Six in the morning. My phone shows an Apple Podcasts notification — today's episode is ready. I press play, walk to the kitchen, and by the time the kettle is on, a calm British voice has told me what yesterday's commits did, what's in flight today, what the markets opened on, the three news items worth knowing about, and a one-liner about the weather designed to make the rain feel personal.
By the time I'm at my desk, the matching newsletter is in my inbox — same brief, written form, with links you can actually click. I haven't opened Twitter. I haven't opened LinkedIn. The day starts on my goals, not someone else's algorithm.
The whole thing runs itself overnight on a Cloudflare Worker. Total running cost: about ten cents a day. Here's how it's built — short version.
// the pipeline
// why the picks are relevant
The curation step doesn't filter "interesting news in general". It filters news relevant to me. The way it knows what me means is my Obsidian vault — a handful of plain-markdown KB notes I maintain: my tech stack (Cloudflare + TanStack + SST), what I'm working on (the active side projects + my day job's domain), what I want to read more about (geotechnical engineering, AI infra, Dutch market). Every morning the curation prompt gets a compact summary of those notes stitched on top of the raw news pile, and Haiku picks accordingly.
Result: a recommendation engine I fully control. Not based on what some algorithm thinks I want — based on what I literally wrote down. Want fewer crypto items? Delete the crypto-curious line from the KB. Want more geotech? Add a note. No tracking pixel, no behavioural model, no "people like you also read". The notes stay on my laptop; only the relevant bytes get pasted into a one-shot prompt at run time. Private by construction.
This is the part I think more people should be doing. You already keep notes. The notes know you better than any feed does. Hand them to a cheap LLM with a "pick what matters to this person" prompt and you get a daily brief that is yours — not a remix of everyone else's morning.
// bonus track
The expensive parts — the voice, the publish pipeline, the podcast-app delivery — are already paid for. Plug a different writer in and you've got a topic-specific show. Mine is a two-host interview format called Conversations with Aria — Aria (witty British host) gets interviewed by Brian (earnest American journalist) about whatever I want to learn about.
Workflow is one command. I drop a markdown brief on a topic — anything from "how a CPT works in detail" to "pile bearing capacity and basal heave in Dutch soft soils" — and the same make-podcast skill writes the dialogue with Kimi K2, voices both speakers in parallel with ElevenLabs, stitches them with ffmpeg, and publishes. ~10 minutes wall clock, ~12 cents in API.
That's how the geotechnical-engineering episodes got made — I wanted a structured refresher on the discipline I work in. So I wrote a brief covering bedrock to bearing capacity, ran the skill, and now I have a fourteen-minute interview I can replay on the commute. Same trick works for anything you want a calm voice to tell you about — for me, for you, for one listener.
// why it works
// the stack
For the longer write-up on the genre, see Audience of one — the personal podcast is a new genre →
Note: this article is an AI-generated summary of how the system works. The product is real. The prose isn't hand-written.