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SageOx
Shared structured team memory for human-agent teams
Last verified August 15, 2026 · Updated daily
What SageOx is building
SageOx builds what it calls a hivemind for human-agent teams. The product is a shared, structured context layer that captures decisions, intent, reasoning, and history across human chats, coding sessions, tool interactions, and agent runs, and makes all of it available as a live, queryable memory that every agent and human on the team can consult before acting. The philosophy is explicit: individual agents today are fluent but isolated. A supply chain agent, a pricing agent, and a margin agent can simultaneously contradict one another, confident and wrong, with no mechanism to reconcile. MCP solved connectivity between agents and tools. SageOx's thesis, articulated by Ajit in a LinkedIn post that is the clearest public statement of the product's intellectual core, is that connectivity is not comprehension. The next enterprise crisis is not that agents cannot connect. It is that they cannot understand what the team has already decided. SageOx is the infrastructure layer that closes that gap. The team also builds in public in an unusual way. They constructed a physical device, a $30 "puck," whose firmware Ajit, Ryan, and Galex wrote over a single weekend, that embeds SageOx's context layer into a physical office space. They demoed it to Steve Yegge (author of the famous Google Platforms Rant and one of the most respected software thinkers in Seattle) and he loved it. That is not a product announcement. It is a signal about how this team operates: they build the thing over the weekend, then hand-deliver it.
Why this matters
The AI agent coordination problem is the defining infrastructure challenge of 2026. IDC projects AI copilots embedded in 80% of enterprise applications by year-end. Gartner expects 40% of enterprise applications to integrate task-specific agents this year, up from under 5% recently. That is dozens of agents per company, each running in isolated context windows, each confident, each contradicting the others without knowing it. The memory and context management problem is not solved by better models. It is solved by infrastructure. A Fortune report from March 2026 put the number on what SageOx is addressing: roughly 70% of operational decisions inside the average enterprise have never been formally documented. The agents that get deployed into these environments inherit that gap. They do not know what was decided last week, last session, or five minutes ago in a parallel agent thread. SageOx captures the why, not just the what, and makes it available at inference time.
Open roles at SageOx
3 positions we're tracking. Roles are re-checked daily and removed when filled.
Hiring outlook
Very High. $15M seed with an explicitly small team. Ajit stated publicly they will make "a small number of key hires" post-raise. No public roles. No ATS. The only door is founders@sageox.ai or hello@sageox.ai.
Working at SageOx
SageOx: Shared structured team memory for human-agent teams. Founded , currently employees. At this stage, expect opportunity to shape your role based on the company stage.
Most SageOx jobs are based in Seattle.
Frequently asked questions
How many jobs does SageOx have open?
SageOx currently has 3 open roles, last verified May 2026.
Does SageOx hire remotely?
All current SageOx roles are based in Seattle.
What roles is SageOx hiring for?
SageOx is hiring across Engineering. The most recent opening is Staff AI/Infrastructure Engineer (Agent Memory Systems).
How do I apply for a job at SageOx?
Apply directly through the links above, or read our guide on how to actually get hired at SageOx.
Where is SageOx based?
SageOx is headquartered in Seattle, US.
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