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PodEcho

An AI podcast digest service — subscribe to your favorite podcasts and creators, and get every new episode as a digest email you can read in minutes.

Role · Solo developer (full-stack) 2026 AI application / web service Stack · TypeScript / React / Express / SQLite / LLM Live ↗
PodEcho

Good podcasts run two or three hours an episode — you bookmark plenty and finish few. PodEcho condenses them first: subscribe to the podcasts and creators you follow, and every day it watches for updates and turns each new episode into a digest email you can read in minutes — a one-line takeaway, the key points, a sectioned walkthrough, highlighted quotes from the transcript, and a verdict on whether the full episode is worth your time.

Try it live — podecho.cicala.chat ↗
PodEcho's four automatic steps: discover episodes, transcribe, summarize with AI, deliver by email
From episode release to your inbox, fully automatic

The experience is designed to be low-noise and trustworthy: subscriptions require double opt-in email confirmation, so nobody can sign you up without consent; every email carries one-click unsubscribe; and every quote in a digest comes from the real transcript — the AI is never allowed to invent one. Episodes with official captions use them directly; everything else goes through automatic speech-to-text, so both video and audio-only podcasts are covered.

Beyond podcasts there’s a second board, AI Picks: every day it trawls news feeds, papers (arXiv), Hacker News, Reddit and video platforms for AI-related content, has the AI summarize and relevance-score each item, and keeps only the handful actually worth reading that day — each with a rating and a one-line reason to read. It runs on its own domain model, separate from the podcast pipeline, while reusing the same budget, cost-tracking and security infrastructure.

The AI Picks board: a daily AI briefing and curated content cards with ratings and reasons to read
AI Picks · daily selection: 8 items distilled from 48 discovered, each with a rating and a reason to read
Engineering

Technical highlights

Under the hood it's an automated backend pipeline, engineered around four concerns.

Reliable

Every job carries a unique key — failures retry automatically, and a retry can never double-send an email; stuck jobs are recovered, and permanently failed ones land in a review queue for one-click retry.

Pluggable

The five external services — AI summarization, speech-to-text, email, RSS, video sources — all live behind interfaces; fake implementations run the whole loop locally at zero cost, and swapping vendors is a one-line config change.

Secure

External fetches go through SSRF protection with timeouts and size caps; subscription tokens are stored hashed; transcripts and titles are treated as untrusted input against prompt injection; AI output passes schema validation and escaping before reaching an email.

Cost-aware

Every AI call is metered for tokens and estimated cost; once the daily budget is hit, new jobs gracefully roll over to the next day instead of being dropped.

PodEcho admin console: channels, episodes, jobs, AI spend and the subscription funnel at a glance
The admin console — job states, AI spend and the subscription funnel at a glance, with one-click retry for failures
321
automated tests, all green
5
pluggable external services
$0
full local demo cost
1
summary-quality eval harness

A claimed defense must become a verified defense — injection resistance isn’t a line in the README, it’s a test that always runs in CI.

— Engineering principle
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