Advancing science and engineering with Antigravity's /teamwork

Related: I've been finding a lot of success (defined as more autonomy with less quality dropoff) with team-based workflows.

A lot of evidence for this.

- Adaptive Auto-Harness: Sustained Self-Improvement for Agentic System Deployment on Open-Ended Task Streams (https://arxiv.org/abs/2606.01770) talks about multi-agent, role-based adaptive harnesses collaborating on non-homogeneous workstreams

- team-solve (https://github.com/guregodevo/memdoor/tree/main/examples/wor...) team of small models beats Fable on LiveCodeBench

- Agensh paper (https://arxiv.org/html/2609.26781v1) also talks about "role-playing agents to study autonomous cooperation"

All show that role-based, multi-agent setups improve performance.

It is not clear to me how or if /teamwork is any different than Claude dynamic workflows.

Antigravity as a harness feels very behind. There's not even any auto mode. And they announced /goal long after I ever felt the need to use it in CC or Codex.

This doesn't tell me how to use it.

As noted by others, we already announced parts of /teamwork in Antigravity here: https://antigravity.google/blog/teamwork-when-ai-becomes-a-r... with more visualizations and more. Thi post was meant to report some advances in math/science/coding/engineering to show-case examples of tasks you can do with it.

We are constantly improving/evolving /teamwork and pushing those changes for external users. Will also post more about improvements and details for building teams of agents dynamically as Antigravity blog posts soon. Stay tuned!

Also I added a list of examples here: https://x.com/mirrokni/status/2121351383236436247?a=ma9UPZg_... and https://lnkd.in/p/esVTpR6p. I'll add a comment with examples as well.

The amount of breakthroughs this could deliver. Previously we should’ve established R&D departments, prepare multi-cultural teams, all to work on a single project. Today? I can see a domain expert, guiding antigravity and delivering fast.

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I think the authors also used Antigravity to write this article, because it sucks at communicating whatever point it’s trying to make. I think it’s something like “We did the OpenAI 100 problems thing, but across many disciplines, and in collaboration with the experts instead of just dumping results on the world, and we also made the tooling feature available,” but I’m not sure because it has that distinct Gemini flavor of packing in so many low-level details that the actual point becomes entirely obscured.

Google is missing LLMs the way that Microsoft and Intel missed cell phones.

Sloppification is now called "advancing". That may even be innovative.

Interesting that a Rust re-write pre optimisation was 30% slower than the C++ equivalent.

I wonder if they optimised the C++ it would actually have more speed benefits than the Rust alternative. Only they can't claim it's a Rust rewrite like every other company at the moment.

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