AgentStack
The daily AI show and the systems behind it: OpenClaw automations, fitness-data connectors, local models, hardware, evaluations, and honest build notes.
Listen
AgentStack Daily
Daily episodes on models, hardware, evaluations, security, and the systems being built around them.
Browse episodesBuild
Fitness connector brief
An agent-ready architecture for Garmin, WHOOP, Speediance, Cronometer, 8Sleep, and normalized reports.
Read the implementation briefField report
AI fitness assistant
How the fitness-data assistant was assembled, what it automates, and where the hard edges still are.
Read the build storyWatch
AgentStack videos
Build walkthroughs, model tests, local hardware, failures, and the systems behind the daily show.
Browse videosImplementation notes
OpenClaw and AgentStack field reports
The durable written layer behind the daily show: architectures, failure modes, connector decisions, and working systems.
Build Logs
OpenClaw Finally Made My Fitness Data Useful
OpenClaw is usually shown as a content machine. My version is less flashy: a local agent system that turns scattered fitness data into daily training decisions.
Field Reports
Agent Brief: Build OpenClaw Fitness Report Connectors for Garmin, WHOOP, Speediance, and More
An agent-ready implementation brief for building OpenClaw fitness report connectors across Garmin, WHOOP, Speediance, Cronometer, 8Sleep, normalized JSON snapshots, and public GitHub repos.
Field Reports
How I Built My AI Fitness Assistant with OpenClaw
Toby explains how he built a personal AI assistant to correlate data from Speediance, Tonal, Garmin, Whoop, and 8Sleep - creating morning and nightly fitness reports that tell him how hard to train and how well he performed.
Build Logs
Building an AI Assistant That Manages Everything
How I built a custom AI on OpenClaw that tracks BJJ, analyzes recovery data, and generates training reports.
Build Logs
I Built an AI That Reads My Recovery Data Every Morning — Here's What It Actually Outputs
I spent a week building a custom fitness intelligence system on OpenClaw that pulls from six data sources and generates a morning training recommendation before I wake up. Here's the real output, the decision logic, and what I've learned from running it daily.
Signal vs. Noise
I Built an AI System That Manages My Entire Fitness Life. Here's How.
OpenClaw isn't just for developers. I use it to pull data from Garmin, WHOOP, 8Sleep, Speediance, and Cronometer - then generate morning and nightly fitness reports automatically. Here's my setup.
Use the podcast for the moving story and the field reports for the durable one
Daily episodes track what changed. Written reports preserve the architecture, evidence, and implementation details worth finding later.