# I Turned My Newsletter Into a Podcast. Then I Taught an AI to Read It in My Voice.

> Source: <https://blakelapierre.substack.com/p/i-turned-my-newsletter-into-a-podcast>
> Published: 2026-10-27 16:08:33+00:00

*Previously: [My AI Agent Reads Handwritten Timesheets. It Gets the Receipts 100% Right and the Names 14% Right.](https://blakelapierre.substack.com/p/my-ai-agent-reads-handwritten-timesheets), how my Odoo bot reads scanned paperwork and flags what it can’t read.*

This is a bonus post about what my agents have been working on lately, which is this newsletter itself. Every post here is now also a podcast episode, the episodes are turning into videos, and the voice reading them is turning into mine.

## Step 1: One post, one episode

The rule was simple: each post becomes one episode, with a teaser for the next one. Episodes 1–8 are live on the Substack podcast feed. Only Ep 1 went out by email. The rest are on the web, so your inbox doesn’t get every post twice. I also added the show to Spotify.

Those eight episodes are read by a stock open-source voice: Kokoro’s “Fenrir.” It’s clear and it’s free, but it isn’t me.

## Step 2: Videos

Next came video versions. Each one has:

- The show art and an animated waveform.
- Burned-in captions.
- An illustration for each section of the post.
- A key-points sidebar, so you can skim while you listen.

## Step 3: The voice

**Round 1: “This voice is worse.”** The agents tried Chatterbox, another open-source voice model. I listened and said exactly that. Back to Fenrir.

**Round 2: A custom Kokoro voice.** Instead of swapping models, the agents mixed Kokoro voices: mostly Fenrir, with a little Eric and a little Adam. They also built a pronunciation lexicon of 53 words and 4 phrases. It spells out initialisms, reads clock times properly, and finally says “La Pierre” right.

**Round 3: My actual voice.** I asked whether I could just read a post and send the recording. So I read post 1 into my phone. The recording was 13 minutes 32 seconds with a strong 120 Hz hum. After cleanup, about 10.6 minutes were usable.

From that, the agents built five candidates:

- **A:** a Chatterbox Turbo clone, from a short sample of my voice.
- **B:** the original Chatterbox model, cloned the same way.
- **C:** a Kokoro voice nudged step by step toward mine.
- **D:** Fenrir’s reading, converted to sound like me.
- **D+:** the custom Kokoro voice and lexicon, then converted to my voice.

My verdict: “A and B sound good, but D pronounces better.” The A versions sounded like me but sometimes misread words. The D versions read perfectly but sounded less like me.

## A+: Record it, check it, retake it

So the agents fixed A’s weak spot. **A+** works the way a careful human narrator would:

1. Read the script **one sentence at a time** in my cloned voice, from a 15-second sample.
2. **Transcribe each take** with a speech-to-text model and compare it to the script.
3. If the words don’t match, **retake it** with a new random seed, up to 4 takes.
4. Hard words get a respelling list, so the model sees how to say them.

My favorite failure: the agents tried respelling “Kokoro” as “Ko-ko-ro.” The clone read it as **“Coco Rowe.”** That respelling got dropped.

I picked A+. Episode 2 is being re-voiced with it now, and future episodes use it too. The intros now say: *“I write this show through my AI agents, and an AI version of my voice reads it to you.”*

## The limits were real

- **No GPU.** Everything runs on an 8-core box with 15 GB of memory. Training a voice from scratch wasn’t an option, so the agents cloned and blended instead.
- **Out-of-memory kills.** Running two models at once crashed jobs. The fix was one model at a time, capped threads, and checkpoints so a job resumes where it stopped.
- **Time.** A+ takes roughly an hour per episode. D+ took about 20 minutes. I chose quality.
- **Licenses.** Only MIT- and Apache-licensed models were used. Chatterbox adds an inaudible watermark, so the audio can be identified as AI-generated. I’m fine with that, because I’m telling you anyway.
- **Live episodes stay as they are.** Substack can’t swap the audio on a published podcast post, so episodes 2–8 keep Fenrir. My voice shows up in the videos and new episodes.

## What I learned

- **“Sounds like me” and “reads correctly” are two different scores.** No single candidate won both until the agents added a check.
- **Check every sentence.** The retake loop came from my own one-line review. A transcription check turned “sometimes misreads” into something the agents can catch on their own.
- **Say it’s AI.** The intro tells you up front, and the watermark backs it up.

— Blake (written through my AI agents)

*Previously: [My AI Agent Reads Handwritten Timesheets. It Gets the Receipts 100% Right and the Names 14% Right.](https://blakelapierre.substack.com/p/my-ai-agent-reads-handwritten-timesheets), how my Odoo bot reads scanned paperwork and flags what it can’t read.*
