Blog
Read about what we're up to and what we're learning along the way
17 articles
Trusted Transparency
A 10-minute look at our core principle of radical transparency in software development
GeekWire: Seattle's SageOx Lands $15M to Help Humans and AI Agents Work in Lockstep
GeekWire covers SageOx's $15M seed round and our mission to build shared context infrastructure for AI-native teams.
Humans and AI Agents Are Now Coworkers — But Not Yet a Team. SageOx Raises $15M to Fix That.
A shared context layer that captures decisions, intent, and history to keep humans and AI agents aligned.
VentureBeat: AI Agents Are Missing All the Discussions Your Team Is Having — SageOx Has an Answer
VentureBeat explores how SageOx is solving the context gap between AI agents and the human conversations that shape team decisions.
How SageOx Got into Firmware
The unexpected journey from AI coding assistants to embedded systems. How a side project led SageOx into the world of firmware development and hardware integration.
Lessons Learned from Implementing an Open Claw for Slack Integration
Galex Yen shares insights on building a skill for Open Claw — from navigating Claw Hub security scans to optimizing token usage for hands-off automation.
How We Work: Source Code Management in Agentic Engineering
Part 5 of our How We Work series. Ryan Snodgrass on how branch management, commit strategies, and repo structure need to evolve when AI agents are writing most of the code.
How We Work: From Ideation to Execution
A 10-minute look at how we operate as an AI-native team — from ideation to execution — with a real-world example from Pier 70 in Seattle.
How We Work: Working on UX Projects
Part 4 of our How We Work series. Ryan Snodgrass on using multiple AI models for design work — and why ChatGPT generates better design prompts than Claude for visual tasks.
How We Work: Improving Prompting by Learning from Teammates
Part 3 of our How We Work series. Ryan Snodgrass on why seeing how your teammates prompt and reason with AI coworkers is one of the biggest learning accelerators.
How We Work: Working with Multiple Agents in Parallel
Part 2 of our How We Work series. Ryan Snodgrass on going from 50 agents to fewer, more focused ones — and why that's actually a sign of progress.
How We Work: Beads, Conductor, Expert Agents, and Skills
Part 1 of our How We Work series. CTO Ryan Snodgrass talks about the tools and workflows that have been the biggest unlocks in agentic engineering — from Beads for task tracking to creating expert agents by combining multiple AI models.