Embedded

Mission Operations Engineer Ian Orzechowski joins us to demystify what it actually takes to operate satellites in space. We discuss managing small satellite constellations, the transition from multi-million-dollar bespoke satellites to commercial off-the-shelf hardware, and how satellite operations balance attitude control, battery health, and command authority (the ABCs of mission ops). Ian also shares stories about recovering tumbling satellites using torque rods, handling solar storm radiation, thermal management in a vacuum, orbital mechanics, collision avoidance maneuvers, and why testing hardware on the ground can sometimes do more harm than good. 
Discussion Resources & Links
Hubble Network – Satellite constellation enabling direct-to-satellite Bluetooth Low Energy (BLE) connectivity

The Amp Hour #728: Space Age Bluetooth with Alex Haro – Deep dive into Hubble Network's underlying BLE-to-satellite hardware technology

Kessler Syndrome – The theoretical scenario where orbital space debris cascades into expanding collisions

WSPR (Weak Signal Propagation Reporter) – Amateur radio protocol designed for low-power, low-data-rate transmissions

Space Engineering & Mission Operations Recommended Reading:
What is Satellite Mission Management? blog post provides an overview of satellite mission operations and ground segment architecture.

The classic handbook on space mission analysis and design is Space Mission Analysis and Design (also on archive.org). There is a new edition: Space Mission Engineering: The New SMAD 

Transcript
Origami in the thumbnail folded by Elecia. Lunar Lander pattern by Kim Best. Rocket designer unknown.

Christopher and Elecia catch up on life, firmware consulting, daydreams, and projects. 
Elecia thinks aloud about low-stimulation education toys. Christopher shares his experience using AI tools to build a custom Swift metronome app to train off-beat timing, specifically how he turned the project into a structured language lesson plan. They discuss using Google's NotebookLM on the Embedded.fm transcripts, award wins, handling guest self-invites, contract engineering advice for high schoolers, security key vulnerabilities, and how moving from desktop to embedded requires viewing your hardware as your framework. 
Discussion Resources & Links
Embedded.fm LLM – Search and query all past Embedded.fm show notes, blog posts, and transcripts

Hasbro Women Innovators of Play – Toy design challenge encouraging women-led innovations

Mermaid Live Editor – Text-based diagramming and flowchart tool for Markdown documentation

eMudhra & GoAhead Vulnerability Overview – Security issues surrounding public key infrastructure, TLS, and embedded web server DHE cipher secrets

Transcript

David Such joins us to discuss his new book, Embedded AI: Intelligence at the Deep Edge. We explore the boundary between classical signal processing, heuristics, and edge machine learning; IMU processing and sensor fusion; and how to determine what sort of ML fits on your processor. David also shares his experiences writing for No Starch Press and why future robotic architectures need a digital cerebellum for low-level reflexes.
David Such is an electrical engineer based in Sydney. He is the director of Reefwing Software.
DISCUSSION RESOURCES & LINKS
David's Website & Book Resources:
Embedded AI: Intelligence at the Deep Edge (No Starch Press, on Amazon)

Embedded AI GitHub Repository

Embedded AI Newsletter Signup
Reefwing Software Website

Reefwing Software on Medium

Technologies & Frameworks Mentioned:
Sensor Fusion, Kalman filters, Mahoney filters, and quaternions for IMU processing

TensorFlow Lite for Microcontrollers & Edge Impulse

Raspberry Pi Pico / RP2040 PIO and DMA engines for high-speed signal processing

Syntiant neural processing chips (Arduino Nicla Voice)

MicroPython for embedded scripting and test automation

Book Giveaway & Discount Code:
No Starch Press is giving away two print copies of Embedded AI (US/Canada residents). Entry rules are in the show, due by Nov 1, 2026. There is also a coupon for the book good through Nov 5, 2026.

