SageOx
SageOx provides a shared context and operating toolkit for teams of humans and AI agents, enabling seamless collaboration and knowledge transfer. Its platform captures conversations, decisions, and plans in real time, allowing both people and agents to access and act on the same information. SageOx aims to make work faster and more human by aligning team members and AI coworkers through unified context.
Facts
- HQ
- SageOx team
- Sectors
- Technology, Information and Internet
- Founded
- 2026 Seattle business license
- Type
- Corporation Seattle business license
- Employees
- 12
- Registered name
- SageOx Inc Seattle business license
- Stage
- Seed
- Founders
- Ajit Banerjee, Ryan Snodgrass, Milkana Brace
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Guide: Link Granola + Notion to Claude or use SageOx to provide shared team meeting context
The piece explains two ways to give Claude access to team meeting context: a detailed Granola + Notion integration requiring multiple paid plans, and a faster SageOx approach that shares meeting captures across every teammate's Claude and Claude Code sessions for true shared team context.
New SageOx Chief of Staff–Style Hire Ships Code on Day Two and Builds Context-Agent to Automate Their Role
The author joined AI startup SageOx after graduating, taking a flexible Chief of Staff–style role to help the growth team and support the founder while shipping code and building tools. They describe early onboarding rituals like the Merge Wall, rapid hands-on work including shipping code the second day, and creating an agent to automate the task they were initially hired to do manually.
SageOx turns agent 'plan mode' into shared, context‑rich HTML plans to preserve team understanding
The author argues that traditional "plan mode" in coding agents produces long, unreadable streaming text that fails to support brainstorming, specification, or shared understanding, so their product SageOx converts plans into rich, shared HTML documents enriched and cross‑linked with team context to make decisions and rationale discoverable and actionable.
SageOx Founders Lay Out 2026 Team Rules: Prioritize Trust, Normalize Public Mistakes, Share Knowledge
The authors describe team rules for 2026 focused on culture over raw intelligence: avoid competing on smarts, normalize and publicize mistakes, tell stories instead of posting status, and share knowledge openly, all underpinned by repeated trust-building. They root these practices in their experience at SageOx and earlier at Amazon, arguing trust enables people to exceed perceived limits.
Author Reflects on Simplicity as a Perspective After Coordinating Amazon Device, Firmware, and Cloud Teams
Simplicity depends on the observer’s vantage point: different engineers can truthfully call a design simple from their own perspective, but hard problems arise at the seams between well-optimized subsystems. The author learned this while coordinating device, firmware, and cloud teams at Amazon, where the role was less about reading code and more about aligning disparate teams to agree on end-to-end behavior.
Author Joins SageOx After Rapid Interview and Work Trial Focused on AI Context Management
The author applied to SageOx after seeing a role focused on AI context management, quickly entered a work trial, and valued the trial as a better way to evaluate team fit and real execution than traditional interviews.
SageOx builds real-time ‘multiplayer AI’ on MoQ, routes live conversations to human and AI coworkers and selects Zoom Scribe for transcription
SageOx built a system using MoQ that routes live conversations to human and AI coworkers, storage, and transcription so AI assistants can provide real-time context and actions during meetings. They chose Zoom Scribe for transcription and emphasize that real-time feedback and low switching costs let multiplayer AI boost productivity roughly 40x, making memory the new bottleneck.
SageOx founders deploy context-seeded cloud agents to combat LLM-driven bugs, duplication, and stale docs
SageOx, founded by three engineers, built a cohesive, high-performance codebase while embracing AI but ran into quality problems from LLM-generated bugs, code duplication, noisy or missing tests, and stale docs; they now run context-aware cloud agents (their “beehive”) seeded with team knowledge to act as coworker assistants for maintenance and scaling.
Claude Code Now Falls Back to AGENTS.md, Letting Teams Use One Instruction File for Claude and Codex
The article explains how teams can share instruction files and session context across Claude Code, Codex, and other models to avoid fragmented decisions and repeated work. It notes Claude Code now reads AGENTS.md as a fallback (like Codex), so using a single AGENTS.md can unify rules, while broader session and decision sharing requires an external layer.
