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Field notes on building, running, and governing AI agents that do real work — from the team building the Machine command center.

QM×Machine
Comparisons

Machine vs QM: two open agent platforms, two different units of work

QM and Machine both give teams persistent agents, isolated computers, Slack and web access, and self-hosting. The decisive difference is deeper: QM organizes work around people and rooms; Machine organizes it around git-backed projects and reviewable sessions.

RC
Ross Cohen·August 2, 2026·11 min read
Machine
Vision

The only moat that matters: why your AI platform needs a learning loop, not a better model

Every AI product is converging on the same architecture. The only defensible advantage is a data flywheel — a learning loop where every interaction makes your system better. Here is what that means, and why Machine is built for it.

RC
Ross Cohen·August 2, 2026·10 min read
Machine
Vision

Your company needs two kinds of capital: human and token

Satya Nadella’s frontier-ecosystem framework reveals the most important strategic idea in AI: every company must build human capital and token capital, and they compound together.

RC
Ross Cohen·August 2, 2026·8 min read
Machine
Architecture

The test of sovereignty: can you swap the model without losing what you built?

The most important question for any company adopting AI: can you switch out the model without losing the institutional expertise you have built? A sovereignty checklist for evaluating your AI platform.

RC
Ross Cohen·August 2, 2026·7 min read
Machine
Architecture

Static software is dead: the shift from code to feedback loops

The way we build software is fundamentally changing. Static software no longer creates a defensible advantage. The shift is to dynamic software that improves through feedback loops.

RC
Ross Cohen·August 2, 2026·7 min read
Machine
Market

Every AI product is the same: the convergence nobody is talking about

Open any agent platform — they are architecturally identical. The marginal differences are not defensible. The only thing that diverges is the learning loop.

RC
Ross Cohen·August 2, 2026·5 min read
Machine
Vision

A frontier without an ecosystem is not stable

The first phase of globalization hollowed out industrial economies. The AI era cannot repeat that. The priority has to be building a frontier ecosystem, not just a frontier model.

RC
Ross Cohen·August 2, 2026·7 min read
Machine
Strategy

Good businesses don’t need moats (and why that’s fine)

The startup world is obsessed with moats. Every pitch deck has a slide. Every investor asks. But most great businesses do not have a true moat, and they are still great businesses.

RC
Ross Cohen·August 2, 2026·6 min read
Machine
Product

What Machine actually is: the AI Management System, layer by layer

One git repo is the source of truth for the agents, the skills, the memory and the connector config. Every session gets its own isolated machine and its own branch. Any model, your keys. Work lands through a change request. Self-hosted or managed cloud. The long version of that sentence.

RC
Ross Cohen·July 31, 2026·11 min read
Poetic×Machine
Comparisons

Machine vs Poetic: both turn workflows into code — the difference is who owns the code

Poetic compiles your procedures into a purpose-built language it runs for you. Machine keeps the workflow as ordinary code in a repo you own, and gates the boundary where it touches the world. A technical comparison of two answers to the same problem.

RC
Ross Cohen·July 31, 2026·9 min read
Machine
Architecture

AGI-ready architecture: what it really means, and how Machine is built for it

AGI-ready doesn't mean an architecture that produces AGI. It means one that absorbs a 100× capability jump without losing state or granting uncontrolled access. How Machine is built for it.

RC
Ross Cohen·July 17, 2026·9 min read
Glean×Machine
Comparisons

Machine vs Glean: search or an agent platform that runs work?

Glean is the best permission-aware enterprise search. But search finds work — it doesn't do it. Here's where you outgrow it, and the open runtime alternative.

Machine Team·July 13, 2026·5 min read
Machine
Security

How to give AI agents tool access safely

How to give AI agents production tool access without raw API keys: scoped connectors, approval policies, server-side credentials, and reviewed work.

Machine Team·July 7, 2026·7 min read
Machine
Enterprise

AI transformation needs a company OS

Why consultancies and AI-transformation teams need one Git-backed workspace for agents, memory, connectors, policy, and auditable work.

Machine Team·June 29, 2026·6 min read
Claude×Machine
Comparisons

Machine vs Claude Cowork: a desktop assistant, or a company-wide agent platform?

Claude Cowork is the best agent on the desktop. But it runs one assistant per person, on Anthropic's models, with your data on their cloud. Here's where you outgrow it — and what an open, company-wide agent platform looks like.

RC
Ross Cohen·June 29, 2026·4 min read
Hermes×Machine
Comparisons

Personal AI agents vs a company OS: Machine, OpenClaw, and Hermes

OpenClaw and Hermes are capable personal agents. But a personal "Jarvis" and a governed company platform are different things. Here is exactly where the line is.

Machine Team·June 28, 2026·4 min read
ChatGPTClaudeGrok×Machine
Comparisons

Beyond the chat box: why ChatGPT, Claude, and Grok aren't an AI workforce

Chat assistants answer; a workforce does the work. Why input-output tools — however brilliant — aren’t the same as a fleet of agents that run your company, own the data, and run on any model.

Machine Team·June 27, 2026·4 min read
Machine
Product

Introducing Machine: the AI command center for your company

A workforce of AI agents that do real work across your tools — defined as files in a git repo, run in isolated sandboxes, governed by review, and built enterprise-first. Here is the whole thing, A to Z.

RC
Ross Cohen·June 6, 2026·7 min read

Run your whole company from one repo you own.

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