Guanlan Dai

Runta

@guanlan

Building @Runta, the execution layer that controls what AI agents can actually do. Prev @Cloudflare and @Kong.

San Francisco, CA runta.com Joined January 2010

483 Following 6.7K Followers 415 Posts

Latest posts 5

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Guanlan Dai @guanlan Jul 16

Today we're announcing @runta's $20M seed, led by @a16z.
Software is constrained when you write it. Agents have to be constrained while they run.
Runta is the execution layer that controls what AI agents can actually do.

1:23

Guanlan Dai @guanlan 1d

We’re spending up to 100B tokens across 26,040 agent runs to answer one question: when you switch models, should you switch harnesses too?

Our v1.0 FrontierHarness leaderboard ranked harnesses on a single model.
V1.1 expands it to 21 harnesses × 5 models × 62 tasks × 4 attempts, 72x the size of v1.0.

Results are coming in live. Link below🧵

0:09

Guanlan Dai @guanlan Nov 4

@Runta's Singapore office is open! 🇸🇬

Six months of preparation. Skipped the cramped high-rises for a green, light-filled workspace.

Hiring for agent infra team for both SG and US:
* Infra Engineer (FaaS / container scheduling / virtualization / RL infra)
* Product Engineer (build in public, open-source, community, design sense)

DM me if you’re into agent infrastructure.

Guanlan Dai @guanlan Oct 30

Finally caught up with an old friend @evanyou at Singapore.

His take on API design for agents: humans love aliases and shortcuts; agents want one canonical way to do each thing. ASTs built for human readability can give way to flat memory representations that are orders of magnitude faster.

Consistency beats convenience when the caller is an agent.

Thanks @hunvreus for hosting and photo.

Guanlan Dai @guanlan Oct 21

Great effort has been putting in this project. Glad to see it's reached the 1.0 milestone.

Yifan Xu Verified account @yifanxu_ephai Oct 21

LayerFS v1.0.0 is out 🎉 Open-source (MIT)

Recursive filesystem for AI agents.

6 core ideas:

1. Ephemeral computing: agents spend ~80% thinking, so each Bash call mounts a Workspace, then commits
2. Decentralized agents: every agent commits to one Store, no DB server
3. Multiagent coordination: every tool call is a Commit; same-file clashes refused
4. Recursive filesystem: forks copy no files, at any depth
5. Ultra storage: dedup, then compression: 10 copies → 0.31
6. Instant bootstrap: ignored files stay in every Commit. ~5 min install vs 0.05 s mount

And 4 more:

7. Auto checkpoints: fork from any step
8. Append-only objects: content-addressed, never rewritten
9. .lww: lockfiles and caches take the newest edit
10. Big file, small edit: a write keeps only its bytes

Here are our links:

github: github.com/Ephemeral-AI-L…
website: layerfs.ai

Watch the video below, and have Fun!!!

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