Jonathon's AI Wiki

DLAM — Rabbit's Plug-and-Play Computer Agent

7 min read

Source: Rabbit Tech First Major Update 2026 (2026-01-29), Rabbit Tech Get Started Using DLAM on r1 (2026-01-31), Rabbit Tech Introducing DLAM Shortcuts (2026-02-27)

DLAM is Rabbit’s general-purpose desktop AI agent — a “plug-and-play computer controller” that pairs an R1 device over USB-C with a Chrome/Edge browser session and lets the user voice-control any Windows or Mac computer through a screen-shared agent. Setup takes a single browser tab visit at dlam.rabbit.tech and a USB cable. February 2026 added DLAM Shortcuts — three-field (name + description + body) reusable command templates that auto-trigger when relevant to a request, addressing the “agents don’t always follow the most efficient paths” problem. DLAM is the consumer-hardware analog of Anthropic’s Computer Use — same idea (agent autonomously drives a desktop), different deployment surface (USB-tethered consumer device + browser screen-share, vs API + sandbox + VM).

Key Takeaways

  • “Plug-and-play computer controller meant for users of all technical levels — no setup required.” Rabbit’s January 29 2026 launch framing. The agent uses the R1 only as the input device; the actual computer-driving happens in the browser via screen-share. Chrome or Edge required (no Firefox/Safari support announced).
  • Setup is six steps and zero downloads.
    1. Open Chrome or Edge.
    2. Go to https://dlam.rabbit.tech/ and authenticate with rabbithole credentials.
    3. Grant microphone permission.
    4. Click the screen-share icon (bottom right) and share your entire screen.
    5. Plug R1 into the computer via USB-C.
    6. Pick the R1 in the connect popup. Done.
  • Two interaction modes. Voice (unmute the mic) or text (keyboard icon). The R1 is the voice input device; you can also type from the browser. Same agent on the back end either way.
  • Capability surface. Per Rabbit’s launch:
    • Browser actions (online shopping cited as an example).
    • Multi-application workflows combining research and document creation.
    • Complex software control — Rabbit specifically called out “music production setup” as a tested case.
    • Gaming scenarios — Rabbit reported successful testing in gaming, suggesting general window-manipulation and game-input support (unusual claim for a computer-use agent in early 2026).
  • DLAM Shortcuts (February 27 2026 launch). Three-field structure:
    • Name — user-defined title.
    • Description — context about what the shortcut does (used by DLAM to decide when to trigger).
    • Body — detailed instructions DLAM executes when the shortcut activates. Once created, shortcuts trigger automatically when the user’s request matches the description — they don’t have to be invoked by name. This is closer to Claude Skills’ invocation model (auto-fire on relevance) than to traditional macros.
  • Real-world Shortcut examples Rabbit ships in their launch post.
    • Daily news briefing — open Chrome → BBC News → summarize top stories → email the brief.
    • Dev workflow — connect to IDE → review recent commits → deploy to GitHub.
    • Creative project setup — open Ableton Live with preferred templates and plugin configurations.
    • Multi-app task chain — extract from spreadsheet → generate report → format → distribute.
  • 16:9 widescreen optimized. Stated explicitly: “DLAM is optimized for 16:9 widescreen monitors. Other aspect ratios may not work optimally.” Vision/grounding presumably trained on standard widescreen resolutions; ultrawide / vertical / 4:3 monitors degrade.
  • Multi-monitor caveats. Windows: share the primary display. macOS: ensure the mouse pointer stays on the shared screen (DLAM only sees the shared display, so mouse drift to a non-shared monitor causes the agent to lose track of cursor state).
  • Free trial at launch. January 29 2026 announcement positioned DLAM as “free trial” with the explicit acknowledgement that “the agent remains in early stages and will continue improving its speed and reliability.” No public pricing tier announced as of the May 2026 fetch.
  • Compared to OpenClaw on R1. DLAM is Rabbit’s own first-party agent — minimal setup (browser tab + USB cable), narrower capability (one desktop, voice from R1), supported by Rabbit. OpenClaw on R1 is third-party, requires self-hosted gateway, broader capability (your own multi-agent fleet), explicitly unsupported. Different trade-off curves; both available on the same device.

