Every Sandboxes & Runtime comparison and buyer's guide for building AI agents — 19 pieces and counting. Each is a head-to-head or a “best X for Y” roundup with a sources-backed verdict.
OpenClaw runs on your own machine, so it feels private and therefore safe. The security crisis of the last three months is a lesson in why those are not the same thing — self-hosting moved the data, not the trust boundary.
Microsoft's new agent runtime scales to zero like a serverless function but keeps the filesystem and a machine identity — quietly moving the lock-in from your framework down to the sandbox your agent lives in.
Foundry Hosted Agents reached GA in early July 2026 as a framework-agnostic runtime. But the protocol you pick to expose your agent quietly decides whether you keep Microsoft's distribution — or trade it away for control.
Both give your agent exactly-once, resume-after-crash workflows. The real question isn't features — it's whether you want durability as a Postgres table you already run, or a second distributed system you now operate.
There are two ways to make an agent survive a crash, and they fail in opposite directions. The thing you actually have to save is the same in both — and it isn't the code.
Firecracker gives each agent a whole Linux to boot — 125 ms of it. Hyperlight keeps the hardware wall and throws away the OS behind it, and that deletion is what makes per-tool-call isolation affordable.
All three move messages between agents. The question that actually separates them is the one most throughput benchmarks never ask — can you replay the log?
All three hyperscalers now sell a managed home for your agent. Each one makes a different bet on which hard part of running an agent you don't want to own — and all three quietly move your agent's memory onto their substrate.
An agent has no ROLLBACK: when step three fails, the first two already happened in the world. The fix is a compensating undo for every tool — and putting the one you can't undo last.
An agent isn't a stateless web service — it's a long-running, resumable process. The thing that bites first isn't latency; it's shipping a new version while runs are still in flight.
The choice isn't speed versus security. It's whether the model is writing code that orchestrates your tools or code that needs the whole operating system — and that picks the security model for you.
The way you start an agent — schedule, HTTP event, or message queue — decides its retry, durability, and concurrency behavior more than the framework you write it in does.
Durable execution and checkpointing give you at-least-once replay, which is strictly worse for side-effecting tools — unless you attach a stable idempotency key before the call, not after the crash.
Three ways to keep an agent's untrusted code off your host kernel — and why the right choice is a triangle of compatibility, cold-start speed, and operational weight, not a security ranking.
Amazon's agent platform sells you everything except the agent. Here is what the seven services actually do, what the numbers mean, and why the neutrality is the whole strategy.
The three managed agent runtimes don't really compete on price or region. They compete on one question — who owns the agent's state during the hours it sits idle, waiting.
Once you've fine-tuned a model, you need a GPU to serve it from. The four serverless platforms developers reach for disagree about one thing that follows you for years — the format you package the model in.
Three "agent sandboxes," three different machines underneath. Choose by your latency-and-lifetime profile and your isolation primitive, not by the feature grid.
Every agent that runs longer than a single request eventually crashes mid-thought. The engine you pick to survive that crash decides how you're allowed to write the loop.
Not buyer's guides — the news, teardowns, and explainers behind this topic.