeds in production, explained through one I built for a $100M+ company.
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Graph Engineering Isn’t About More Connections — It’s About Which Ones Get Used
Adding more communication pathways between agents doesn’t necessarily improve multi-agent performance. In a controlled, reproducible experiment across 50 runs, recovery remained remarkably stable from 20% to 100% relationship density. But as the network became denser, the fraction of edges actually ...
In this article, you will learn three practical strategies for managing small context windows in large language models, along with working Python examples that demonstrate...
7 Kimi K3 Features That Make Every Other Model Feel Outdated
Developers launch new models every week, but most barely change how you work. Kimi K3 is different—not because of benchmark charts, but because of a few small API changes that fundamentally affect how you use it. The first is reasoning_effort, which defaults to maximum, alongside 131,072 max_complet...
What Can I Actually Do with a Small Language Model?
But by keeping these limits in mind, and planning for them, we can effectively use these small, local models for the following broad operations scenarios.
7 Regression Tests Every AI Agent Should Pass Before Deploy
In this article, you will learn seven concrete regression tests for catching the orchestration-layer failure modes that matter most before deploying an AI agent to...
Loop Engineering for RAG: The Small Loops Inside Each Step, the Big Loops Across the Pipeline
Enterprise Document Intelligence [Vol.1 #13bis] - The four bricks return useful results most of the time. Loop engineering is what the system does the rest of the time: when retrieval misses, when generation fails the schema, when the listing comes back incomplete, when an API call times out. Three ...
Designing a Persistent Knowledge Layer That Refuses to Guess
RAG Retrieves, It Never Remembers. A vendor-neutral blueprint for applications that accumulate understanding. Includes a complete Azure-native implementation (Microsoft Foundry, Azure AI Search, Cosmos DB, FastAPI) mapped to a property-insurance corpus.
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Mathematical Experiments Are Becoming Abundant Through Human-Machine Teaming
Two open problems, exact-arithmetic checking and a proof assistant, over a single weekend.
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RAG Workflow and Loop Engineering: The Dispatcher That Decides When to Loop and When to Stop
Enterprise Document Intelligence [Vol.1 #13] - Putting the patterns together, and why this is what “agentic RAG” should look like
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A preprocessing pipeline let my car price model peek at the test set before the exam, and the twelve points of R squared it cheated its way to
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Can a language model do live adversarial level design? Yes, emphasis on the adversarial part
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NVIDIA Nemotron 3.5 Lightning: The AI Agent Workhorse
Long-running AI agents often spend most of their time on routine execution rather than difficult reasoning. After making a plan, they may perform hundreds of tool calls, file reads, validations, commands, and formatting steps, so using a frontier reasoning model for every action can become unnecessa...
Cut an Enterprise RAG Pipeline’s Latency and Cost by Calling the LLM Less, Not by Buying a Faster Model
Enterprise Document Intelligence [Vol.1 #9ter] - The pipeline from Article 9 calls a model at several steps to be sure it is right. On easy questions that is needless latency. A per-question signal routes them past the model, about two seconds saved for a keyword match.
The post Cut an Enterprise RA...
How Baidu Unlimited-OCR Works: Solving Long-Document Transcription
About a month ago, Baidu (often called the “Google of China”) introduced Unlimited-OCR, an advancement over DeepSeek OCR. The model was designed to transcribe long, multi-page documents with high accuracy while delivering fast and stable inference. Unlike conventional vision-language OCR systems, Un...
An operating system (OS) is the fundamental software that acts as an intermediary between computer hardware and user applications. It manages hardware resources such as the CPU, memory, storage, and input/output devices, while providing essential services like process scheduling, file management, se...