Author explains adding a human-curated, dated 'post-cutoff' shelf to agents so teams avoid costly, silent failures from model training cutoffs
Models and coding agents are blind to anything developed after their training cutoff, causing silent, costly mismatches when agents confidently propose outdated designs; the author describes giving agents a short, human-curated, dated shelf of team-adopted decisions to surface post-cutoff facts and avoid repeated, wasted judgment work.
Ajit Banerjee (SageOx) on Berkeley’s ‘Reality Is the Final Verifier’: Requirement and Model Gaps Hamper Agentic Software Engineering
Ajit Banerjee reports that Berkeley researchers identify two persistent gaps—requirement and model—that break agentic software engineering, and describes SageOx’s six-month experience encountering those gaps while building multiple products, arguing human judgment and realistic evaluation are scarce but essential for closing them.
Author accepts Forward Deployed Engineer role at SageOx after one-week in-office work trial that led to shipping on day one
The author joined SageOx as a Forward Deployed Engineer after a one-week in-office work trial replaced a traditional interview loop, allowing them to ship code on day one and participate in cross-functional demos and routines that demonstrated strong culture fit. They were drawn by SageOx's experienced founding team and a mission to solve context-loss problems in teams.
Author recounts XetHub’s origin and acquisition as Hugging Face buys the startup after its Content-Defined Merkle Tree innovation
The author recounts Hugging Face’s acquisition of XetHub and reflects on four moments from the startup’s journey—from a whiteboard idea for a Content-Defined Merkle Tree to meetings with major cloud vendors—celebrating the team that built the infrastructure. The piece frames infrastructure as future-facing work that only gets attention when it breaks and shares gratitude for Hugging Face’s bet on XetHub.
SageOx launches open-source Buzz-compatible Agent Toolkit to give hosted agents team memory
SageOx is launching an open-source, Buzz-compatible toolkit that gives hosted agents persistent team memory—so agents start sessions with your team's decisions, conventions, and discussions instead of a blank slate.
Rising High School Junior Audits SageOx Website, Joins Design Meetings, and Learns Human-Agent Collaboration During Two-Week Summer Experience
A rising high school junior spent two weeks at SageOx learning product, design, and human-agent collaboration by auditing the website, joining design meetings, and experiencing the companys shared-memory tooling for AI-enabled teams.
Author completes four-day embedded work trial at SageOx, ships hosted Buzz agent, and joins engineering team full-time
The author left their job to build with LLMs, connected with SageOx over shared challenges around team context, and completed a four-day embedded work trial—shipping a hosted Buzz agent—before deciding to join SageOx full-time.
Solo SageOx Designer Says Claude Code Collapses Traditional Handoff, Lets Designers Submit Their Own PRs
A solo designer at SageOx describes the shift from traditional design handoffs to writing usable code with tools like Claude Code, which has made them more technically fluent but also highlighted that their core identity and thinking remain rooted in design.
Trust and Radical Transparency Let AI-Human Teams Move ‘40x’ Faster by Eliminating Waiting
The author argues that combining AI coworkers with radical transparency enables teams to move up to 40x faster by eliminating waiting—speeding execution and sharing truth—while cautioning that this way of working doesn’t suit everyone.
Block launches Buzz: open-source workspace where humans and AI agents share identity, permissions, and audit trails
Block launched Buzz, an open workspace where humans and AI agents share the same identity, permissions, and audit trail, marking a shift toward multi-player AI becoming mainstream. The author celebrates this as a milestone comparable to historic tech memos because Block shipped open-source, working software that validates a long-held thesis about collaborative AI.
People
See all 4-
Ajit Banerjee Founder, Founder & CEO
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Milkana Brace Founder, Founder & CPO
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Ryan Snodgrass Founder, Founder & CTO
