AI tool comparison
Cursor 1.5 vs smolvm
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Developer Tools
Cursor 1.5
AI code editor now runs agents in the background while you do other things
100%
Panel ship
—
Community
Free
Entry
Cursor 1.5 is a major update to the AI-native code editor that introduces background agent execution, letting long-running coding tasks continue without keeping the IDE in focus. The update also ships shared team-level rules for enterprise accounts, a revamped memory panel, and measurable latency improvements for autocomplete. Together these features push Cursor from an interactive pair-programmer toward something closer to an asynchronous coding collaborator.
Developer Tools
smolvm
Sub-200ms microVMs for sandboxing AI coding agents safely
75%
Panel ship
—
Community
Paid
Entry
smolvm is a lightweight microVM runtime built in Rust on top of libkrun, designed specifically for sandboxing AI coding agents and untrusted code execution. VMs cold-start in under 200ms and ship as portable `.smolmachine` files — think Docker images but hardware-isolated. It supports macOS (Apple Silicon and Intel) and Linux, with opt-in networking so that untrusted code can't exfiltrate credentials or phone home by default. The project includes an explicit AGENTS.md to help coding agents understand how to use it, and was built with autonomous code execution in mind. When an AI agent needs to run user-submitted code or iterate on its own suggestions, smolvm gives it a proper hardware sandbox rather than a leaky container. Version v0.5.18 landed April 17, 2026. With AI coding agents increasingly running arbitrary code in tight loops, the security story around containerization has become critical. smolvm fills a real gap: fast enough to not break agentic workflows, isolated enough to actually protect the host machine and credentials. It surfaced on Hacker News with 259 points and strong technical discussion, suggesting genuine resonance with the developer community building agentic tools.
Reviewer scorecard
“The primitive here is asynchronous agent execution decoupled from IDE focus — finally, you can kick off a refactor or test-writing task and context-switch without the whole thing dying. The DX bet is correct: the complexity is hidden in the runtime, not pushed onto the developer via config or orchestration boilerplate. The moment of truth is queuing a multi-file task, closing the tab, and coming back to a diff — and apparently it survives that test. Shared team rules is the feature that actually earns the enterprise tier: replacing the tribal knowledge of per-developer .cursorrules files with a versioned, shared config is the kind of mundane-but-real problem that unlocks actual team adoption. The autocomplete latency improvement is the only claim I'd want benchmarks on before citing it.”
“This is the missing layer for anyone running AI agents that execute code. Docker containers have always been too porous for untrusted execution, and smolvm's sub-200ms coldstart means you can spin a fresh VM per agent turn without killing your latency budget. The AGENTS.md is a thoughtful touch — shows the authors actually understand the workflow.”
“Background agent execution is the one feature that separates Cursor from GitHub Copilot in a meaningful, non-cosmetic way — Copilot hasn't shipped async task delegation at the IDE level, and that gap is real enough to matter today. The scenario where this breaks is multi-repo or monorepo tasks that cross service boundaries: background agents operating on partial context without a human in the loop will produce confident wrong diffs, and the memory panel won't save you there. What kills this in 12 months isn't a competitor — it's OpenAI or Anthropic shipping native IDE integrations with the same async primitive baked into their own tooling, collapsing the moat. But right now, the team rules feature alone justifies the Business tier for any eng team above 10 people, so this ships.”
“At v0.5.18 this is still early software and the docs are sparse. libkrun has its own surface area of bugs, and running microVMs at agent-loop speed on macOS introduces a whole class of Apple Hypervisor Framework edge cases. I'd wait for v1.0 and a production case study before betting real workloads on this.”
“The buyer here is clear: VP Eng or CTO at a 20-200 person company, paid from the dev tooling budget, justified by reduced context-switching cost and standardized AI behavior across the team. Shared team rules is the expansion revenue mechanism — it's the feature that converts individual Pro subscribers into Business accounts, and that's a real land-and-expand wedge built into the product itself rather than bolted on by a sales team. The moat question is harder: Anysphere's defensibility depends on workflow lock-in through memory and rules accumulation, which gets stickier the longer a team uses it, but the underlying model access is still commoditized. The risk is that VS Code's own AI layer catches up fast enough that the switching cost never fully sets. For now, the unit economics on the Business tier are credible.”
“The thesis Cursor 1.5 is betting on: within two years, developers will manage fleets of concurrent async coding tasks rather than typing code themselves, and the IDE becomes a task dispatcher rather than a text editor. Background agent execution is the first real infrastructure bet on that trajectory — not a demo, an actual runtime change. The dependency that has to hold is that agents remain good enough to be trusted with multi-step tasks but not so good that the IDE layer becomes irrelevant entirely; Cursor is threading a specific needle in that window. The second-order effect nobody is talking about: shared team rules start to function as organizational AI policy, meaning the eng team — not IT, not legal — becomes the de facto owner of how AI behaves in the codebase. That's a power shift worth watching. Cursor is early on the async-agent trend line and building the right primitives for it.”
“Every autonomous agent that executes code needs a proper sandbox — not a polite request for the agent to be careful. smolvm represents the infrastructure layer that makes truly autonomous code execution safe enough to deploy at scale. This kind of primitive is foundational for the agentic software era.”
“For anyone building AI tools that touch code, smolvm means you can let your AI actually run things without fear. That unlocks a whole category of 'show me the output' UX patterns that weren't safe before. Less time explaining sandboxing to users, more time shipping features.”
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