Docker, Adobe & tldraw: Where Should Your Agent Run?
The discussion explores the critical architectural question of where AI coding agents should execute, presenting four distinct models: Docker advocates for secure microVM sandboxes; Helix ML proposes centralized, dedicated computing resources for each agent; Adobe demonstrates running the agent loop entirely within the browser tab; and tldraw visualizes agents collaborating as characters on an infinite canvas. The consensus highlights the trade-offs between isolation, centralized control, and environmental fidelity.
Key takeaways
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MicroVMs for Agent Sandboxes
0:09
Docker recommends using micro VMs instead of traditional containers for agent sandboxes because enterprise security teams view shared kernels as an unacceptable isolation boundary.
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Centralized Agent Infrastructure
3:03
Helix ML argues for giving every agent its own dedicated computer on centralized infrastructure (e.g., Kubernetes) to facilitate seamless handoffs of work across global time zones.
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Browser-Native Agent Loops
7:33
Adobe demonstrated an agent that runs its entire loop and controls the browser from within the browser tab, showcasing the concept of the 'self-licking ice cream cone' (SLICC).
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Collaborative Canvas Agents
6:13
tldraw presents agents as interactive characters on a canvas that can coordinate, plan, and execute tasks as a team, allowing for simultaneous, visible collaboration.
