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.
#4971: Fine-Tune vs Prompt: Taming Hallucinated Deadlines
Big models add fake deadlines. Small models miss tasks. Which wrongness can you build a system around?
#4970: Labels vs. Book Covers: Structured Extraction Tradeoffs
General vision models vs. purpose-built pipelines for extracting data from messy real-world labels and covers.
#4969: How to Train a One-Class Detector from 300 Photos
From photo folder to production YOLO model — the real walkthrough for custom object detection.
#4967: AI Gateways: Worth the Middleware Tax?
When does an AI gateway's overhead justify its features? We break down the tradeoffs.
#4966: Local vs Cloud: Running Hugging Face Models
Hugging Face's compatibility tracker, cache management, and the real difference between Inference Endpoints and the direct API.
#4958: Multi-Model Transcription with LLM Reconciliation
Using multiple transcription engines and an LLM judge to catch errors in voice-to-text — especially tricky technical terms.
#4931: Building a DIY Barcode Inventory Cart
Old laptop, USB scanner, and Linux kiosk mode for a dedicated home inventory terminal.
#4925: ESP32 Mics for Remote Home Monitoring
Why an $8 ESP32 with a MEMS mic beats expensive cameras for remote audio monitoring in a vacation home.
#4920: Local Dictation on Android: The Real Bottlenecks
Why on-device speech-to-text on Android hits a wall at 30 seconds — and what silicon actually matters.
#4919: Parakeet vs Whisper: On-Device Dictation Showdown
NVIDIA Parakeet beats Whisper on phone dictation despite having more parameters. Here's why architecture matters more than model size.
#4902: Backward Batching: Fixing Slow Uploads Without Blocking Users
How one developer used background threads and deferred AI processing to fix a cataloguing workflow.
#4836: When AI Actually Touches Money
How Amazon uses LLMs to classify damage and set refunds — and the guardrail stack that keeps the AI from touching the dollar amount directly.
#4834: Why Your AI Bill Keeps Surprising You
How a 37-cent project and a $100 simulation reveal the hidden math of AI API pricing.
#4832: Your AI Memory Should Be Markdown Files
Why your AI project memory should live in Git-tracked Markdown files, not a proprietary platform.
#4827: When Your One-Person Stack Starts Fighting You
Your custom-built system was a perfect fit. Now it's a cast you can't escape.
#4826: Schema Design Is an Art Form
Why AI-generated schemas skip the thinking that makes databases survive contact with reality.
#4825: Russian Dolls: Skills, MCPs, and Plugins
When to use a skill vs MCP vs plugin in Claude Code — and when to keep it simple.
#4824: Build vs Pull: Docker Deploy Strategies for Solo Devs
Where to build your Docker image and how to trigger deploys — three patterns for small teams on a VPS.
#4822: Cloud-Local AI Hybrid: Does It Actually Work?
Can you pair Claude's reasoning with a local Qwen 7B for savings? The gap is wider than you think.
#4815: Agent Framework Lock-In: What Actually Breaks
Code-defined vs visual builders. LangGraph vs CrewAI. How portable are agent workflows really?