Development
Building software: programming, developer tools, APIs, deployment and DevOps, and building with AI (agents, MCP servers, RAG, AI coding tools). An extra channel alongside an episode's main one, so AI engineering episodes sit in both.
#6222: Why Fine-Tuning Runs Can't Always Resume
Eighty cents and twenty-five minutes per training run — so why does the checkpoint question still keep a tinkerer up at night?
#6221: How Many Examples Does Fine-Tuning Actually Need?
Everyone says "thousands." Nobody says how many for your task. Here's how to measure the number yourself.
#6219: Dictation Beyond the Keyboard
Pedals, push-to-talk, and Android gesture apps promise keyboard-free dictation — but can any of it become a dependable daily setup?
#6218: Training a LoRA to Write Like You
A Humanizer model stripped every trace of the author. The fix isn't a better Humanizer — it's a LoRA trained on your own writing.
#6217: Fine-Tuning a Trillion-Parameter Model at Home
What does it actually take to full fine-tune a trillion-parameter model? Sixteen terabytes of optimizer state, hundreds of GPUs, and a very big bill.
#6207: Two WERs, One Model: Inside ASR Eval Harnesses
Same model, same audio, two different word error rates. The gap lives in the normaliser — and that's just layer two of three.
#6205: Where Should Your Notebook Actually Run?
Colab's free GPU comes with a 12-hour wall and hidden secrets in your saved outputs. Here's where notebooks should actually live.
#6203: How Claude Code Sessions Message Each Other
Two terminals, one machine: how Claude Code sessions find each other by name, pass messages, and subscribe to an idle ping.
#6202: Israel Votes, Part 6: Asking the Decision Models
Two decision models, identical evidence, one table of betting prices — and both flip their pick for Israel's next leader.
#6201: Inside Cloudflare's Clef: A Language Model That Can't Speak
Cloudflare's Clef reads text, images, and video but outputs only probabilities — no words. Here's what's actually under the hood.
#6200: What Israeli Election Polls Hide Behind Seat Counts
A new open source tool simulates 100,000 election allocations from a single poll — and shows why "4 seats" is less certain than it sounds.
#6199: Running AI Experiments Before an Election
What MLflow, Braintrust and notebooks actually do when you have five days and one forecast to get right.
#6198: Benchmarking a TTS Model on Your Own GPU
Real-time factor, warm-up artifacts, and why an 8-bit quantized speech model might not run any faster.
#6196: Fine-Tuning ASR: When Your Model Memorizes You
Your fine-tuned speech model aces your training recordings — but does it actually work on fresh audio?
#6194: Teaching a TTS Model His Own Accent
One man fine-tuned a text-to-speech model on his own voice to get Irish-accented English that can say Hebrew words mid-sentence.
#6192: What Actually Happens When You Train a Model
Data in, model out — except the "data" is pairs, the split is the whole game, and one leaked speaker can fake your score.
#6191: What Actually Happens During Fine-Tuning
Sixteen bytes per parameter in, two out — a walk through the forward pass, backward pass, and optimizer that turn a dataset into new weights.
#6190: When Your AI API Quietly Changes Under You
Same API name, different model behind it. How to tell when the thing you tested stops being the thing you're using.
#6186: A Virtual Disk Inside Your Linux Filesystem
Loop devices let a plain file act as a real disk — format it, encrypt it, mount it from fstab. Here's what works, and what bites back.
#6183: Private Podcast Feeds: Tokens, Buckets, and Basic Auth
How do you keep a podcast feed for four people away from everyone else? Tokens, buckets, and the auth podcast apps barely support.