Reduced RAG: Stop Stuffing Context Windows and Start Extracting Signals

If you're brand new to RAG, start with RAG Explained and RAG Architecture. This post is for the point where you've built a RAG pipeline that mostly works… and now you're paying for it in cost, fragility, and "why did it answer that?" debugging sessions. What…

Constrained Fuzzy OCR - The Three-Tier OCR Pipeline

Part 4: Image Intelligence introduced the ImageSummarizer wave architecture and the broader patterns. This article deep-dives into the OCR subsystem—three tiers of text extraction, intelligent routing, and the filmstrip optimization that achieves 30× token…

Image Summarizer: A Constrained Fuzzy Image RAG Engine

Parts 1-3 described Constrained Fuzziness as an abstract pattern. This article applies those patterns to a working image analysis pipeline that demonstrates the principles in action. CLI Tool - Command-line interface for image analysis Core Library - The…

Constrained Fuzzy Context Dragging: What Gets Remembered

One of the easiest ways to make an AI system fail is to let it remember too much. Most "context handling" approaches boil down to one of two mistakes: Stuff everything into the prompt and hope the model figures out what matters Repeatedly re-summarise…

Constrained Fuzzy MoM: Signal Contracts Over Agent Chatter

Part 1 described a pipeline: Substrate, Proposer, Constrainer. One probabilistic component, bounded by deterministic truth. But what happens when you have multiple proposers? Multiple LLMs? Vision models talking to text models? Heuristics feeding into neural…