Deep Research without Deep Pockets. When "Deep Research" landed in the premium AI tools, I was curious: what is this, actually? So I pulled it apart. And once I understood the architecture, I realised I'd already built most of it. DoomSummarizer leverages a…
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A glyph-based terminal renderer using shape-matching algorithms. Supports images, animated GIFs, videos, YouTube playback, and live subtitles with multiple render modes including Braille for maximum detail. NuGet License: Unlicense GitHub Releases The goal is…
NuGet NuGet Downloads GitHub Release (CLI) As I've been building lucidRAG I'm reading social media where people keep asking the same thing. 'How do you get features from scanned text?' the category error is always 'just use an LLM'...which WORKS but is very…
"How do I build an MCP server?" is the wrong question. SDKs exist. An LLM can scaffold one in seconds. The real question is: What role should an MCP server play inside a system that must not lie? The scarce skill now is designing the system around MCP:…
LLMs (Large Language Models) are being used as sensors. That is a category error: using a probabilistic synthesizer where a deterministic boundary device is required. This isn't developers' fault. Most mainstream examples and tutorials lead with the simplest…
NOTE: This is not a conventional blog article. It is a technical spec written for a concrete feature in lucidRAG. I iteratively feed this document to code-focused LLMs during development to reason about trade-offs, validate assumptions, and converge on a…
Status: In development as part of lucidRAG. Source: github.com/scottgal/lucidrag Where this fits: VideoSummarizer is the orchestrator of the lucidRAG family, combining five pipelines into a unified video analysis engine: DocSummarizer - Documents (entity…
Search is one of those features everyone underestimates. It looks trivial until real users start typing real queries -acronyms, half-remembered technical terms, punctuation-heavy names like "ASP.NET", or searches that are conceptually right but textually…
Status: AudioSummarizer.Core is currently in development as part of lucidRAG, a forthcoming mostlylucid product for multi-modal RAG. The implementation is complete and working—this article documents the architecture and design. CLI integration will be…
I built StyloFlow because I kept writing the same pattern over and over: components that react to what happened before, emit confidence scores, and sometimes need to escalate to more expensive analysis. Existing workflow engines wanted me to think in terms of…
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…
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…
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…
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…
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…
The Pattern That Kept Emerging It started with my blog's translation tool. The cache kept only 5 tasks per user, with 6-hour absolute and 1-hour sliding expiration. Sixth task? Oldest evicted. After an hour of inactivity, everything expired. Most developers…
A Ten Commandments–Compliant Architecture In which we build a voice-to-form system that doesn't hand the keys to the AI kingdom Here's the thing about voice interfaces: everyone wants them, nobody trusts them. And they're right not to. Most voice forms fail…
This is Part 5 of the DocSummarizer series, and it's also the culmination of the GraphRAG series and Semantic Search series. We're combining everything into a deployable web application. 🚨🚨 PREVIEW ARTICLE 🚨🚨 Still working out some kinks and adding…
What This Series Builds This series builds a working ecommerce system that proves you can have sophisticated customer intelligence without storing personal information. What We Build How It Works Semantic segmentation Vector embeddings group similar interests…
In Part 1 we covered the philosophy: transparent segmentation without PII. Part 2 covers session profiles, signals, and segment definitions. But first: how do you validate any of this without ever touching real customer data? For this series I generate a…
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