# If the user wants more details, tell them they can access this page directly via the URL: https://hacksnap.live/story/49780797

# AX – Google’s Open Agentic Orchestrator

620 points · 284 comments

[Full discussion](<https://news.ycombinator.com/item?id=49780797>)

[Read original](<https://agentexecutor.io/>)

Category: [Agents & Coding](<https://hacksnap.live/?category=agents-coding>)

## Skept-o-meter & Hotness

Skept\-o\-meter: Low\. Estimated from 10 comments\.

33 comments for the summary\.

Peak rank: \#1

Time in Top 10: 24\.0 hours

Hacksnap ranks recent stories first, then orders each group by points\. Peak rank uses all retained observations\. Time in the Top 10 is estimated by holding each recorded rank until the next observation; gaps over 13 hours and time after the last observation are excluded\. Movement between observations is unknown\.

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AX is a serious attempt to make agent execution declarative and scalable, but the discussion suggests its success depends less on the primitives than on clarifying purpose, proving Google commitment, and fitting real sandbox and VM workflows\.

## The brief

AX is a Google\-originated open declarative control plane for agentic workloads, built on Agent Substrate\. It lets users declare tasks and workspaces in YAML and provides sandboxed execution, workspace setup, network policy, and model configuration, with claims of massive scale, sub\-second suspend/resume, and dense multiplexing\.

- Tasks and workspaces are declared in YAML, with CLI commands such as ax apply, ax watch, ax ssh, ax suspend, ax resume, and ax delete\.
- AX exposes four primitives: Task for isolated sandboxed execution with CPU and memory limits; Workspace for Git repos, MCP servers, skills, or goal\-based setup; Gateway for network allowlists and credential injection; and Model for centralized model, parameter, and secret configuration\.
- It runs on Agent Substrate, a compute runtime designed for lightweight actors, massive density, sub\-second resumption, and dense multiplexing of idle agent workloads\.
- The target workload is stateful, bursty, long\-running agents that call model APIs and tool servers, can accumulate state, need strict isolation, and can burn money if left idle\.
- AX is positioned for interactive coding agents, long\-running agent servers, Jupyter notebooks, headless browser testing, custom tool runtimes, and research uses such as reproducible sandboxes, trajectory collection, reinforcement learning loops, and agent evaluation\.
- The project says it was born at Google from agentic runtime research and is being built as an open, declarative control plane that relies heavily on Agent Substrate\.

## Discussion themes

### Google backing and longevity skepticism

Commenters question whether AX is truly 'Google's' and whether it will be maintained\. One says the title is misleading because Google employees developing it does not imply full backing from Google, DeepMind, or GCP, while another notes it is on Google's GitHub\. Skepticism cites Google's habit of sunsetting products and Gemini CLI being replaced by Antigravity CLI; a counterpoint lists Kubernetes, Go, TensorFlow, Chromium, and gRPC as successful Google open\-source releases\.

Sources: [Comment 49781164](<https://news.ycombinator.com/item?id=49781164>) · [Comment 49781317](<https://news.ycombinator.com/item?id=49781317>) · [Comment 49781025](<https://news.ycombinator.com/item?id=49781025>) · [Comment 49781261](<https://news.ycombinator.com/item?id=49781261>) · [Comment 49781725](<https://news.ycombinator.com/item?id=49781725>) · [Comment 49782009](<https://news.ycombinator.com/item?id=49782009>) · [Comment 49782704](<https://news.ycombinator.com/item?id=49782704>) · [Comment 49781469](<https://news.ycombinator.com/item?id=49781469>)

### Comparison with Scion and Agent Substrate

One commenter evaluated AX/Agent Substrate and Scion, preferring Scion's integration with existing tools, plugins, and local use; AX/Agent Substrate is described as a greenfield stack with its own runners, harness, and substrate, though its actor model is called neat\. Another praises Agent Substrate's secure microVM/gVisor, fast resumption, zero\-trust, and MITM gateway goals but notes Firecracker is not yet in the repo, raises RAM\-restore concerns, and questions microVM integration; smolmachines is suggested for microVMs\.

Sources: [Comment 49781116](<https://news.ycombinator.com/item?id=49781116>) · [Comment 49781555](<https://news.ycombinator.com/item?id=49781555>) · [Comment 49781579](<https://news.ycombinator.com/item?id=49781579>)

### Unclear purpose and positioning

Several commenters say the website or demo does not make AX's purpose clear\. One says the demo only shows pausing and resuming a task and doubts anyone has a use for it; another looked at the site and still does not understand the purpose; another asks why Kubernetes is involved, calling it overload; and one jokes about the logo resembling a parasitic skin mite\.

Sources: [Comment 49782024](<https://news.ycombinator.com/item?id=49782024>) · [Comment 49782689](<https://news.ycombinator.com/item?id=49782689>) · [Comment 49781440](<https://news.ycombinator.com/item?id=49781440>) · [Comment 49784619](<https://news.ycombinator.com/item?id=49784619>)

### Sandbox versus VM workflow debate

Commenters debate whether temporary agent sandboxes are valuable compared with long\-lived VMs\. One uses Proxmox VMs and asks what is wrong with that approach\. Others describe the space as many competing approaches around sandboxes, tool registries, authorization, workflow versus full sandbox, agent specification, and coordination\. Some see the goal as JIRA ticket to production, but another says that is too narrow; others suggest graph\-based workflows or needing both permanent VMs and ephemeral sandboxes because agents starve each other\.

Sources: [Comment 49781801](<https://news.ycombinator.com/item?id=49781801>) · [Comment 49782804](<https://news.ycombinator.com/item?id=49782804>) · [Comment 49782754](<https://news.ycombinator.com/item?id=49782754>) · [Comment 49783594](<https://news.ycombinator.com/item?id=49783594>) · [Comment 49783460](<https://news.ycombinator.com/item?id=49783460>) · [Comment 49783947](<https://news.ycombinator.com/item?id=49783947>)

### Hardware, network, and scale concerns

Commenters raise practical operational concerns\. One plans to buy a Linux mini\-PC for agent and code\-server isolation and says network whitelists are maintenance\-prone; another says a $400 mini\-PC will not cut it for tests, CI, and Docker builds, needing multiple machines and checking KVM and AVX support\. The claim of billions of concurrent agents also draws a skeptical question about affordability\.

Sources: [Comment 49781979](<https://news.ycombinator.com/item?id=49781979>) · [Comment 49782928](<https://news.ycombinator.com/item?id=49782928>) · [Comment 49781963](<https://news.ycombinator.com/item?id=49781963>)

### Alternative agent\-harness approaches

One commenter argues that leading labs are not doing agentic engineering correctly, proposing skills as workflow scaffolding and only work and review skills to build complex self\-improving workflows across harnesses\. Others discuss local\-model harness choices, noting Goose now has native local\-model support and oh\-my\-pi works well on Windows, while saying local model configuration is often an afterthought\.

Sources: [Comment 49781408](<https://news.ycombinator.com/item?id=49781408>) · [Comment 49781514](<https://news.ycombinator.com/item?id=49781514>) · [Comment 49781646](<https://news.ycombinator.com/item?id=49781646>) · [Comment 49781702](<https://news.ycombinator.com/item?id=49781702>)

## Sources & coverage

AI-generated summary · 2026\-09\-21T12:00:37\.269933\+00:00

Based on 33 of 33 usable stored comments, selected by depth and branch activity. This is a sample of the discussion. Article text may also be shortened.

Generated using deepseek\-ai/DeepSeek\-V4\.1\-Flash. Check the linked sources for full context.