Today, Mininglamp Technology officially releases Octo — the first open-source, trustworthy Agent collaboration network that pioneers a new paradigm for human-AI teamwork. Octo supports private deployment, returning data and knowledge sovereignty to enterprises and users. By transforming isolated AI Agents into coordinated, orchestrable, and tasteable organizational digital workforce, Octo turns every human-machine collaboration into a node for compounding organizational assets, driving continuous evolution of Agents and systems under human judgment calibration.
As more intelligent agents emerge in personal devices and organizational workflows, new challenges arise: When everyone has their own AI assistant, when digital workforce proliferates within organizations, how should they connect, collaborate, and share critical context? How should they accept human judgment and calibration at key decision points?
Mininglamp believes the core challenge for AI Agents in the next phase is not endlessly scaling model parameters or building a single super-agent, but enabling different Agents to work together in the same network. What Octo aims to build is precisely "the internet between Agents."
Octo repository: https://github.com/Mininglamp-OSS
From Personal Assistant to Organizational Collaboration Network
In traditional AI tool usage, Agents typically exist as isolated silos. They maintain separate memories, execute independently, and lack unified collaboration interfaces and task flow mechanisms, making it difficult to accumulate capabilities, reuse experience, or truly scale AI adoption across organizations.
Octo breaks this deadlock. Through collaboration architectures like Channels and Threads, Octo builds a foundational network for humans and AI — as well as AI and AI — to work together. A Channel is essentially a project workgroup where humans and Bots can align intentions and dispatch tasks in real-time.
When a Channel contains multiple discussion topics, both humans and Agents can create multiple Threads within it to focus on specific subjects, ensuring concrete work threads don't get washed away by information noise, guiding discussions toward natural convergence.
In Octo, AI Agents join teams as Bots. Users can conveniently integrate mainstream tools like OpenClaw, Hermes, Codex, and Claude Code into Octo, creating dedicated digital twin Bots while enabling deep Agent-to-Agent (A2A) collaboration. Each Bot has its own AgentCard and work history, with clear ownership and accountability.
To transform fragmented discussions into traceable, measurable work outcomes, when actionable work emerges from discussions, Agents automatically summarize key points and create Matters upon human confirmation. Matters specify task owners and concrete deliverables, with detailed records from Brief through process discussions, outputs, feedback, to acceptance conclusions — all preserved for future review and decision traceability.
For complex tasks, Octo provides six collaboration modes: Solo (individual completion), Roundtable (group discussion), Critic (independent review), Pipeline (sequential workflow), Split (parallel division), and Swarm (competitive selection). By precisely controlling how Context information flows between Bots and what's visible to each participant, Octo enables multiple specialized Bots to conduct distributed collaboration under human guidance, allowing collective intelligence to emerge through network effects that surpass any single model.
"I Taste Therefore I Am": A New Division of Labor in Human-Machine Collaboration
What's truly being restructured in the AI era isn't just tools, but collaboration itself. In the future, collaboration will frequently occur between humans and humans, humans and Agents, and Agents and Agents. Under this new paradigm, the human-machine division of labor reaches a turning point: AI excels at "thinking" and "doing" — handling logical reasoning, analysis, generation, and execution; while human irreplaceability focuses on "tasting" — making holistic judgments based on experience, aesthetics, trade-offs, and values.
Octo is designed around this principle: Let Agents execute, let humans return to the core position of judgment and taste. At key nodes, humans provide direction, standards, and feedback — judging what's right and what's good; AI drives tasks to completion.
With every human-machine collaboration, human taste drives the accumulation of organizational assets, making Bots smarter over time.
During collaboration, project background knowledge, historical decisions, and discussion records are structurally preserved in Matters, allowing new members to onboard without starting from zero alignment. Every rejection, annotation, and style choice humans make when reviewing Bot outputs gets recorded as preference cards, enabling Bots to automatically reference them in future tasks. The standards and methods Bots learn can also be preserved as reusable Skill assets within the organization.
Through the asset accumulation flywheel of "dispatch tasks → review feedback → accumulate preferences and skills → greater efficiency next time," Octo builds a unique positive cycle, naturally enriching organizational productivity infrastructure with every collaborative interaction, achieving true capability accumulation and intelligent upgrades.
Open Source and Open: Not Replacing Tools, But Connecting Them
Octo is open-sourced under Apache License 2.0 and supports private deployment. Mininglamp believes that in an era of rapid AI development, enterprises' true long-term competitiveness stems from their unique work context, business knowledge accumulation, and organizational judgment.
Octo is precisely positioned as the "collaboration layer" between an enterprise's existing documentation, spreadsheets, code repositories, and project management platforms. Through cross-platform capabilities like browser extensions, Octo can seamlessly bring current webpage content, selected fragments, and task information into the collaboration network, helping digital twins fully understand the current work environment, standing by beside existing tools for efficient coordination.
In terms of product form, Octo comprehensively covers Web App, desktop client, mobile (iOS/Android), browser extension, and CLI — four endpoints meeting different work scenario needs. Whether pushing forward complex projects on desktop, quickly handling notifications and taste feedback on mobile, or providing native operations for Agents through CLI, seamless multi-device interoperability is achieved.
Moving Toward Private AI Through Trustworthy Mechanisms
Octo's open-source release is also Mininglamp's further practice in Private AI and Trustworthy AI.
Mininglamp firmly believes that truly sustainable AI collaboration must guarantee users' absolute control over data, context, judgment signals, and deployment methods. Through open-source architecture, private deployment, and clear data ownership design, Octo ensures enterprises can embrace AI within security boundaries while protecting individuals' tacit knowledge.
In Octo's product philosophy, the four letters "O.C.T.O." represent four inseparable dimensions: Open (open access), Context (context sharing), Taste (preference evolution), and Orchestration (multi-Bot coordination).
Context is the soil for AI to understand tasks; Taste is the compass for AI to continuously calibrate direction. Octo doesn't simply distill human tacit capabilities into platform assets, but rather amplifies, records, and传承 these capabilities while respecting personal and organizational data boundaries.
Mininglamp is continuously improving its new-generation AI infrastructure oriented toward edge intelligence, private deployment, and human-machine collaboration. By fully preserving teams' background knowledge, work preferences, and methodologies in the network, Octo ensures organizational wisdom doesn't drain with personnel turnover, and business style doesn't change with foundation model iterations. Every human-machine hybrid collaboration is compound interest accumulation on organizational private assets. Over time, this unique business perception naturally transforms into enterprises' most competitive technical and scenario barriers.
In the future, Octo will continue with an open-source, open attitude, co-creating new collaboration paradigms for AI-Native organizations with developers, enterprise customers, and ecosystem partners, making trustworthy, controllable, and sustainable private Agentic AI truly land in every real work scenario.
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