Adam Smith from UC Santa Cruz joins us to discuss local Small Language Models (SLMs) and building open, autonomous tools. We explore his BayLeaf AI counterplatform, transagency (the "me-and-the-car" concept of human-agent collaboration), context distillation, and running models locally without relying on data-harvesting corporate clouds. 
Adam also shares practical strategies for working with coding agents, including why plain-text AGENTS.md files outperform model weight fine-tuning for long-term knowledge retention. He also describes how he uses open-source tools like OpenWebUI, OpenCode and OpenChamber to integrate small and local LLM integration into development environments and web chats. 
Discussion Resources & Links
Adam's Projects & Research:
BayLeaf AI Counterplatform: Hyper-local, open-source AI infrastructure built for UC Santa Cruz. See also the BayLeaf Getting Started Guide and BayLeaf Blog.

Adam Smith's UCSC Directory Page & Personal Website

Adam Smith on YouTube & GitHub (@rndmcnlly)

Open-Source Agent Harnesses & Wrappers:
OpenCode – Open-source command-line coding agent harness with VS Code integration (comparable to Claude Code)

OpenChamber – Graphical desktop wrapper for OpenCode with VS Code support (comparable to Claude Cowork)

OpenWeb UI – Self-hosted web interface and desktop app for local and remote LLM models

OpenRouter – Token broker/middleman routing requests across competitive LLM inference providers

r/LocalLlama – Community subreddit for local LLMs, open weights, and hardware advice

AGENTS.md Convention & Agent Skills Standard – Open standards for persistent context management

Context Distillation Paper (arXiv)

Adam's Guide to Building Transagent Capabilities:
Scope by Project Roots: Harnesses like OpenCode and OpenChamber use project root folders to establish clear, safe boundaries for agent execution.

Store Context in Plain Text: Keep global and project preferences in simple .md files (like AGENTS.md or GLOSSARY.md). Plain text files make your accumulated knowledge portable across different model front-ends and harnesses.

Handle Errors by Rewinding: When your LLM or agent makes a mistake, don't yell at it or try to correct it inline—go back in time to before the error and alter your prompt or context to lead it away from the mistake.

Refactor Preferences into Skills: As your AGENTS.md context grows, ask the agent to factor recurring preferences out into modular skill files (.agentskills).

Teach Transagency: Distinguish between standalone agent capabilities (autonomous work) and transagent capabilities (how the agent works with you).

Build Local Tools: Ask the agent to build desktop helpers (QuickLook triggers, push notifications, or fuzzy glossary lookup) to keep a shared orientation.

Elecia: "Complete one project or start a dozen?"
Adam: "Tens of thousands, and start hundreds more within the starting of the other projects recursively forever."
Transcript

Aaed Musa joins us to talk about building robot dogs, custom actuators, and his YouTube channel. He shares how he moved from 3D-printing servo robots in his parents' garage to designing capstan drives, and how he uses reinforcement learning to train quadrupedal walking gaits. We also talk about his senior design project (CARA 2.0), his Spider-Man web-shooter build, lessons in storytelling and video editing, and why he's starting a company to bring friendly, expressive quadrupeds into the home. 
Aaed Musa is a mechanical engineering graduate from Purdue University, a hardware creator on YouTube, and co-founder of the robotics startup Mecha. 
DISCUSSION RESOURCES & LINKS
AAED'S CHANNELS & PROJECTS:
Aaed Musa on YouTube: Project videos covering quadrupedal robot dogs, Spider-Man web shooters, and custom actuators. Oh, and planetary gears.

More detailed project write ups are under projects on his personal site, including CARA 2.0.

Github repository

Robots Everywhere with Aaed Musa | The Amp Hour

ROBOTICS & ACTUATOR TECH:
Dyneema DM20: synthetic rope with zero creep used in zero-backlash capstan drives

NVIDIA Isaac Sim: simulation and reinforcement learning environment for robotics

OpenMV: Very smart MicroPython-powered machine vision modules. Kwabena Agyeman has spoken with us about OpenMV before:

497: Everyone Likes Tiny 

477: One Thousand New Instructions

212: You Are in Seaworld

SOME YOUTUBE CHANNELS MENTIONED:
Good 3d printing youtube channels:

3DPrintingNerd 

CNCKitchen 

MadeWithLayers 

Jeremy_Fielding: great for explaining how things work and coming at engineering from a non engineering direction (Embedded 385: I Just Wanted an Industrial Arm)

James Bruton: Robot dogs! 

Mark Rober has fantastic storytelling and approachable engineering.

Stuff Made Here has robots and gadgets, generally a broad scope of engineering.