// 2026

ctx2pod

planned

Transform context into podcasts built for learning and knowledge discovery — turn documents, codebases, and research into audio you can actually absorb.

Note: This project is planned: the repository is staked out and the concept is scoped, but implementation has not started. The write-up below describes intent, not shipped behavior.

Project Overview: There’s a category of material you genuinely want to absorb—a dense paper, an unfamiliar codebase, a stack of internal docs before joining a project—that you never get around to because absorbing it requires sitting down and reading. Meanwhile there are hours a week (commute, walking, dishes) where your attention is available but your eyes aren’t.

ctx2pod converts arbitrary context into podcast-style audio designed for learning: not a text-to-speech read-through, but something structured the way a good explainer episode is—framing the problem before the details, building concepts in order, and returning to the important points instead of stating them once and moving on.

The Problem

Straight text-to-speech fails on anything substantive. Prose written to be read has structures that don’t survive the ear: dense parenthetical asides, forward references, tables, code blocks, and paragraphs that assume you can re-scan the previous one. Listening to it is worse than not listening.

Audio built for learning needs different source material than audio built for narration.

Objectives

  1. Ingest arbitrary context — documents, papers, repositories, notes, and links as input rather than a single supported format.
  2. Restructure for the ear — reorganize content into an order that works when you can’t skim or scroll back.
  3. Optimize for retention — pacing, recap, and emphasis that leave you actually knowing something afterward.
  4. Support discovery, not just consumption — surface adjacent ideas and connections rather than narrating one document in isolation.

Direction

The interesting work here is in the transform, not the voice. Turning read-optimized material into listen-optimized material—deciding what to cut, what to expand, what order to build ideas in, and where to reinforce—is the part that determines whether the output is useful or just background noise.

Status

Planning. Repository initialized; content pipeline and audio design are being worked out.