Akira Labs

Building hardware-isolated micro-VM environments that make AI-generated code safe, verifiable and ready for execution. Get STARTED with Akira 👇

[Akira Labs @AkiraLabs01]

🚨Your AI agents can write production code. But can you actually run it safely?

Akira Labs is the trusted execution layer for
AI-generated code, VM-isolated sandboxes designed for autonomous agents, LLM workflows and untrusted scripts.

Beta access is opening. Get early access early [link in the first comment]!

[Akira Labs @AkiraLabs01]

Most infrastructure isn’t designed to run untrusted AI-generated code.

Traditional VMs provide strong isolation. Each VM runs its own kernel, so if something breaks or gets exploited, the blast radius stays contained.

The problem is speed.

VMs typically take 20–60 seconds to boot, which makes them impractical for interactive workflows where AI agents need to execute code inside reasoning loops.

MicroVMs change the equation.

When an agent sends code to our platform:
• a fresh MicroVM spins up in ~625ms
• the code runs inside its own isolated kernel
• crashes or exploits stay contained to that instance

This is what makes agentic workflows practical in production.

Agents can execute untrusted code safely without slowing down their reasoning loop.

Hardware-level security https://t.co/nKjKYxMr77

[Akira Labs @AkiraLabs01]

AI is writing more code than humans, yet most infrastructure still assumes the code being executed is trusted.

That assumption breaks down with AI-generated and agentic workloads.

When agents write and run code autonomously, you need execution environments that are secure by default.

Akira isolates execution at the hardware level, so developers don’t have to choose between speed, safety, and flexibility.

If you're building with Claud Code, OpenClow, or similar AI coding environments and running into issues with safely executing generated code, give Akira a try (link in bio).

It’s the execution layer built for the AI-native developer stack ⚡

[Akira Labs @AkiraLabs01]

OpenClaw hit 145k GitHub stars in <2 weeks.

180k+ deployments and full system access. But then security caught up.

What they found:
• One-click RCE (CVSS 8.8)
• 42k+ exposed instances
• 93.4% auth bypass
• 400+ malicious “skills”
• Top skill = silent data exfiltration

Palo Alto Networks called it a lethal trifecta: private data access, untrusted content, external comms and persistent memory.

This was predictable.

No isolation boundary means that every file, key and credential is reachable. Execution is the control surface.

That’s the problem we’re solving at Akira Labs.

We’re building the execution layer for AI agents.

Join the waitlist. Link in BIO!

[Akira Labs @AkiraLabs01]

GET BETA ACCESS ➡️https://t.co/pI06P6mzQR

[Akira Labs @AkiraLabs01]

🚨Your AI agents can write production code. But can you actually run it safely?

Akira Labs is the trusted execution layer for
AI-generated code, VM-isolated sandboxes designed for autonomous agents, LLM workflows and untrusted scripts.

Beta access is opening. Get early access early [link in the first comment]!

[Akira Labs @AkiraLabs01]

Every team building AI agents eventually hits the same wall: Where do you safely run the code your agents generate?

- Local execution is risky.
- Containers share kernels.
- VMs are too slow.

Akira Labs gives you instant, hardware-isolated MicroVM sandboxes, built for untrusted code and agentic workflows.

[Akira Labs @AkiraLabs01]

Deploying AI agents that execute code needs three things:

1. Safe execution for untrusted code
2. Fast enough performance for agent workflows
3. Infrastructure that doesn't need a DevOps team

Most teams build custom sandboxing infrastructure. It takes days of work and introduces new security risks.

Akira handles the execution layer through an API. Your agent calls run_code, we execute in isolated MicroVMs, and results come back in under a second.

Works with Claude, GPT-4, or any MCP-compatible model.

Deploy agents without building sandboxing infrastructure with https://t.co/hV3Li7LlEI

[Akira Labs @AkiraLabs01]

Running code you didn't write yourself requires a different security model than traditional DevOps.

Traditional approaches assume code passes review before execution. AI-generated code breaks that assumption completely.

Akira treats every execution as potentially hostile:
- Hardware isolation: each execution gets its own MicroVM with a separate kernel
- Resource limits: CPU, memory, and execution time are capped automatically
- Network isolation: MicroVMs can't access your internal network by default
- Audit logs: structured metadata captured for every execution

The security model is built into the platform. You don't configure isolation policies or manage infrastructure.
Your agent sends code, Akira handles the rest!

Explore more at https://t.co/vstsnlqfU6

[Akira Labs @AkiraLabs01]

Happy holidays from Akira Labs.🎄
We built Akira to solve a problem we kept running into: safely executing AI-generated code without building custom infrastructure.

Thanks to everyone who's tried the platform and shared feedback.
We are learning what works and what needs to improve.
More improvements coming in 2026.

[Akira Labs @AkiraLabs01]

In large organizations, agentic systems don’t fail on performance.

They fail in security review, because no one can explain the blast radius when agents behave unexpectedly.

[Akira Labs @AkiraLabs01]

This makes AI agents practical.
Your agent can execute untrusted code without slowing down its workflow. The isolation is strong enough for production. The speed is fast enough for interactive use.
Hardware-level security without the wait: https://t.co/X3xzWZTuH8

[Akira Labs @AkiraLabs01]

If you're running untrusted code, the choice matters. 🧵

[Akira Labs @AkiraLabs01]

How Akira uses MicroVMs?
Your agent sends code to our API. We spin up a fresh MicroVM in ~625ms. Code runs in its own isolated kernel.
If something tries to escape, it's trapped in that VM. If the code crashes, only that MicroVM is affected.

[Akira Labs @AkiraLabs01]

AI is writing more code than humans, but our infrastructure still assumes the code is trustworthy.

That assumption breaks in the era of AI-generated and agentic workloads.

Akira Labs isolates execution at the hardware level so teams don’t have to choose between speed and safety.

This is the foundation of AI-native infrastructure.

[Akira Labs @AkiraLabs01]

@XIX1909 Exactly. 🔥

[Akira Labs @AkiraLabs01]

Hello, world! We are Akira Labs.

AI can write code, but running that code safely is still a nightmare.
Containers share kernels, VMs are slow, and running code locally just isn't safe.

We built Akira to fix these problems.
Akira gives you isolated MicroVM sandboxes through an API and proper isolation without the infrastructure headache.

This is just the beginning.
Stay tuned as we open up the next layer of infrastructure for AI-native development.

[Akira Labs @AkiraLabs01]

Why developers choose MicroVMs over containers:
Each sandbox gets its own kernel. If something breaks or gets exploited, it gets isolated at the hardware level.

Akira Labs currently supports Python and TypeScript, with more languages coming based on what developers need.

You call an API, we handle the isolation.
https://t.co/hV3Li7KNPa