Where this fits in agent surface taxonomy

  • vs Anthropic Computer Use — Same idea (agent drives desktop), different surface. Computer Use runs API-driven inside a sandbox VM with the developer’s code calling it. DLAM is end-user-driven via browser screen-share with R1 voice input. Computer Use is for application developers building agent products; DLAM is for users running the agent on their own machine.
  • vs browser-harness — Browser-harness is Anthropic’s research-mode browser-only agent surface. DLAM screen-shares the entire desktop, not just one tab — broader scope.
  • vs Cowork + Apify — Apify scrapes via cloud-hosted browsers. DLAM controls the user’s own browser (and the rest of the user’s apps). Different cost model — Apify per page, DLAM per minute of agent runtime.
  • vs DLAM-via-CLI on the upcoming Cyberdeck — Rabbit’s pre-released cyberdeck (announced same January 29 2026 post) is positioned for “CLI and native agent applications,” implying DLAM or its descendant might run natively on the device rather than tethered to a host computer. Different architecture entirely; worth watching.
  • DLAM Shortcuts vs Claude Skills. Both auto-trigger on description match. Both are user-defined reusable units. Skills are SKILL.md files installed to ~/.claude/skills/; DLAM Shortcuts are stored in Rabbit’s cloud and tied to the rabbithole account. Skills are filesystem-portable; Shortcuts are not.

Implementation

  • Tool/Service: DLAM (Deep Learning Action Model) — Rabbit’s general computer agent.
  • Setup:
    • Browser: Chrome or Edge only.
    • URL: https://dlam.rabbit.tech/ (rabbithole login).
    • Hardware: Rabbit R1, USB-C cable, computer (Win or Mac), 16:9 monitor preferred.
  • Cost: Free trial as of January 29 2026 launch; no announced pricing tier as of fetch.
  • Integration notes:
    • Vertical / ultrawide / 4:3 monitors: degrades.
    • Multi-monitor on Windows: must share primary display.
    • Multi-monitor on macOS: keep mouse pointer on shared screen.
    • The R1 is only the voice input. The agent runs server-side in Rabbit’s cloud, screen-shares your computer back, and drives your computer via screen-share + cursor control.
    • Network failure on R1 or rabbit.tech = DLAM session interrupted.
  • DLAM Shortcuts setup:
    • With R1 USB-C connected and authenticated to dlam.rabbit.tech, click the gear icon (bottom left) for shortcuts.
    • Create a new shortcut with name + description + body.
    • Refresh to activate. The shortcut fires automatically when a user request matches the description.

Open Questions

  • Privacy model. DLAM screen-shares the user’s entire desktop to Rabbit’s cloud. What’s logged, retained, used for training? No published privacy policy specifically for DLAM screen-share traffic.
  • Latency. Sub-second cursor responsiveness or noticeably laggy? No published benchmarks. The “music production setup” claim implies sub-second is achievable; user reports on r/Rabbitr1 mostly haven’t covered DLAM specifically yet.
  • Linux support. Win + Mac only as of launch. No Linux mentioned.
  • Persistence. Shortcuts: stored where? Locally on the R1, in rabbithole, or both? Are they synced across multiple R1s on the same account?
  • Failure recovery. When DLAM gets confused (wrong window focus, modal dialog, captcha), what’s the recovery flow? Voice intervention from R1, pause-and-take-over, full restart?

Try It

  1. First-time DLAM session. With your R1 charged and on the latest OS, plug into a Mac or Windows machine via USB-C. Open Chrome → dlam.rabbit.tech → log in → grant mic → share entire screen → plug in R1 → connect.
  2. Try a low-stakes voice task. Hold to talk on R1: “Open my calendar for this week.” Watch the agent drive your browser. Get a feel for latency and accuracy.
  3. Create one DLAM Shortcut. Pick a workflow you do daily — e.g., “morning brief” (open three tabs you always open). Name + description + body, save, refresh. Then see if it auto-fires when you say “give me my morning brief.”
  4. Test the rough edges. Try a workflow that crosses two apps. Try one in a non-16:9 window. Try with a captcha. Document the failure modes.
  5. If you also use Anthropic Computer Use, run the same task in both to compare. Computer Use needs API + code; DLAM needs USB + browser. Note where each shines.

Graph View

Backlinks