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Technical articles

Browse all technical articles on the MDisBetter blog.

Technical

Audio Quality vs Transcription Accuracy: Complete Guide

Signal-to-noise ratio, microphone choice, room treatment and pre-processing: what actually moves transcription accuracy from 60% to 99% on real recordings.

10 min read May 2026
Technical

Building an Enterprise Document Migration Pipeline: Word to Markdown

Architecture for migrating thousands of Word documents to Markdown: audit, categorise, prioritise, convert with Pandoc, quality-check, organise and publish.

12 min read May 2026
Technical

How We Built MDisBetter's PDF Converter: Lessons Learned

Engineering retrospective: the architecture decisions, the failure modes we hit, the accuracy improvements that actually moved the needle.

8 min read May 2026
Technical

Building a Searchable Audio Archive with AI Transcription

Voicemails, meetings and interviews sit unindexed. Convert them to Markdown, organize by date and speaker, then search with ripgrep or Obsidian in seconds.

10 min read May 2026
Technical

Building a Searchable Video Library with AI Transcription

Turn videos into a searchable text archive: transcribe them, organize the Markdown with frontmatter metadata, then search it all with ripgrep or Obsidian.

11 min read May 2026
Technical

Building a Web Knowledge Base for AI: Architecture Guide

End-to-end architecture for turning web sources into a queryable AI knowledge base: conversion, chunking, embedding, vector storage and update strategy.

11 min read May 2026
Technical

Converting JavaScript-Heavy Pages to Markdown: Technical Deep Dive

Static fetch vs headless browser, Playwright and Puppeteer mechanics, wait conditions, and cost tradeoffs behind URL-to-Markdown tools on JS-rendered SPAs.

9 min read May 2026
Technical

How AI Transcription Actually Works (Whisper, ASR, and Beyond)

From HMM-era speech recognition to encoder-decoder transformers and Whisper's 680k-hour training set, plus why structured Markdown output matters afterward.

10 min read May 2026
Technical

How the DOCX Format Works Internally (And Why Conversion Is Hard)

A .docx file is a ZIP archive of XML. Walk through document.xml, styles.xml, and OOXML to see why naive text extraction loses heading semantics.

11 min read May 2026
Technical

How PDF Works Internally (And Why Text Extraction Always Breaks)

A technical deep-dive into the PDF file format: content streams, glyph positioning, why extraction is lossy, and what this means for AI workflows.

9 min read May 2026
Technical

How YouTube Transcript Extraction Actually Works

How YouTube captions work: auto-generated ASR versus creator-uploaded tracks, why auto-captions are unreliable, and how fresh AI re-transcription compares.

11 min read May 2026
Technical

How HTML to Markdown Conversion Actually Works (Under the Hood)

Technical deep dive: DOM parsing, tree-walking, element-by-element conversion rules, and why naive html2text falls short on modern web pages.

9 min read May 2026
Technical

Mammoth vs Pandoc vs AI: Word to Markdown Conversion Deep Dive

Technical comparison of three Word-to-Markdown approaches: Mammoth.js, Pandoc, and AI-powered conversion. When to use each, with realistic tradeoff numbers.

11 min read May 2026
Technical

Markdown vs HTML for LLMs: Token Count Comparison (Real Numbers)

We counted tokens for HTML and Markdown versions of 5 representative web pages with tiktoken. Markdown averaged 85% fewer tokens. GPT-4o cost math included.

8 min read May 2026
Technical

Markdown vs Plain Text for Transcripts: Why Structure Matters

What plain-text transcripts lose and what Markdown preserves: punctuation, sections, timestamps, emphasis, and the LLM extraction quality difference.

9 min read May 2026
Technical

Markdown vs SRT vs VTT: Which Transcript Format for What?

SRT and VTT are subtitle formats for video players, plain text is unstructured, and Markdown adds structure plus AI-readiness. When to use each format.

10 min read May 2026
Technical

Markdown Chunking Strategies for RAG: Headers vs Tokens vs Paragraphs

Three chunking strategies for RAG pipelines: header-based, token-based, paragraph-based. When each wins, with code examples and evaluation metrics.

9 min read May 2026
Technical

Token Count: PDF vs Markdown on 20 Real Documents (Hard Numbers)

Methodology and results from a 20-document benchmark measuring token usage on raw PDF vs Markdown for ChatGPT, Claude, and Gemini. With cost implications.

8 min read May 2026
Technical

Using Video Content in RAG Pipelines: Architecture Guide

Technical guide to integrating video into RAG: transcript to Markdown, chunk by H2/H3, embed, retrieve. Python with sentence-transformers and ChromaDB.

12 min read May 2026
Technical

Content Extraction: Readability vs Trafilatura vs AI-Powered

A technical look at the main-content extraction problem. Mozilla Readability, Trafilatura, and LLM-based extraction compared: strengths and weaknesses.

10 min read May 2026
Technical

Why Word Tables Are the Hardest Conversion Problem (Technical)

Word tables allow nested tables, merged cells, and multi-row headers. Markdown tables are flat rows and columns. What survives, what breaks, how to bridge it.

10 min read May 2026