AgentStack
Die tägliche KI-Show und die Systeme dahinter: OpenClaw-Automatisierungen, Fitness-Daten-Konnektoren, lokale Modelle, Hardware, Evaluierungen und ehrliche Build-Notizen.
Anhören
AgentStack Daily
Tägliche Episoden zu Modellen, Hardware, Evaluierungen, Sicherheit und den Systemen, die darum herum entwickelt werden.
Episoden ansehenEntwickeln
Fitness-Konnektor-Briefing
Eine agentenfähige Architektur für Garmin, WHOOP, Speediance, Cronometer, 8Sleep und normalisierte Berichte.
Implementierungs-Briefing lesenFeldbericht
KI-Fitness-Assistent
Wie der Fitness-Daten-Assistent zusammengestellt wurde, was er automatisiert und wo die harten Grenzen noch liegen.
Build-Geschichte lesenAnsehen
AgentStack-Videos
Build-Walkthroughs, Modelltests, lokale Hardware, Fehlschläge und die Systeme hinter der täglichen Show.
Videos ansehenImplementierungs-Notizen
OpenClaw- und AgentStack-Feldberichte
Die dauerhafte schriftliche Ebene hinter der täglichen Show: Architekturen, Fehlermodi, Konnektor-Entscheidungen und funktionierende Systeme.
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.
Nutze den Podcast für die aktuelle Geschichte und die Feldberichte für die dauerhafte
Tägliche Episoden verfolgen, was sich geändert hat. Schriftliche Berichte bewahren die Architektur, Beweise und Implementierungsdetails, die es wert sind, später wiedergefunden zu werden.